research topics neuroscience

Research Topics & Ideas: Neuroscience

50 Topic Ideas To Kickstart Your Research Project

If you’re just starting out exploring neuroscience-related topics for your dissertation, thesis or research project, you’ve come to the right place. In this post, we’ll help kickstart your research by providing a hearty list of neuroscience-related research ideas , including examples from recent studies.

PS – This is just the start…

We know it’s exciting to run through a list of research topics, but please keep in mind that this list is just a starting point . These topic ideas provided here are intentionally broad and generic , so keep in mind that you will need to develop them further. Nevertheless, they should inspire some ideas for your project.

To develop a suitable research topic, you’ll need to identify a clear and convincing research gap , and a viable plan to fill that gap. If this sounds foreign to you, check out our free research topic webinar that explores how to find and refine a high-quality research topic, from scratch. Alternatively, consider our 1-on-1 coaching service .

Neuroscience-Related Research Topics

Investigating the neural mechanisms underlying memory consolidation during sleep.
The role of neuroplasticity in recovery from traumatic brain injury.
Analyzing the impact of chronic stress on hippocampal function.
The neural correlates of anxiety disorders: A functional MRI study.
Investigating the effects of meditation on brain structure and function in mindfulness practitioners.
The role of the gut-brain axis in the development of neurodegenerative diseases.
Analyzing the neurobiological basis of addiction and its implications for treatment.
The impact of prenatal exposure to environmental toxins on neurodevelopment.
Investigating gender differences in brain aging and the risk of Alzheimer’s disease.
The neural mechanisms of pain perception and its modulation by psychological factors.
Analyzing the effects of bilingualism on cognitive flexibility and brain aging.
The role of the endocannabinoid system in regulating mood and emotional responses.
Investigating the neurobiological underpinnings of obsessive-compulsive disorder.
The impact of virtual reality technology on cognitive rehabilitation in stroke patients.
Analyzing the neural basis of social cognition deficits in autism spectrum disorders.
The role of neuroinflammation in the progression of multiple sclerosis.
Investigating the effects of dietary interventions on brain health and cognitive function.
The neural substrates of decision-making under risk and uncertainty.
Analyzing the impact of early life stress on brain development and mental health outcomes.
The role of dopamine in motivation and reward processing in the human brain.
Investigating neural circuitry changes in depression and response to antidepressants.
The impact of sleep deprivation on cognitive performance and neural function.
Analyzing the brain mechanisms involved in empathy and moral reasoning.
The role of the prefrontal cortex in executive function and impulse control.
Investigating the neurophysiological basis of schizophrenia.

Neuroscience Research Ideas (Continued)

The impact of chronic pain on brain structure and connectivity.
Analyzing the effects of physical exercise on neurogenesis and cognitive aging.
The neural mechanisms underlying hallucinations in psychiatric and neurological disorders.
Investigating the impact of music therapy on brain recovery post-stroke.
The role of astrocytes in neural communication and brain homeostasis.
Analyzing the effect of hormone fluctuations on mood and cognition in women.
The impact of neurofeedback training on attention deficit hyperactivity disorder (ADHD).
Investigating the neural basis of resilience to stress and trauma.
The role of the cerebellum in non-motor cognitive and affective functions.
Analyzing the contribution of genetics to individual differences in brain structure and function.
The impact of air pollution on neurodevelopment and cognitive decline.
Investigating the neural mechanisms of visual perception and visual illusions.
The role of mirror neurons in empathy and social understanding.
Analyzing the neural correlates of language development and language disorders.
The impact of social isolation on neurocognitive health in the elderly.
Investigating the brain mechanisms involved in chronic fatigue syndrome.
The role of serotonin in mood regulation and its implications for antidepressant therapies.
Analyzing the neural basis of impulsivity and its relation to risky behaviors.
The impact of mobile technology usage on attention and brain function.
Investigating the neural substrates of fear and anxiety-related disorders.
The role of the olfactory system in memory and emotional processing.
Analyzing the impact of gut microbiome alterations on central nervous system diseases.
The neural mechanisms of placebo and nocebo effects.
Investigating cortical reorganization following limb amputation and phantom limb pain.
The role of epigenetics in neural development and neurodevelopmental disorders.

Recent Neuroscience Studies

While the ideas we’ve presented above are a decent starting point for finding a research topic, they are fairly generic and non-specific. So, it helps to look at actual studies in the neuroscience space to see how this all comes together in practice.

Below, we’ve included a selection of recent studies to help refine your thinking. These are actual studies, so they can provide some useful insight as to what a research topic looks like in practice.

The Neurodata Without Borders ecosystem for neurophysiological data science (Rübel et al., 2022)
Genetic regulation of central synapse formation and organization in Drosophila melanogaster (Duhart & Mosca, 2022)
Embracing brain and behaviour: Designing programs of complementary neurophysiological and behavioural studies (Kirwan et al., 2022).
Neuroscience and Education (Georgieva, 2022)
Why Wait? Neuroscience Is for Everyone! (Myslinski, 2022)
Neuroscience Knowledge and Endorsement of Neuromyths among Educators: What Is the Scenario in Brazil? (Simoes et al., 2022)
Design of Clinical Trials and Ethical Concerns in Neurosciences (Mehanna, 2022) Methodological Approaches and Considerations for Generating Evidence that Informs the Science of Learning (Anderson, 2022)
Exploring the research on neuroscience as a basis to understand work-based outcomes and to formulate new insights into the effective management of human resources in the workplace: A review study (Menon & Bhagat, 2022)
Neuroimaging Applications for Diagnosis and Therapy of Pathologies in the Central and Peripheral Nervous System (Middei, 2022)
The Role of Human Communicative Competence in Post-Industrial Society (Ilishova et al., 2022)
Gold nanostructures: synthesis, properties, and neurological applications (Zare et al., 2022)
Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis (Cui et al., 2022)

As you can see, these research topics are a lot more focused than the generic topic ideas we presented earlier. So, for you to develop a high-quality research topic, you’ll need to get specific and laser-focused on a specific context with specific variables of interest. In the video below, we explore some other important things you’ll need to consider when crafting your research topic.

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If you’re still unsure about how to find a quality research topic, check out our Research Topic Kickstarter service, which is the perfect starting point for developing a unique, well-justified research topic.

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121 Original Neuroscience Research Topics

Now, wouldn’t it be great if you had a list of awesome neuroscience research topics to choose from? Our PhD dissertation help would definitely make writing a thesis or dissertation a lot easier. Well, the good news is that we have a long list of neuroscience paper topics for you right here.

The list of topics is updated periodically, so you will surely be able to find a unique topic; something that nobody has though of yet. And yes, you can use any of our topics for free.

Writing a Neuroscience Dissertation

To write a good dissertation, you need more than just our interesting neuroscience topics. Your supervisor expects you to make some progress pretty quickly, so you really need all the help you can get. You can get all the assistance you need to get started quickly from our dissertation experts and you’ll also find the following guide useful:

Set up your project and conduct the necessary research and data analysis. Don’t forget to think about an interesting, captivating thesis statement. Start by writing the first chapter of the dissertation, the introduction. This will provide your readers with comprehensive background information about your study. Write the Literature Review chapter. This will take some time, especially if you are dealing with a popular subject. Write the Methodology chapter. This is basically an iteration and in-depth description of each and every method you have used to collect the data. Write the Results chapter. In this chapter, you will present your readers the results of your research. You don’t need to provide your own take on the data yet. Next comes the Discussion (or Analysis) chapter. This is where you are free to discuss your results and show your readers how they support your thesis. Finally, the Conclusion chapter wraps everything up. You can summarize your methods, results and analysis and make it clear that your paper has answered all the relevant research questions. Write the References section and the Appendices section. Edit and proofread your work thoroughly to make sure you don’t lose points over some minor mistakes – or have our expert proofreaders and editors do it for you.

This step-by-step guide applies to any thesis or dissertation. However, before you even get this far, you need a great topic to start with. Fortunately, we have 121 brand new topics for you right here on this page.

Interesting Neuroscience Topics

If you are looking for some of the most interesting neuroscience topics, you have definitely arrived at the right place. Our experts have put together the best list of ideas for you:

Research the occurrence of cerebrovascular disease in the United States
What causes a headache?
An in-depth look at muscular dystrophy
The causes of multiple sclerosis
Talk about neuroregeneration
Define cognitive neuroscience
Everything about dementia
Study brain development from birth to age 2
What causes Parkinson’s disease?
The function of peripheral nerves
What are vestibular disorders?
Pain and the science behind it
An in-depth analysis of stem cells

Engaging Topics in Neuroscience

Are you looking for some engaging topics in neuroscience? If you want the best ideas, all you have to do is take a look at the following list and take your pick:

Research the Down syndrome
A closer look at ADHD
What causes brain tumors?
What causes epilepsy episodes?
Research the occurrence of schizophrenia in the UK
An in-depth look at brain stimulation
Treating severe depression in young adults
Improving memory in the adult population
The importance of sleep for brain health
Mapping the human brain

Comprehensive Neuroscience Topic for Every Student

The nice thing about our blog is that we have a comprehensive neuroscience topic for every student. Even better, all our topics are relatively simple, so you don’t have to spend a lot of time doing research:

The future of brain implants
The processes behind depression
The role of dopamine
How are emotions created?
Love starts in your brain, not your heart
ADHD behavior and brain activity
Effects of illegal drugs on dopamine production
How does dyslexia manifest itself?
Early stages of Schizophrenia
The link between gut bacteria and the brain
Studying the brains of people with a high IQ

Neuroscience Research Questions

The best way to get ideas for your next paper is to take a look at some original neuroscience research questions. Here are some that should get you started right away:

How do brain tumors cause damage?
What causes substance addiction?
What role does the brain play in autistic spectrum disorders?
Does being a vegetarian influence your brain?
What causes chronic migraines?
Why is Pierre Paul Broca’s work important?
Why is stress so dangerous for the brain?
How do genes influence the onset of Alzheimer’s disease?
What can cause a brain tumor?
Does music affect the human brain?
Can repeated head injuries damage the brain? (think about modern sports)
What does being Bipolar I mean?

Easy Neuroscience Paper Topics

Our experts have created a list of easy neuroscience paper topics for you. You could start writing your thesis in no time if you choose one of these great ideas:

What causes epilepsy?
A closer look at Alzheimer’s disease
What can cause a loss of feeling?
The effects of dementia on the brain
The symptoms of Parkinson’s disease
What can cause memory loss?
Mitigating headaches without medication
The effects of a mild stroke
Talk about Amyotrophic Lateral Sclerosis
What can cause a lack of coordination?

Neuroscience Research Topics for College Students

We have a list of awesome neuroscience research topics for college students and you can use any one of them for free. Take a look at our best ideas yet:

Can the brain be linked to substance abuse?
How does the brain recognize people?
Latest development in brain surgery
An in-depth look at neuroplasticity
Innovative medication for treating brain disorders
Treating Alzheimer’s in 2023
How damaging is Cannabis for the brain?

Cognitive Neuroscience Research Topics

If you want to talk about something in cognitive neuroscience, we have put together the best and most interesting cognitive neuroscience research topics:

The role played by neurons in our body
What is Magnetoencephalography?
How difficult is it to map the entire brain?
Define consciousness from a neurological POV
How does our brain affect our perception?
Discuss Transcranial Magnetic Stimulation procedures
Latest advancements in Functional magnetic resonance imaging

Brain Research Topics

Brain research is a very interesting thing to talk about, especially since we are still struggling to understand how certain things work. Take a look at some amazing brain research topics:

Study the brain development of an infant
Brain tumor stages
The effect of social media on the human brain
Multiple sclerosis treatment options
What can cause muscular dystrophy?
Discuss 3 cerebrovascular diseases
Interesting breakthroughs in cellular neuroscience
Talk about our brain’s problem-solving abilities
The effects of sugar on brain chemistry

Neurobiology Topics

We agree, researching a topic in neurobiology is not easy. However, with the right neurobiology topics, you could write an awesome thesis without spending years working on it:

Research the role of the amygdala
What are brain neurotransmitters?
The causes of posttraumatic stress disorder
How do we recognize a bipolar disorder?
The importance of hormones
Talk about experimental psychology

Behavioral Neuroscience Research Topics

Do you want to write your dissertation on a behavioral neuroscience topic? Our experts have compiled a list of the most interesting behavioral neuroscience research topics for you:

The processes behind sensation
How does the brain control our movement?
An in-depth look at motivated behavior
Best way to diagnose a sleep disorder
Improving success at academic activities
How does your brain perceive the environment?

Cool Neuroscience Topics

We have some very cool neuroscience topics right here and the good news is that they’re all relatively easy. The list has been updated recently and new topics have been added:

Effects of plant-based diets
The life and work of Cornelia Bargmann
Discuss a breakthrough in neurotech
3D brain function mapping
Discuss the importance of brain implants
The life and work of Róbert Bárány

Controversial Topics in Neuroscience

Just like any other field, neuroscience has its controversies. And what better way to start a dissertation than finding the most controversial topics in neuroscience:

Discuss the Bayesian brain theory
Ethics behind wearable brain gadgets
Discuss postnatal neurogenesis
Can our brain “deep learn”?
Invasive brain imaging procedures
How do we differentiate between good and bad?

Hot Topics in Neuroscience

Did you know that getting hot topics in neuroscience is not overly difficult? This section of our list of topics is updated periodically, so you can definitely find an original idea right here:

Electrical brain stimulation methods
Define the concept of Free Will
Talk about hereditary brain disorders
How is speech formed?
Can our brain hibernate?
What causes aggressive behavior?

Current Topics in Neuroscience

The best way to make your thesis interesting is to write about something that is of great interest. This means you need to choose one of our current topics in neuroscience:

Cerebellar Neurons that can help you lose weight
Effects of a meat-based diet
Latest brain mapping technology
CT scans in 2023
Brain implants that can control a computer
An in-depth look at super-agers

Complex Neurological Research Topics

Are you looking for some complex neurological research topics? If you want to give a difficult topic a try, don’t hesitate to choose one of these excellent ideas:

An in-depth look at the Demyelinating disease
The effects of a cerebrovascular stroke
Bioterrorism in 2023
Legal issues in neurology
Dopamine’s link to aggressiveness
Brain changes that lead to alcohol addiction

Can You Help Me With My Thesis?

So, can you help me with my thesis? Of course, we can help you with much more than some interesting neuroscience research paper topics. Our experienced professionals are ready to give you the best dissertation assistance on the Internet and make sure you get a top score on your paper. All our university educated ENL writers have extensive experience writing dissertations on any subject and topic you can imagine. These cheap dissertation writing services can deliver a final paper in no time, so don’t hesitate to get in touch with us even if you are on a tight deadline.

Our PhD-holding writers and editors are ready to spring into action right now. We can help you with the research, as well as with thesis writing, editing and proofreading. Moreover, we can write a high quality research paper for any high school, college or university student. Your professor will love our work – guaranteed. Our company has 24/7 customer support, so you can order custom academic content online at any time of day or night. What are you waiting for? Give us a try and get a discount!

Image Credits

Neurodevelopmental Disorders: Courtesy of Lauren Orefice (MGH/HMS) Tools and Technology: Courtesy of Barbara Robens, lab of Ann Poduri (BCH) Sensory and Motor Systems: Courtesy of Lauren Orefice (MGH/HMS) Mental Health and Illness: Courtesy of Olga Alekseenko, Lab of Susan Dymecki (HMS) Neurodegenerative Disease: Courtesy of Jeff Lichtman (Harvard) and Takao Hensch (Harvard/BCH) Cellular and Molecular Neuroscience: Courtesy of Isle Bastille, lab of Lisa Goodrich (HMS) Theory and Computation: Courtesy of Tianyang Ye, lab of Hongkun Park (Harvard) Development Neuroscience: Courtesy of Katherine Morillo, lab of Christopher A. Walsh (BCH)

150+ Astonishing Neuroscience Research Topics For Students In 2023

Neuroscience is the study of the brain and nervous system, exploring how they work together to control our thoughts, feelings, and behaviors. It’s a field that delves deep into the complexities of our inner workings.

Why Is Neuroscience Important? Understanding neuroscience is crucial because it unlocks the mysteries of human cognition, behavior, and health. It helps us comprehend mental disorders, develop therapies, and enhance well-being.

In this blog, we will guide you on how to select a captivating subject for your research paper, and we have an extensive list of 150+ astonishing topics suitable for students in 2023. Whether you are a neuroscientist or just curious about the brain, stay tuned with us to learn more about neuroscience research topics.

What Is Neuroscience?

Table of Contents

Neuroscience is the study of the brain and the nervous system. It helps us understand how our brain works and how it controls things like thinking, feeling, and moving. Imagine your brain as the boss of your body, and neuroscience is like a detective trying to figure out how the boss gives orders and makes things happen.

Neuroscientists use tools like brain scans and experiments to learn about the brain. They also study diseases that affect the brain, like Alzheimer’s and Parkinson’s, to find ways to help people who have these conditions. So, neuroscience is all about discovering the secrets of our brain and helping us live healthier and happier lives by understanding how it works.

Why Is Neuroscience Important?

Neuroscience is important because it helps us understand how our brain and nervous system work, impacting our overall health and well-being. Here are 5 key reasons why neuroscience is crucial:

Mental Health: It helps us comprehend mental disorders like depression and anxiety, leading to better treatments and support.
Neurological Diseases: Neuroscience research aids in finding cures and treatments for diseases like Alzheimer’s, Parkinson’s, and epilepsy.
Learning and Education: It guides educators in developing effective teaching methods by uncovering how the brain learns and remembers.
Addiction and Behavior: Neuroscience helps us address addiction issues and understand human behavior better.
Brain Development: It provides insights into child development, allowing us to support children’s growth and well-being.

How to Choose a Topic for Neuroscience Research Paper

Here are some steps on how to choose a topic for a neuroscience research paper:

1. Personal Interest

Select a topic that genuinely interests you. If you are curious about a specific aspect of the brain or nervous system, it will make your research more enjoyable and motivating. Think about what you find fascinating: memory, emotions, or brain disorders.

2. Relevance

Ensure your topic is relevant and meaningful. Consider how your research can contribute to our understanding of the brain or benefit society. For instance, studying a topic related to brain diseases can directly impact improving treatments and people’s lives.

3. Availability of Resources

Check if there are enough resources available for your chosen topic. This includes access to research papers, books, and equipment. It’s essential to have the necessary tools and information to conduct your research effectively.

4. Feasibility

Assess the feasibility of your research topic. Can you realistically conduct experiments or gather data on this subject? Consider the time, budget, and access to necessary facilities or subjects for your research.

5. Guidance and Mentorship

Seek guidance from professors or mentors in the field. They can help you refine your topic, provide valuable insights, and point you in the right direction. Having expert guidance can significantly enhance the quality of your neuroscience research paper.

Here are 150+ astonishing neuroscience research topics for students in 2023 :

Simple Neuroscience Research Topics

1. The impact of sleep on memory consolidation.

2. The effects of stress on the brain.

3. How does exercise improve cognitive function?

4. The role of neurotransmitters in mood disorders.

5. The neurobiology of addiction.

6. Brain development in infants.

7. The effects of meditation on brain health.

8. Neural mechanisms of decision-making.

9. Neurological basis of learning disabilities.

10. The relationship between brain injuries and personality changes.

Interesting Neuroscience Research Paper Topics

11. The connection between gut microbiota and brain function.

12. Neural correlates of empathy and compassion.

13. Neuroplasticity and its applications in rehabilitation.

14. The impact of music on brain activity and emotions.

15. Brain-computer interfaces and their potential for communication.

16. The role of genetics in neurological disorders.

17. Neuroimaging techniques for studying brain disorders.

18. The neuroscience of creativity and innovation.

19. Cognitive decline in aging and potential interventions.

20. The neural basis of consciousness and self-awareness.

Unique Neuroscience Research Paper Topics

21. The influence of virtual reality on neural perception.

22. Neurobiology of love and romantic attachment.

23. Exploring the neural basis of synesthesia.

24. The role of mirror neurons in social cognition.

25. Neural mechanisms underlying laughter and humor.

26. Brain activity during lucid dreaming.

27. The neuroscience of fear and phobias.

28. Neuroethical considerations in brain enhancement technologies.

29. The impact of environmental toxins on brain health.

30. Neural mechanisms of religious experiences.

Captivating Neuroscience Research Ideas

31. Studying the effects of micro-dosing psychedelics on brain function.

32. Investigating the neural basis of consciousness in non-human animals.

33. The neurobiology of near-death experiences.

34. Exploring the role of neural oscillations in sensory perception.

35. Brain changes in astronauts during long-term space travel.

36. The influence of social media on brain connectivity.

37. Neurocognitive aspects of artificial intelligence.

38. Neural correlates of deja vu experiences.

39. The impact of chronic pain on brain structure and function.

40. Neurological consequences of extreme sports and high-risk activities.

Impressive Neuroscience Research Paper Ideas

41. Mapping the connectome: A comprehensive study of neural networks.

42. Brain-machine interfaces for neuroprosthetics and communication.

43. The potential for brain rejuvenation through stem cell therapies.

44. The neurobiology of Alzheimer’s disease and potential treatments.

45. Investigating the neural basis of consciousness disorders.

46. role of epigenetics in brain development and aging.

47. Advanced neuroimaging techniques for studying brain connectivity.

48. Neural mechanisms of memory reconsolidation and erasure.

49. Neurobiology of traumatic brain injuries and recovery.

50. The ethics of cognitive enhancement and neuroenhancement.

Top-trending Neuroscience Research Topics

51. What foods you eat affect the health and performance of your brain.

52. Neurobiology of long COVID and neurological symptoms.

53. The use of artificial intelligence in analyzing brain imaging data.

54. Brain mechanisms underlying social isolation during lockdowns.

55. The role of neuroinflammation in neurological disorders.

56. Developing neuroprotective strategies against neurodegenerative diseases.

57. Neural correlates of mindfulness-based interventions for stress reduction.

58. Brain changes associated with addiction to video games and social media.

59. The neuroscience of racial and gender disparities in healthcare.

60. Neuroethical implications of brain privacy in the digital age.

Neuroscience Thesis Topics

61. Examining the role of dopamine in reward-based learning.

62. Investigating the neural basis of post-traumatic stress disorder.

63. Neurobiological markers of autism spectrum disorder.

64. Brain plasticity and recovery after stroke.

65. The impact of sleep disorders on cognitive function.

66. Neural mechanisms of pain perception and chronic pain management.

67. The role of neuroinflammation in multiple sclerosis.

68. Neuroimaging biomarkers for early detection of Alzheimer’s disease.

69. Brain-computer interfaces for locked-in syndrome patients.

70. The neural basis of consciousness and its philosophical implications.

Mental Health Research Topics
Quantitative Research Topics For STEM Students

Cognitive Neuroscience Research Topics

71. Neural correlates of language processing and comprehension.

72. The role of attention in perceptual processing.

73. Memory consolidation during sleep and wakefulness.

74. Brain mechanisms of decision-making and risk-taking behavior.

75. The neurobiology of creativity and problem-solving.

76. Emotional regulation and its neural substrates.

77. Neural basis of cognitive aging and interventions to improve cognition.

78. Neurocognitive processes involved in learning and education.

79. The impact of mindfulness meditation on cognitive function.

80. Cognitive and neural processes in face recognition.

A Few More Cognitive Neuroscience Research Ideas

81. Neural mechanisms of time perception and its distortions.

82. Investigating the role of the prefrontal cortex in executive functions.

83. The effects of bilingualism on brain structure and cognitive flexibility.

84. Neural substrates of empathy and theory of mind.

85. The influence of culture on the neural processing of emotions.

86. Neural basis of decision-making in ethical dilemmas.

87. Cognitive neuroscience of addiction and relapse prevention.

88. The impact of video gaming on cognitive skills and brain function.

89. Neurocognitive aspects of dyslexia and reading interventions.

90. The role of neurofeedback in enhancing cognitive performance.

Behavioral Neuroscience Research Topics

91. Neural mechanisms of addiction and substance abuse.

92. The role of hormones in shaping behavior and cognition.

93. Brain circuits involved in aggression and violence.

94. Social neuroscience: Understanding the neural basis of social interactions.

95. Investigating the effects of early-life stress on behavior and mental health.

96. Neurobiology of motivation and reward systems.

97. Neural correlates of decision-making in moral dilemmas.

98. Brain mechanisms underlying learning and memory in animals.

99. The impact of traumatic brain injury on behavior and personality.

100. The role of epigenetics in behavioral disorders.

Clinical Neuroscience Research Topics

101. Biomarkers for early diagnosis of neurological diseases.

102. Innovative treatments for neurodegenerative disorders like Parkinson’s disease.

103. Neuroimaging in psychiatric disorders: Insights and applications.

104. Advances in neurorehabilitation after brain injuries and strokes.

105. Understanding and treating childhood neurological disorders.

106. Precision medicine in neurology and psychiatry.

107. Brain stimulation techniques for mood disorders and chronic pain.

108. The impact of nutrition on brain health and cognitive function.

109. Psychopharmacology and the development of new psychiatric medications.

110. Ethical considerations in clinical trials for neurological interventions.

Neuropharmacology Research Topics

111. Mechanisms of action of common psychiatric medications.

112. Drug development for Alzheimer’s disease and other neurodegenerative conditions.

113. The neurochemistry of addiction and potential pharmacotherapies.

114. Psychotropic drugs and their effects on neurotransmitter systems.

115. Neuropharmacology of pain management and opioid alternatives.

116. The use of psychedelics to help mental well-being.

117. Pharmacological interventions for neuroinflammatory disorders.

118. Neuropharmacology of sleep and wakefulness.

119. Drug interactions in neurological and psychiatric treatments.

120. Precision medicine approaches in neuropharmacology.

Computational Neuroscience Research Topics

121. Modeling neural networks and their dynamics.

122. Machine learning and artificial intelligence in brain research.

123. Computational models of visual perception and object recognition.

124. Simulating brain diseases and disorders for drug discovery.

125. Theoretical models of consciousness and self-awareness.

126. Neural network algorithms for brain-computer interfaces.

127. Computational approaches to studying neural plasticity.

128. Modeling brain disorders in silico for treatment development.

129. The role of computational neuroscience in understanding neurodevelopment.

130. Ethics and biases in machine learning applications to neuroscience.

Neuroscience and Psychology Research Topics

131. What brain structure has to do with behavioral traits.

132. Neurocognitive processes involved in decision regret.

133. The neural basis of cognitive dissonance.

134. Brain mechanisms underlying the placebo effect.

135. The impact of early-life stress on psychological development.

136. Neurobiology of addiction and its psychological consequences.

137. The role of neural oscillations in consciousness and perception.

138. Neural correlates of emotional intelligence.

139. Cognitive and neural factors in resilience to stress.

140. The psychology of neurofeedback therapy.

Neuroscience and Mental Health Research Topics

141. The neurobiology of depression and novel treatments.

142. Neuroimaging markers for predicting schizophrenia risk.

143. Neural mechanisms of post-traumatic stress disorder (PTSD).

144. It has to do with mental health and the gut-brain connection.

145. Brain changes associated with obsessive-compulsive disorder ( OCD ).

146. Neural correlates of bipolar disorder and mood swings.

147. How traumatic events in childhood can affect mental health as an adult.

148. Neurobiological underpinnings of eating disorders.

149. Psychiatric genetics and the risk of mental illnesses.

150. Neurocognitive interventions for anxiety disorders.

151. How sleep affects how well kids do in school.

Understanding the importance of neuroscience and picking the right topic for your research paper is crucial in the field of Neuroscience Research Topics. Neuroscience is all about studying the brain and nerves, which helps us learn about brain-related issues and how people think and behave.

In addition, choosing a good topic is the first step, and we provide you 150+ interesting ones for students in 2023. Whether you’re curious about how the brain changes, addiction, or ways to look at the brain, there are many topics to explore. So, get started on your neuroscience research journey and uncover the secrets of the human mind!

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179+ Interesting Neuroscience Research Topics For Students

Neuroscience is the study of the brain and how it works. It’s like opening a door to a world of wonders, where every discovery sheds light on the inner workings of our minds.

Students are drawn to neuroscience because it helps us understand ourselves better. We want to know what makes us tick, why we behave the way we do, and how we can make a difference in the world through science.

That’s where our blog comes in. We’re here to make neuroscience easy to understand and exciting to explore.

We’ll share many interesting neuroscience research topics that students can dive into, so come along as we journey through the wonders of the brain together!

Neuroscience: What is it?

Table of Contents

Neuroscience is the study of the brain and nervous system. It delves into understanding how these intricate systems function, from the smallest neurons to complex brain networks.

By exploring the structure, organization, and functions of the brain, neuroscience seeks to unravel the mysteries of human behavior, cognition, and consciousness.

Through various methods such as imaging techniques, electrophysiology, and behavioral studies, neuroscientists aim to decipher the underlying mechanisms of neurological disorders, enhance brain health, and ultimately advance our understanding of what it means to be human.

Students Should Understand the Importance of Neuroscience Research Topics

Understanding the importance of neuroscience research topics is crucial for students for several reasons:

Advancing Knowledge

Neuroscience research topics offer students insight into the complexities of the brain and nervous system, fostering a deeper understanding of how these intricate systems shape behavior, cognition, and emotions.

Improving Healthcare

By studying neuroscience, students gain valuable knowledge about the underlying mechanisms of mental health disorders, leading to more effective interventions and destigmatization of mental illness.

Informing Education

Neuroscience research informs teaching practices by elucidating how the brain learns and retains information, guiding educators in creating more effective learning environments and strategies.

Advancing Medical Treatments

Insights gained from neuroscience research contribute to the development of novel treatments for neurological disorders such as Alzheimer’s, Parkinson’s, and epilepsy, offering hope for improved patient outcomes and quality of life.

Exploring Consciousness

Neuroscience research delves into the nature of consciousness, shedding light on philosophical questions about the mind and subjective experience, enriching interdisciplinary dialogues and intellectual inquiry.

List of Best Student-Friendly Neuroscience Research Topics

Here’s a list of neuroscience research topics that students can explore:

Brain Development and Plasticity

Neuroplasticity in Aging Brains
Effects of Early Childhood Experiences on Brain Development
Role of Neurogenesis in Learning and Memory
Plasticity in the Visual Cortex
Environmental Influences on Brain Plasticity
Effects of Exercise on Brain Plasticity
Developmental Disorders and Brain Plasticity
Plasticity and Recovery after Brain Injury
Epigenetic Regulation of Brain Plasticity
Neuroplasticity and Language Acquisition
Music and Brain Plasticity
Plasticity in Neurorehabilitation

Cognitive Neuroscience

Neural Mechanisms of Decision-Making
Attention and Working Memory in the Brain
Neural Basis of Language Processing
Executive Function and Prefrontal Cortex Activity
Neural Correlates of Creativity
Memory Consolidation and Retrieval Mechanisms
Neural Basis of Emotion Regulation
Neural Processing of Time Perception
Brain Networks Underlying Social Cognition
Neurobiology of Decision-Making Disorders
Perception and Neural Representations
Neural Basis of Consciousness

Neurobiology of Mental Disorders

Neurobiology of Depression and Anxiety
Schizophrenia: Insights from Neuroimaging Studies
Molecular Mechanisms of Bipolar Disorder
Genetics of Autism Spectrum Disorders
Neurobiology of Obsessive-Compulsive Disorder
Post-Traumatic Stress Disorder: Brain Mechanisms
Addiction and Reward Circuitry in the Brain
Neurobiology of Eating Disorders
Neural Correlates of Attention-Deficit/Hyperactivity Disorder (ADHD)
Neurobiology of PTSD
Sleep Disorders and Brain Function
Neural Basis of Schizoaffective Disorder

Neuropharmacology and Drug Development

Drug Targets in Neurodegenerative Diseases
Pharmacological Treatment of Epilepsy
Psychopharmacology of Mood Disorders
Novel Therapeutic Approaches for Alzheimer’s Disease
Pharmacological Interventions for Parkinson’s Disease
Drug Addiction: Neurobiological Insights
Neuropharmacology of Pain Management
Pharmacogenomics in Neuropsychiatric Disorders
Neurotransmitter Systems and Drug Development
Nanotechnology in Drug Delivery to the Brain
Herbal Remedies and Neurological Disorders
Pharmacological Approaches to Enhance Cognitive Function

Neuroimaging Techniques

Functional MRI (fMRI) and Brain Connectivity
Diffusion Tensor Imaging (DTI) in White Matter Tractography
Positron Emission Tomography (PET) in Neuroscience Research
Magnetoencephalography (MEG) and Brain Dynamics
Structural MRI in Brain Morphometry
Electroencephalography (EEG) in Cognitive Neuroscience
Near-Infrared Spectroscopy (NIRS) for Brain Monitoring
Voxel-Based Morphometry (VBM) in Neuroimaging Studies
Functional Near-Infrared Spectroscopy (fNIRS) in Brain Imaging
Resting-State Functional Connectivity Analysis
Multi-Modal Imaging Approaches in Neuroscience
Advanced Imaging Techniques in Animal Models

Neurogenetics and Epigenetics

Genetic Variants Associated with Neurological Disorders
Epigenetic Regulation of Brain Development
Gene-Environment Interactions in Brain Function
Neurogenetics of Neurodegenerative Diseases
Epigenetic Modifications and Memory Formation
Neurodevelopmental Disorders and Genetic Risk Factors
Role of microRNAs in Neural Regulation
Epigenetic Mechanisms in Addiction
Genomic Instability and Brain Tumors
Neuroepigenetics in Aging
Neurogenetic Basis of Neurodevelopmental Disorders
Epigenetic Therapies for Neurological Disorders

Neuroethics and Neurolaw

Ethical Considerations in Brain-Computer Interfaces
Privacy and Data Security in Neuroimaging Research
Neuroenhancement and Cognitive Enhancement Technologies
Neuroimaging in Legal Decision-Making
Ethical Implications of Neuropsychiatric Interventions
Neuroethical Issues in Brain Stimulation Research
Informed Consent in Neuroscientific Studies
Ethical Challenges in Neuroimaging of Consciousness
Neuroethics of Brain-Computer Interface Technology
Neuroethics and Artificial Intelligence
Neurolaw and Brain-Based Lie Detection
Ethical Issues in Neurological Disorders Research

Neurobiology of Learning and Memory

Hippocampal Function in Spatial Memory
Neurobiological Basis of Fear Conditioning
Memory Reconsolidation Mechanisms
Neurobiology of Habit Formation
Neuroplasticity and Skill Learning
Synaptic Mechanisms of Memory Encoding
Molecular Basis of Long-Term Potentiation (LTP)
Neurobiology of Memory Retrieval
Aging and Memory Decline
Neurobiological Processes in Motor Learning
Emotional Memory Processing in the Brain
Memory Formation in Sleep and Dreaming

Neuroimmunology

Role of Microglia in Brain Development and Disease
Neuroinflammation in Neurological Disorders
Blood-Brain Barrier Dysfunction in Neurodegeneration
Immunomodulatory Therapies for Multiple Sclerosis
Neuroimmune Interactions in Psychiatric Disorders
Role of T Cells in Central Nervous System Disorders
Neuroinflammatory Responses to Traumatic Brain Injury
Cytokine Signaling in Neurological Diseases
Gut-Brain Axis and Neuroimmune Communication
Autoimmune Encephalitis and Neurological Dysfunction
Immune Cell Trafficking in the Central Nervous System
Neuroimmune Crosstalk in Neurodevelopmental Disorders

Computational Neuroscience

Neural Network Models of Learning and Memory
Computational Approaches to Brain Connectivity Analysis
Spiking Neural Networks for Information Processing
Machine Learning Applications in Neuroimaging
Modeling Neural Oscillations and Synchronization
Reinforcement Learning in Decision-Making Models
Network Dynamics in Brain Diseases
Neural Encoding and Decoding Techniques
Computational Models of Visual Perception
Brain-Inspired Computing Architectures
Computational Psychiatry and Mental Health Modeling
Computational Approaches to Brain-Computer Interfaces

Neuroengineering and Brain-Computer Interfaces

Development of Neuroprosthetics for Motor Rehabilitation
Brain-Machine Interface Technologies for Communication
Neurofeedback Systems for Cognitive Enhancement
Neurostimulation Techniques for Treating Neuropsychiatric Disorders
Closed-Loop Systems in Deep Brain Stimulation
Wearable Devices for Monitoring Brain Activity
Optogenetics in Controlling Neural Circuits
Brain-Computer Interface Applications in Virtual Reality
Neurotechnology for Restoring Sensory Functions
Neuromorphic Computing and Brain-Inspired Chips
Brain-Computer Interface Accessibility for Individuals with Disabilities
Ethical Considerations in Neuroengineering Research

Neurobiology of Sleep and Circadian Rhythms

Brain Regions Involved in Sleep Regulation
Role of Melatonin in Circadian Rhythms
Circadian Clock Genes and Brain Health
Impact of Sleep Deprivation on Cognitive Performance
Neurobiology of Dreaming
Sleep Architecture and Memory Consolidation
Effects of Shift Work on Brain Function
Circadian Rhythms and Metabolic Health
Brain Plasticity During Sleep
Sleep Disorders in Neurodegenerative Diseases
Chronobiology and Mood Disorders

Neurobiology of Sensory Systems

Auditory Processing in the Brain
Visual Perception and Neural Processing
Somatosensory System and Tactile Perception
Olfactory Processing and Brain Circuits
Gustatory System and Taste Perception
Multisensory Integration in the Brain
Vestibular System and Spatial Orientation
Pain Perception and Neurobiology
Neurobiology of Itch Sensation
Sensory Adaptation Mechanisms in the Brain
Crossmodal Plasticity in Sensory Deprivation
Neurobiology of Proprioception

Neurobiology of Motivation and Reward

Dopaminergic Pathways in Reward Processing
Neural Basis of Motivated Behavior
Incentive Salience and Brain Circuits
Neurobiology of Addiction and Reward Dysfunction
Role of Serotonin in Mood and Motivation
Endocannabinoid System and Reward Processing
Neuronal Mechanisms of Reinforcement Learning
Hormonal Influences on Motivation and Reward
Neurobiology of Hedonic Eating Behavior
Neural Circuits Underlying Social Reward
Motivational Deficits in Neuropsychiatric Disorders
Reward Prediction Errors and Learning

Neurobiology of Aging and Neurodegeneration

Cellular Senescence and Brain Aging
Oxidative Stress and Neurodegenerative Diseases
Protein Aggregation in Neurodegeneration
Neuroinflammation and Age-Related Cognitive Decline
Mitochondrial Dysfunction in Neurodegenerative Disorders
Role of Autophagy in Brain Health and Aging
Neurotrophic Factors and Brain Aging
Genetic Risk Factors for Age-Related Neurodegeneration
Environmental Factors in Brain Aging
Neuroprotective Strategies for Age-Related Cognitive Impairment
Lifestyle Interventions for Brain Health and Longevity

How to Choose a Neuroscience Research Topic?

Choosing a neuroscience research topic can be an exciting yet daunting task. Here are some steps to help you navigate the process:

Identify Your Interests: Start by reflecting on areas of neuroscience that intrigue you the most, such as cognitive neuroscience, neuropharmacology, or neurodevelopment.
Review Existing Literature: Conduct thorough research to understand current trends, gaps, and unanswered questions within your chosen area.
Consider Feasibility: Evaluate the resources, equipment, and expertise available to you, ensuring your chosen topic is manageable within your constraints.
Consult with Mentors: Seek guidance from professors, advisors, or experts in the field to refine your ideas and gain valuable insights.
Brainstorm Potential Topics: Generate a list of potential research topics based on your interests, literature review, and feedback from mentors.
Narrow Down Your Choices: Assess each potential topic’s relevance, novelty, and significance to select the most promising one for your research.
Define Clear Objectives: Clearly articulate the research questions or hypotheses you aim to address with your chosen topic.
Consider Ethical Implications: Ensure your research topic aligns with ethical standards and regulations governing research involving human or animal subjects.
Seek Approval: Present your chosen topic to relevant authorities or review boards for approval before proceeding with your research.
Stay Flexible: Remain open to adjustments and refinements to your research topic as you delve deeper into your study and encounter new insights along the way.

Resources for Students Interested in Neuroscience

For students interested in neuroscience, there are various resources available to enhance their understanding and engagement with the field. Here are some recommended resources:

Academic Journals

Access reputable neuroscience journals like “Neuron” and “Journal of Neuroscience” for cutting-edge research articles.

Online Courses

Platforms like Coursera , edX , and Khan Academy offer free or low-cost courses covering various aspects of neuroscience.

Explore fundamental neuroscience textbooks like “ Principles of Neural Science ” by Kandel et al. or “Neuroscience: Exploring the Brain” by Bear et al.

Research Institutes

Consider internships or volunteer opportunities at neuroscience research institutes or university labs for hands-on experience.

Professional Organizations

Join organizations like the Society for Neuroscience (SfN) for networking opportunities, conferences, and resources.

Neuroscience Websites

Websites like Neuroscience for Kids provide educational resources, activities, and information for students.

Podcasts and Blogs

Listen to neuroscience podcasts or follow neuroscience blogs for accessible explanations and discussions on current topics.

Wrapping Up

Neuroscience research offers students a profound opportunity to delve into the complexities of the brain and nervous system, shaping our understanding of human cognition, behavior, and health.

As we conclude our exploration, I encourage readers to embrace the excitement of neuroscience, delve deeper into its mysteries, and contribute to the ongoing scientific dialogue.

Let’s remain curious, engaged, and open to the wonders of the brain, for within its intricate pathways lie endless possibilities waiting to be discovered.

Together, let’s continue our journey of discovery and unraveling the secrets of the mind.

1. What are some career options in neuroscience research?

Diverse pathways exist, including academic research, healthcare, biotechnology, education, and technology development.

2. What are some current challenges and future directions in neuroscience research?

Understanding consciousness, treating brain disorders, developing brain-computer interfaces, and personalized medicine are some exciting areas of exploration.

3. What are some emerging trends or areas of interest in neuroscience research?

Emerging trends in neuroscience research include neurotechnology, brain-machine interfaces, computational neuroscience, and neuroethics.

4. What are some reputable journals and databases for neuroscience research?

Some reputable journals include Nature Neuroscience, Neuron, and Journal of Neuroscience. Databases like PubMed and PsychInfo also provide access to a wealth of neuroscientific literature.

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Undergraduate Neuroscience Research and Thesis Neuro Research Guide

Neuro research guide, guide to choosing a neuroscience research lab, part 1: what factors to consider when joining a lab..

There are hundreds of Harvard affiliated labs, and all of them are different. Below, we have distilled those differences into several important categories to consider as you make your choice. The overarching goal is to help you choose a lab that will foster your development as a scientist.

Research Topic. Students often feel that the research topic is the decisive factor. For example, you may have a topic that you are already passionate about ( e.g., Alzheimer’s Disease, Traumatic Brain Injury, or Free Will). While this pre-existing interest can be a great motivator, consider the following: over three semesters and one summer, you will spend > 750 hours in the lab! For that much time, we think the priority should be finding a great lab environment with supportive mentors.

False! A topic isn’t usually exciting until you learn more about it. We find that once students realize what questions are being asked, what the debates are in this area, and what real-world implications the topic has, what methods are being used/developed, they quickly become passionate about their work.
False! Medical and graduate schools are evaluating your lab experiences in two major ways: First, they want evidence of your scientific development in the lab, including your independence in designing experiments/analyzing data and your understanding of your research topic. Second, they want to see an authentic, personalized, positive letter from your faculty mentor detailing your drive, independence, attention to detail, collegiality, etc .

Size of the lab. The size of the lab is not always, but very often, a predictor of student success. Higher visibility labs tend to be big (>20 people). Although they are publishing great papers, the environment may not be ideal for undergrads. Why? In bigger labs, it is harder to get face time with the faculty mentor. Moreover, each daily supervisor (post doc or grad student) may have several undergraduates working with them or be consumed with their own work. Students can feel lost when they do not get enough mentoring and attention. Another peril of working for ‘rockstar’ faculty is that projects may be aiming for publication in Nature, Science, or Cell, which can take more than 5 years of full-time teamwork … when things go right. As such, students are often a small part of a bigger, longer project (a ‘cog in the machine’). Their role is often more of a technical one with less control, thought, or creativity in the experimental design and therefore less scientific development and growth.

In spite of the drawbacks, some students prefer to work on high visibility projects in big labs. That is fine but be aware that these projects can lead to lower thesis evaluation grades because faculty evaluators look for evidence that the student has put independent thought and individual work into the thesis.

Independence and Project Type. It is daunting to be responsible for your own research project’s success or failure, especially when you are just starting out in science. Yet, this really is the best way to learn how to do science. Having to make decisions about what experiment to do or how to analyze your work requires a deep understanding of your research area. Large, team projects can be fun, but students often grow and learn more from small projects where they can make decisions.

Typically, projects that are small in scope (short term) work best, so you can learn from your mistakes and get feedback on your results within weeks to reconfigure if need be. Working more independently on a project also gives you more control of your data, rather than being handed data from someone else and not having any influence on how or why the experiments were done.

Mentoring. Arguably the most important aspect of your lab experience is your direct mentor. Try to meet your direct mentor before signing up with a lab. You want to make sure that they are invested in your success: meaning, 1) they has time to meet with your regularly, they have reasonable demands on your time (15 hours or less per week during the term), and they can communicate clearly with you.

Whatever lab you’re in, be sure to schedule face time with the faculty mentor (alone or with your daily supervisor) at least once per month. This will help you forge a connection to the lab head and be part of conversations that can influence your study design and color the interpretation of your results. You should also make an effort to attend lab meeting to learn about other projects and develop your critical thinking/questioning skills.

Commute/ Location. It might seem harrowing, but commuting to a lab is very possible. The free M2 shuttle can get you to the Longwood/hospital area in about 30 minutes (outside of rush hour times and extreme weather). The MBTA can get you to MGH, MIT, Broad Institute just as quickly. As long as you can arrange your schedule to have big blocks of consecutive lab time (3 hours), the commute will only be a fraction of your dedicated lab time.

The good news, if you don’t want to commute, is that labs closer to Cambridge typically have more experience working with undergrads. This often translates into a better mentoring culture for students. All things being equal, we recommend you start looking for a lab on campus (Biolabs, NW Building, William James). If you don’t find a good fit there, consider labs at the Medical School that are affiliated with the Program for Neuroscience . If you still aren’t satisfied, you can extend your search to other Harvard-affiliated hospitals or centers (MGH, Children’s Hospital, Beth Israel, Brigham and Women’s, McLean, etc .)

Part 2: Questions to ask before joining a lab.

Here is a list of potential questions to ask the lab director when you meet to talk about joining a lab:

Typically, students meet with the faculty mentor two or three times per semester. Its great if it is more frequently, but it should not be less.
Typically, students work with a grad student or a post-doc. They often meet every time the student comes to lab (at least at the beginning) and communicate informally by email. Since they play a big role in mentoring you, it is always a good idea to meet them before joining.
Student projects are most rewarding when students are involved in experimental design and all aspects of data analysis. It gives the student more ownership and control of the project, which very often creates a better environment to learn to do science.
Longer term experiments (more than a year) are usually team-projects where students don’t have much influence or control of the project.
While every student is different, other undergrads in the lab can usually tell you what kind of experience to expect. (Laura and Ryan can give you feedback on labs students have worked in as well in case you want an additional opinion.)
Lab meetings can be a great way to assess the group dynamics and lab culture to make sure it feels like a comfortable and stimulating environment for you.
Typically, students should expect to spend 5-10 hrs/week if they are volunteering in the lab during the semester, or 10-15 hrs/week if they are enrolled in research for credit (Neuro 91). Most labs expect students spend one summer working full-time in the lab (often before senior year) if they are serious about a thesis or a career in research after graduation.
This varies by lab: sometimes students will choose among several options. Sometimes there might only be one project that needs additional help (or has an available mentor). Occasionally, faculty mentors want students to develop their own project idea! You just don’t know until you ask.

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Neuroscience Dissertation Topics – Based on Recent Academic Research

Published by Ellie Cross at December 29th, 2022 , Revised On August 16, 2023

Are you looking for the best neuroscience dissertation topics? Here we go! Here are some intriguing neuroscience study topic suggestions that you may find helpful.

Neuroscience is a scientific field that studies the structure and function of the nervous system. On a broad scale, the topic covers numerous behavioural, computational, cellular, evolutionary, functional, molecular, and therapeutic facets of the nervous system.

Many students have trouble coming up with fascinating neuroscience research project topics. Choosing a topic for the dissertation is a crucial step in the dissertation writing process . Using brainstorming techniques, you can narrow down a large concept into a specific study area. Spend an hour brainstorming and reflecting on ideas that might make for a good project.

If you don’t have the time to brainstorm because you have been procrastinating for too long, choose one of the neuroscience topics suggested below.

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You can create an impactful thesis paper using any of the suggestions in our list of neuroscience dissertation and thesis topics. You can also modify the preceding topics according to your academic level and country of study. Get in touch with our team if you are looking for customised neuroscience dissertation topics .

Moreover, if you have trouble completing your neuroscience study, use our dissertation writing service to achieve your desired grade. Neuroscientists on our team of experienced academic writers are experts at composing and delivering research dissertations on any neuroscience topic without plagiarism .

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How to find neuroscience dissertation topics.

To find neuroscience dissertation topics:

Research recent advancements.
Explore unanswered questions.
Review neuroscience journals.
Consider interdisciplinary angles.
Consult professors and experts.
Select a topic aligning with your passion and skills.

Growing Brains, Nurturing Minds—Neuroscience as an Educational Tool to Support Students’ Development as Life-Long Learners

Associated data.

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Compared to other primates, humans are late bloomers, with exceptionally long childhood and adolescence. The extensive developmental period of humans is thought to facilitate the learning processes required for the growth and maturation of the complex human brain. During the first two and a half decades of life, the human brain is a construction site, and learning processes direct its shaping through experience-dependent neuroplasticity . Formal and informal learning, which generates long-term and accessible knowledge, is mediated by neuroplasticity to create adaptive structural and functional changes in brain networks. Since experience-dependent neuroplasticity is at full force during school years, it holds a tremendous educational opportunity. In order to fulfill this developmental and learning potential, educational practices should be human-brain-friendly and “ride” the neuroplasticity wave. Neuroscience can inform educators about the natural learning mechanisms of the brain to support student learning. This review takes a neuroscientific lens to explore central concepts in education (e.g., mindset, motivation, meaning-making, and attention) and suggests two methods of using neuroscience as an educational tool: teaching students about their brain (content level) and considering the neuro-mechanisms of learning in educational design (design level).

1. Educational Neuroscience (Teaching for the Brain and Teaching about the Brain)

Educational neuroscience is an interdisciplinary field exploring the effects of education on the human brain and promotes the translation of research findings to brain-based pedagogies and policies [ 1 ]. The brain is the target organ of education. Education is thought to influence brain development [ 2 , 3 ] and health, even as the brain ages [ 4 , 5 ]. Studying the dynamics between the brain and education can be instrumental in finding ways to better support learners across the lifespan.

Educational neuroscience research explores every possible relationship between the physiological, mental, and behavioral aspects of learning. Some studies have tried to identify the optimal physical conditions for neuroplasticity and learning. This stream of educational neuroscience research includes studies exploring the effects of sleep (or sleep deprivation), physical exercise, and environmental pollution on the brain and its cognitive performance [ 1 ]. While these studies focus on the effect of brain health on learning, other studies examine the effect of learning on brain health, assessing the long-term effects of learning/education on the human brain and exploring in what ways formal/informal education is associated with better aging of the human brain [ 2 , 3 , 4 ].

Some educational neuroscience studies take a developmental approach to study the relationship between cognitive and learning capacities across the lifespan. For example, multilevel measurements collected from adolescents (e.g., neuronal, hormonal, psychological, and behavioral) have advanced our understanding of how the massive neuronal changes that take place during adolescence promote cognitive development but also introduce immense neuronal and mental vulnerability (and the onset of most psychiatric disorders) [ 1 , 5 , 6 , 7 ]. Other studies in this line of research explore the factors supporting neuroplasticity in the mature brain—to support lifelong learning [ 8 ].

Educational neuroscience also explores the nature–nurture aspects of learning, for example, examining how learning environments interact with genetic conditions and what DNA variations predict differential learning abilities [ 9 ]. Environmental influences on learning include studies about the impacts of socio-economic status (SES) on the brain and cognitive developmental trajectory [ 10 ]. Furthermore, educational neuroscience seeks to understand the mechanisms that facilitate general learning abilities (such as executive control and social and emotional skills), discipline-specific learning abilities (such as literacy, numeracy, and science), the connections between these mechanisms, and the extent to which these learning skills are trainable [ 11 ].

As a developing, interdisciplinary research field, educational neuroscience faces challenges, limitations, and criticism, especially concerning the ability to generalize research findings in lab conditions to classroom learning, and its validity and transferability to larger scales, such as mass education systems. Other challenges stem from the fact that learning is one of the most basic yet complex brain functions that incorporates the entire brain and has a continuous effect. Furthermore, empirical studies in educational neuroscience are challenging and cumbersome due to the interdisciplinary nature of the field (education, psychology, and neuroscience); the need for repeated measures over time; and the young target population (school students), which imposes ethical restrictions on experimental designs. Finally, while still evolving as a research field, educational neuroscience is intriguing for many educational leaders who are enthusiastic about applying neuroscience in education practices. Unfortunately, the current gap between the high demand and limited supply may lead to misuse of neuroscience in pedagogy (e.g., neuromyths or the justification of educational methods based on limited to no evidence) [ 1 ].

While educational neuroscience is preliminary in forming evidence-based pedagogy, it can already offer valuable information and a much-needed bridge between educators and scientists in translating the research of learning into effective educational practices.

Neuroscience-informed educational design (teaching the way the brain learns) can promote learning motivation, high-level information processing, and knowledge retention. Moreover, neuroscience educational content (teaching about the brain) can inform students about their developing brains to promote scientific education and self-exploration.

1.1. Learning and Neuroplasticity

Human development is based on nature (genetics), nurture (physical and social environments), and their interactions (epigenetics) [ 12 , 13 ]. These factors play an essential role in learning processes and the reorganization of neuronal networks to create neuronal representations of new knowledge. Learning and training new knowledge or skills evoke specific and repeated activity patterns, and in the process of Hebbian neuroplasticity, neural pathways are reinforced by the strengthening of specific synapses, while less functional ones are eliminated [ 14 , 15 , 16 ].

Almost half a century ago, Vygotsky introduced the zone of proximal development (ZPD) [ 17 ] in education. According to the ZPD, learning and development depend on an optimal balance between support and challenge (see Figure 1 : the zone of proximal development and neuroplasticity), which should be tuned and tailored for each learner based on their specific developmental stage. The ZPD model was revolutionary, as it emphasized the importance of the educational environment (nurture) in unlocking the internal potential (nature) of students, and it placed the learning process (as opposed to the learning product ) as the central educational goal [ 17 ]. Some decades later, the biology of learning revealed a beautiful alignment with Vygotsky’s theory—with evidence showing that brain neuroplasticity is highly affected by environmental conditions and the balance between demands (challenge) and available resources (support) [ 18 ]. The impact of stressors on learning can be constructive or destructive depending on the intensity, duration, and accumulation of the stressors and the coping mechanisms and support that one has.

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The zone of proximal development and neuroplasticity. An integrative approach between Vygotsky’s educational model and the neuroscience of learning. When learning and performance demands exceed the available support and resources, students are likely to be overwhelmed and resort to survival mode (stress zone). When learning and performance demands are significantly lower than the available support and resources, students are likely to be under stimulated and resort to static mode (comfort zone). When learning and performance demands match the available support and resources, students are likely to be appropriately challenged and work within their zone of proximal development, which promotes neuroplasticity and growth (stretch zone).

Neuroscience research suggests that experience-dependent neuroplasticity [ 19 ], which facilitates learning processes, benefits from several principles. The central one is that learning a skill or new knowledge requires the activation of relevant neuronal pathways. The research also points to the saliency, intensity, and repetition of the learned skill/knowledge as valuable strategies for enhancing neuroplastic changes [ 16 , 20 , 21 ]. Learners cannot be passive recipients of content but must be active participants in the learning process.

An enriched environment for enhanced neuroplasticity offers physiological integrity, cognitive challenge, and emotional safety. More specifically, an enriched environment includes adequate sleep and nutrition, sensory–motor and cognitive challenges, opportunities for exploration and novelty, and secured relationships that act like a safety net and enable learners to take on challenges [ 22 , 23 ]. Conversely, a lack of these conditions may slow down or decrease the level of neuroplasticity in the developing brain.

The social and cognitive safety net that enables learners to aim high while taking risks and to turn failure into resilience is rooted in safe relationships (with adults and peers) and in holding a growth mindset. A growth mindset is the belief that intelligence and learning potential are not fixed and can be developed [ 24 ]. Holding a growth mindset has been associated with academic success, emotional wellbeing, and motivation while reducing racial, gender, and social class achievement gaps [ 25 , 26 , 27 , 28 , 29 , 30 ]. While the impact of mindset interventions on academic performance is debatable regarding the general population [ 31 ], the literature is clear about the potential of growth mindset intervention in supporting the academic development of high-risk and economically disadvantaged students [ 26 , 27 , 31 , 32 ].

The notion of human potential as something dynamic resonates with the concept of the plastic brain. Moreover, teaching students about neuroplasticity and the dynamic potential of their brains has been shown to effectively reinforce a growth mindset [ 32 ].

1.1.1. Using Neuroplasticity as Educational Content

Teaching students about experience-based neuroplasticity and the dynamic changes in neuronal networks during learning provides strong evidence of their natural and powerful learning capacity. Furthermore, teaching students about neuroplasticity with explicit connections to the growth mindset and development creates a motivating premise for learners—according to which their learning potential is dynamic and depends significantly on their attitudes and learning practices.

The neuroplasticity rules of “use it or lose it” and “use it to improve it” mean that, while teachers should support and guide them, learning occurs by and within the students. This physiology-based realization can help build students’ responsibility and ownership over their learning.

Harnessing neuroplasticity and a growth mindset to motivate students can be especially important with neurodivergent learners, whose cognitive development and learning styles deviate from the typical range. Twenty percent of the population is neurodivergent, including students on the autistic spectrum (ASD), students with learning disabilities (e.g., dyslexia), attention disorders (e.g., ADHD), neurological disorders (e.g., epilepsy), and mental illness (e.g., PTSD). While neurodiversity and variations in neuronal and cognitive expressions hold many advantages [ 33 ], neurodivergent students face extra challenges navigating neurotypical-oriented school systems. Learning about neuroplasticity can be a potent form of validation for neurodivergent students, as neurodiversity is a natural result of experience-dependent neuroplasticity [ 19 ]. In addition, by fostering a growth mindset and neuroplasticity awareness, neurodivergent students can be motivated to participate in evidence-based interventions. For example, teaching students with dyslexia about the specific structural and functional brain changes associated with the reading interventions that they apply [ 34 , 35 , 36 ] can motivate them to endure the hard work before noticing visible results.

1.1.2. Using Neuroplasticity to Guide Learning Design

Organizing learning systems around conditions that promote neuroplasticity can enhance learners’ academic development and wellbeing. When a student accomplishes today what was not in their reach yesterday, it is the product of neuroplasticity through a growth mindset.

Educational environments that promote neuroplasticity include encouraging and modeling a healthy lifestyle (physical exercise, a balanced diet, sufficient sleep, and regulated stress), —for example, educating students about the counter-productiveness of sleep deprivation (e.g., “all-nighter” study marathons) on learning. In addition, learning systems should invest in intellectual stimulation (novelty and challenge) and the system’s social and emotional climate (human connections). Neuroplasticity and development are optimal in the stretch zone, where learners experience a motivating level of challenge and stimulation while feeling emotionally supported and socially safe. This ratio between support and challenge should be individualized (between learners and within learners over time).

Educating teachers about neuroplasticity can be powerful in understanding and supporting students that were affected by trauma. Childhood adversity hampers neuroplasticity duration and magnitude [ 37 ]; a surviving brain is not a learning brain. While neuroplasticity is compromised by early trauma, neuroplasticity is also the key to healing from trauma. Schools have a pivotal role in battling the damage of early trauma by creating enriched and safe learning environments that reinforce alternative neuronal pathways to reverse the effects of early adverse environments on child brain development [ 22 , 38 , 39 , 40 ].

1.2. Learning Motivation and Reward

Learning and adaptation are essential for surviving and thriving in dynamic environments. The brain evolved to make sense of information from our external and internal environments and to produce adaptive behaviors that promote survival. The brain is, therefore, a learning machine by nature, and learning does not require external initiation. However, learning is highly experience-dependent and can be directed and enhanced through education.

The brain reward system evolved to reinforce effortful behaviors that are essential for survival (e.g., foraging, reproduction, and caregiving). Such behaviors activate the dopaminergic system associated with reward and motivation [ 41 ]. The hormone/neurotransmitter dopamine is a central player in reward-motivated behavior and learning through the modulation of striatal and prefrontal functions [ 42 ]. The human brain reward system balances between (limbic) impulsive desire and (cortical) goal-directed wanting to guide flexible decision-making and adaptive motivational behaviors.

Psychologically, intrinsic motivation is driven by the need to experience a sense of competence, self-determination, and relatedness [ 43 , 44 , 45 , 46 , 47 ].

Competence refers to a perception of self-efficacy and confidence in one’s abilities to achieve a valuable outcome. Self-determination refers to the sense of autonomy and agency in the learning process. Relatedness refers to the drive to pursue goals that hold social value, which can be achieved by working collaboratively as part of a team or by creating something that resonates with others. Relatedness is a strong motivational driver, as it touches on a primary and primordial need to be part of a group and a higher spiritual and intellectual need for self-transcendence and impact.

Overall, these components are based on the human inclination to be valued and validated by the self and others. Biologically, they reflect basic survival needs that combine self-reliance (competence and ownership) and social reliance. Psychologically, these are all subjective perceptions that serve the need to maintain positive self-perception and self-integration. Finally, educationally, they reflect the natural human curiosity and tendency to learn and develop continuously.

The human brain reward system in the 21st century is an evolutionary mismatch. There is a discrepancy between the conditions that the reward system evolved to serve and those that it often faces in the 21st century. The reward system evolved over millions of years to motivate humans to work hard (invest time and energy) in maintaining their survival needs (e.g., nutrition, protection, reproduction, and the learning of new skills). However, this system is not designed for the abundance and immediacy of stimulation in the digital and instant reward era, which promotes the persistent release of dopamine that leads to an increased craving for reward (seeking behavior; wanting) and a decreased sense of pleasure and satisfaction (liking) [ 42 , 48 ].

Some of the most significant challenges of modern education systems relate to the massive changes in how people consume information and communicate in the digital era. Digital platforms have become dominant in information consumption and communication, which provide access to unlimited information and reinforce immediate rewards.

1.2.1. Using Neuroscience (of Reward and Motivation) as Educational Content

The science of human motivation, including its evolutionary mismatch, can be utilized to shed some light on students’ struggles with learning motivation. It can further provide a framework for students to explore their motivational (approach or avoid) tendencies regarding learning and academic challenges. Moreover, learning the neuroscience underlying motivation and reward can raise students’ awareness and proactivity in managing and protecting their reward system. Since adolescence is the peak time for the initiation of substance use, and early onset imposes a higher risk of mental health and substance abuse disorders persisting into adulthood [ 49 , 50 , 51 ], neuroscience knowledge about the reward system and its vulnerability (especially during brain development) is essential educational knowledge that can help in the prevention and mitigation of teen addiction.

1.2.2. Using Neuroscience to Guide Learning Design and Intrinsic Motivation

While students of the digital era are the most stimulation-flooded and attention-challenged in human history, learning is a process that takes time, selective attention, and perseverance. Therefore, learning designs that harness students’ intrinsic motivation for training and the development of stamina and grit (skills that might be hampered in the digital era) are precious for students’ health and success.

Motivational drivers include an adequate level of challenge that fits the student’s sense of competence and that creates optimal arousal levels, opportunities to expand social relatedness and impact, and balance between support and autonomy (see the ZPD, Figure 1 ).

Importantly, in classroom learning, educators are required to manage the attention, motivation, and reward system of not one but many students, which is a complex task. The typical classroom presents a broad spectrum of learners with diverse learning needs and stretch zones ( Figure 1 ). While the facilitation of autonomy and the sense of competence varies between learners and requires personalized support, the social norms that promote learning are more ubiquitous and apply to most learners. While educators do not always have the resources to support students’ motivation individually, harnessing the social aspects of classroom learning is a manageable, effective strategy to elevate students’ motivation. Learning environments that demonstrate empathy, inclusiveness, and psychological safety have shown positive results in students’ behavior, self-esteem, motivation, and academic success [ 52 , 53 , 54 , 55 , 56 ]. Social motivation has been shown to enhance the encoding of new information (even if the content is not social) [ 57 ]. Learning-for-teaching and peer tutoring (one student teaching another student) effectively encode information into memory. Beyond memory improvement, peer tutoring has many further benefits to both the tutor and the learner in academic achievements [ 58 , 59 ], motivation, and ownership over the learning process and results in a deep conceptual understanding of the material [ 60 ].

The teacher’s demeanor is another controllable factor with a high potential to affect students’ motivation. For example, the literature points to teachers’ immediacy (creating physical and psychological closeness with students) as an effective way to enhance students’ engagement, learning motivation, and performance (including memory retention) [ 61 , 62 , 63 , 64 , 65 ]. Immediacy can be demonstrated through verbal and non-verbal gestures that communicate interest and personal connection (relating to personal stories, using animated voice and body language, creating eye contact, and using humor).

The research also indicates that, when students perceive the content as being personally relevant, they are more motivated to study [ 66 ]. Therefore, educators can actively make the learning content more relevant by using stories and real-life examples, making explicit connections and demonstrations of how the content may be relevant/applicable to the students, and giving students opportunities to reflect and share their connections to the learning material.

In summary, physiological and psychological approaches point to primary motivational drivers that direct engagement and investment in the learning process. Not surprisingly, these drivers that are anchored around social and intellectual needs align with the conditions supporting neuroplasticity discussed in the first part of this review.

1.3. Intrinsic and Extrinsic Processing in Learning and Meaning-Making

As the environment provides more information than the brain can handle, survival depends on saliency detection and attention management to direct perception and behavior. The brain constantly selects and attends to relevant input while suppressing irrelevant or distracting information [ 67 ]. Information that is valuable or urgent for survival and prosperity receives attention. Attention capacities (e.g., alerting, orienting, and controlling attention) are managed by several brain systems that interact and coordinate [ 68 , 69 , 70 ]. Top–down, cognitive-driven attention that fosters a goal-directed thinking process is associated with the dorsal attention network (consisting of the intraparietal sulcus and the frontal eye fields) [ 71 ]. This mechanism enables students to read a paragraph, listen to a lecture, think about the teacher’s question, or write an essay. A second attention system is bottom–up and stimulus-driven, and it orients attention to unexpected and behaviorally relevant stimuli. This ventral attention network consists of the right temporoparietal junction and the ventral frontal cortex [ 71 ]. This attention-grabbing mechanism enables the individual to respond quickly to urgent environmental demands, for example, moving away to prevent a struck-by-object accident. Flexible attention control depends on dynamic interactions and switching between the two systems and involves the central executive network (CEN) [ 68 , 70 ].

The insula and anterior cingulate cortex comprise the core structures of the saliency network [ 72 ], another major player in attention altering to emotionally salient stimuli through the interaction of the sensory and cognitive influences that control attention [ 72 , 73 , 74 ].

In addition to outward-focused attention, the human brain is also invested in inward-focused processing. Functional brain imaging studies of the human brain show a robust functional anticorrelation between two large-scale systems, one highly extrinsic and the other deeply intrinsic [ 75 , 76 , 77 ]. The central executive network (CEN) is an externally driven system and is paramount for attention control, working memory, flexible thinking, and goal-directed behavior. The core components of the CEN are the dorsolateral PFC and the lateral posterior parietal cortex (hence, the frontoparietal network) [ 72 , 78 ]. When the human brain is not occupied with external tasks, the default mode network (DMN) is activated. This internally driven cognitive network includes the posterior cingulate cortex (PCC) and the medial prefrontal cortex (MPFC) as core components. The DMN is thought to facilitate reminiscing, contemplating, autobiographical memory, self-reflecting, and social cognition [ 79 ]. Conversely, the DMN is immediately suppressed when the brain is engaged in externally driven tasks and stimulation.

Resting-state brain imaging studies revealed that the activity in the DMN during resting awake states indicates the quality of subsequent neural and behavioral responses to environmental stimuli [ 72 , 80 ]. Moreover, a high connectivity between “intrinsic” (DMN) and “extrinsic” (CEN) brain networks, and specifically emotional saliency, attention (extrinsic), and reflection (intrinsic) networks is associated with better cognitive performance, meaning-making, and broad perspective thinking [ 75 , 76 , 81 ]. These networks function antagonistically but are highly connected and balance each other. Furthermore, the anticorrelation between their function is associated with better task performance and positive mental health [ 79 , 82 ]. Recent studies also suggest that a causal hierarchical architecture orchestrates this anticorrelation between externally and internally driven brain activities. More specifically, that regions of the saliency network and the dorsal attention network impose inhibition on the DMN. Conversely, the DMN exhibits an excitatory influence on the saliency and attention system [ 79 ].

1.3.1. The Neuroscience of Extrinsic and Intrinsic Processing as Educational Content

Teaching students about the dynamics of the default mode and executive control network can help them understand how their brain processes information, the importance of each process (e.g., extrinsic and intrinsic), and their integration for meaningful learning. This knowledge can be applied as students explore and experiment with ways to enhance their learning and memory by intentionally engaging both intrinsic and extrinsic processing and integrating the two.

1.3.2. Using the Neuroscience of Extrinsic and Intrinsic Processing to Guide Learning Design

Traditionally, instructional education is based on learning objectives that are externally dictated and is focused on outward attention (stimulus-driven lectures and assignments). Mind-wandering has become the enemy of classroom teachers, as it indicates students’ lack of attention and poor learning.

Nevertheless, neuroscience research indicates that meaning-making and cognitive performance benefit from the interplay between extrinsic and intrinsic oriented attention and processing [ 56 , 75 ].

Learning instructions should consider the different attention mechanisms, evoking adequate arousal levels and leading to goal-directed thinking. Furthermore, students will benefit from an educational design that stimulates the natural interplay between “intrinsic” (DMN) and “extrinsic” (CEN) brain networks by incorporating external stimulation (e.g., presenting content), allocating time and space for intrinsic reflection (e.g., guided reflection and journaling), and integrating the two (e.g., guided class discussion and insights sharing) [ 83 , 84 ].

2. Discussion

2.1. teaching students about their developing brains.

As far as we know, humankind is the only species with access to the underlying mechanisms of its perception, learning, and inner workings. In addition, the human brain is endowed with a lengthy developmental period of approximately 25 years [ 85 , 86 ]. Therefore, schooling years are the prime time for neuroplasticity, and students can learn about their brains while they are highly malleable and can utilize this to amplify their learning and growth.

While students were traditionally required to choose whether to focus on the humanities or science fields, an integrative view is becoming increasingly common in academic institutes. Multidisciplinary studies have been shown to promote students’ positive learning and professional outcomes [ 87 ]. Teaching neuroscience from a dual perspective, both scientific/objective and humanistic/subjective, is a novel but natural bridge between the humanities and science fields.

Studying neuroscience with explicit connections to the lived experience of brain development and its behavioral manifestation can be academically and personally transformative for students.

Shedding a scientific light on students’ experiences as they unfold can support significant developmental processes during those years, such as improvements in executive functions, emotional regulation skills, meta-cognition, and social cognition [ 88 ].

Among the topics and burning issues of teens and young adults that neuroscience can offer insights into are selective and leaky attention [ 89 ], the reward system and addiction [ 90 ], the PFC–limbic developmental mismatch during adolescence [ 91 ], neurodiversity and inclusion, emotion regulation, and mental health [ 92 ].

Moreover, adding a personal layer to neuroscience studies fits the notion that personal relatedness and relevance are essential for learning motivation. Teaching neuroscience from a dual (scientific and personal) perspective and connecting neuroscience knowledge to a deeper understanding of the self and others can elevate engagement and nurture students’ passion for science and their ability to integrate and transfer scientific knowledge across contexts. In addition, similar to the effect of physical education, educational neuroscience can promote the awareness of brain health and encourage students to be intentional about their education and developmental trajectory.

2.2. Teaching the Way(s) the Human Brain Learns Best

Teaching students in brain-friendly ways means implementing principles that align with how the human brain encodes, consolidates, and retrieves information. Educational neuroscience points to the importance of a holistic and integrated view of cognitive, emotional, and social aspects to support learning and development [ 52 , 75 , 93 , 94 ]. Maintaining physical health, cognitive challenge, and emotional safety are essential factors in creating an enriched environment that supports neuroplasticity and learning.

Assessing the learning progress rather than the end product can encourage students to move away from rote memorization to more meaningful learning that carries on beyond the final exam.

Meaningful learning can be promoted by learning designs that encourage students to take experimental and explorative approaches, take risks, and make mistakes without detrimental consequences to their grades.

Furthermore, assessments throughout the learning process and not only at the end of it, using multiple sample points and low-risk tasks, can provide information on the student’s learning curve and allow for personalized and timely feedback that students can apply to improve their learning on the go.

These methods not only promote psychological safety but also align with the evidence-based practices of building long-term and accessible knowledge by spreading out the learning concept across time (spacing), practicing information retrieval from memory (recall), and integrating and transferring knowledge (the application of knowledge in different contexts) [ 95 ].

3. Conclusions

Brain knowledge is brainpower; teaching students about their developing brain can support their academic and personal development by deepening their understanding of science and humanities, their mental capacity, and their self-identity. Educational neuroscience is a promising field in teaching students about their brains and teaching them in brain-friendly ways to support them in becoming lifelong learners.

Funding Statement

This research received no external funding.

Institutional Review Board Statement

The study did not require ethical approval.

Informed Consent Statement

Not applicable.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Innovative 3D gold microelectrode arrays enhance understanding of neuronal network communication

by Liu Jia, Chinese Academy of Sciences

Understanding the dynamics of neuronal communication is crucial for advancing neuroscience research and developing effective therapies for neurological disorders.

Neuronal network models have been valuable in neuroscience, and provide high controllability and repeatability for studying brain functions, disease mechanisms, and the impacts of neurological drugs. However, traditional two-dimensional (2D) microelectrode arrays (MEAs) used for monitoring these networks have limitations, particularly in stability and signal-to-noise ratio, which hinder long-term recordings necessary for long-term studies .

In a study published in ACS Nano , a group of scientists led by Prof. Cai Xinxia from the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences, in collaboration with international colleagues, developed an innovative approach to investigating the dynamics of neuronal networks.

They significantly improved the ability to monitor and analyze communication within neuronal networks utilizing three-dimensional (3D) gold microelectrode arrays.

The scientists introduced a customizable, polymer-modified 3D gold microelectrode array capable of providing stable, high signal-to- noise ratio (SNR) recordings over extended periods. This innovation enables detailed exploration of cell communication within neuronal networks over extended periods, overcoming the deficiencies of planar 2D MEAs.

The 3D structure enhances electrical conductivity and biocompatibility, enabling more effective coupling with electrically active cell membranes.

The scientists applied directed spatial and temporal patterns of electrical stimulation to cultured neuronal networks, and monitored their dynamics over three weeks. By employing correlation heatmaps and mutual information networks, they quantified the networks' synaptic-based communication and connectivity.

Analysis of synaptic delay and signal speed between cells led to the development of a communication connectivity model, revealing dynamic changes in network communication over time.

The findings of this study provide a valuable tool for future studies on neuronal network dynamics. The ability to monitor communication changes within these networks can enhance the understanding of both healthy brain function and disease mechanisms.

Journal information: ACS Nano

Provided by Chinese Academy of Sciences

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EDITORIAL article

Editorial: 15 years of frontiers in cellular neuroscience: myelination and remyelination processes.

$\r\nQingchao Qiu$

1 Department of Veterans Affairs, Michael E. DeBakey VA Medical Center, Houston, TX, United States
2 Department of Neurology, Houston Methodist Research Institute, Houston, TX, United States

Editorial on the Research Topic 15 years of frontiers in cellular neuroscience: myelination and remyelination processes

Introduction

Myelin, the insulating sheath around nerve axons, plays a critical role in the conduction of electrical signals within the nervous system ( Nave, 2010 ). Comprising nearly half of the brain's white matter and even more in peripheral myelinated axons, myelin is essential for proper nervous system development and maintenance. Myelin sheaths are lipid-rich substances produced by oligodendrocytes in the central nervous system (CNS) and Schwann cells (SCs) in the peripheral nervous system (PNS) ( Figure 1 ) ( Balakrishnan et al., 2020 ; Yu et al., 2023 ). One oligodendrocyte in the CNS can insulate several axons, unlike SCs in the PNS, which wrap around only a single axon. Decades of research, propelled by cutting-edge technologies, have significantly advanced our knowledge of myelin's structure, functions, and the dynamic processes of myelination and remyelination. Myelination, regulated by a precise genetic program, is essential for developmental neurobiology and ongoing neuronal function and integrity ( Sock and Wegner, 2019 ). Disruptions in myelination, seen in conditions like multiple sclerosis, Guillain-Barre syndrome, and Charcot-Marie-Tooth disease, can result in severe neurological deficits ( Mehndiratta and Gulati, 2014 ). However, the nervous system can repair itself through remyelination, a regenerative process where damaged myelin sheaths are repaired or replaced. This process is carried out by glial progenitor cells in the CNS and residual SCs in the PNS ( Momenzadeh and Jami, 2021 ). Understanding these mechanisms is key to developing treatments for a wide array of neurological disorders, highlighting the importance of myelination and remyelination in neurobiology. This editorial synthesizes findings from two reviews and two research articles, shedding light on the latest advancements in neuroimaging and cellular biology that enhance our understanding of myelin dynamics in both healthy and diseased states of the nervous system.

Figure 1 . Illustrates the processes of myelination and remyelination in both the CNS and PNS. (A) In the CNS, the process starts with oligodendrocyte progenitor cells and progresses through several stages to produce myelinating oligodendrocytes. Following demyelinating injuries, these progenitor cells migrate, proliferate, and differentiate at the injury site, leading to remyelination by forming new myelin sheaths. (B) In the PNS, Schwann cells evolve from neural crest cells through several developmental stages, culminating in mature myelinating or non-myelinating Schwann cells. These mature cells are pivotal in forming the myelin sheath, which is essential for insulating axons, thereby enhancing the speed and efficiency of electrical signal transmission across nerve fibers. Damage to these cells can lead to demyelination, with adjacent Schwann cells undergoing dedifferentiation and redifferentiation to support nerve regeneration. Created with BioRender.com .

Articles in this Research Topic

Modern neuroimaging techniques provide crucial insights into myelin dynamics in the human brain, both under normal and pathological conditions ( Laule et al., 2007 ). The review by Kujawa et al. presents new magnetic resonance imaging (MRI) techniques and biophysical models to map myelin in vivo , highlighting the potential of physical exercise to influence myelination and remyelination in the human brain. It details current research, including four cross-sectional studies, four longitudinal studies, and a case report, showcasing the beneficial effects of an active lifestyle on myelin content across all ages. The findings suggest that intensive aerobic exercise can induce myelin expansion, underscoring the importance of exercise in managing demyelination in aging and neurodegenerative conditions. This review advocates for further research to determine the most beneficial exercise intensities for neurological health, making it an invaluable asset for clinical and research applications.

The remarkable adaptability of SCs is crucial after nerve damage or in cases of demyelinating neuropathies, where they first dedifferentiate and then redifferentiate to aid in nerve regeneration and recovery ( Boerboom et al., 2017 ). The review article by Zhang et al. discusses the critical issue of delayed peripheral nerve injury (PNI) repair in elderly patients, focusing on the role of aging SCs. As the primary facilitators of nerve repair, SCs orchestrate various reparative functions, including demyelination, secretion of neurotrophic factors, and axon remyelination. This review highlights how structural and functional changes in aged SCs contribute to diminished nerve repair capabilities that result in chronic pain, muscle atrophy, and severe disability. Exploring these age-related alterations emphasizes the urgent need for further research into SC biology to potentially enhance therapeutic strategies for PNI in the elderly.

The specific localization of proteins within the nervous system's various cells is crucial for their functionality, impacting nerve development and maintenance ( Sock and Wegner, 2019 ). The study by Fazal et al. focuses on the distribution and functionality of SARM1 in myelinating glia cells, addressing whether its dysfunction could impact neuropathology or interfere with myelination therapies. The study reveals that while SARM1 mRNA and protein are present in oligodendrocytes, with activation leading to cell death, it is notably absent or non-functional in peripheral glia such as SCs and satellite glia. This suggests that therapeutic strategies targeting SARM1 to preserve axons in nervous system diseases are unlikely to affect myelination negatively. The findings also underscore that SARM1 is not necessary for the initiation or maintenance of myelination in both the central and peripheral nervous systems. This research crucially informs the development of SARM1 inhibitors as potential treatments for neurological disorders, providing a clearer path for targeting this protein without harming myelin integrity.

Demyelinating diseases cause severe long-term neurological damage. Promoting remyelination can restore nerve function and prevent further neuronal loss and clinical disability, driving research into drugs that could enhance remyelination for therapeutic use ( Harlow et al., 2015 ). Cisneros-Mejorado et al. explore the potential of β-carbolines to enhance remyelination in a rat model of demyelination in the inferior cerebellar peduncle (DRICP model). Employing the DRICP model, the authors induced demyelination using ethidium bromide, confirming the damage histologically and assessing it with diffusion-weighted MRI. The study evaluated the remyelinating effects of three β-carbolines that modulate the GABAA receptor in oligodendrocytes. Notably, the N-butyl-β-carboline-3-carboxylate (β-CCB) and ethyl 9H-pyrido [3,4-b]indole-3-carboxylate (β-CCE) demonstrated significant efficacy in promoting remyelination as evidenced by improved dMRI metrics and increased myelin content histologically. These findings suggest that specific β-carbolines could be promising in therapeutic strategies targeting white matter recovery.

Concluding remarks

The Research Topic of articles reviewed herein not only enrich our understanding of myelin dynamics in both normal and pathological states but spotlight the intrinsic capability of the nervous system to adapt and repair itself. From enhancing our grasp of neuroimaging techniques to unraveling the molecular intricacies of myelination and remyelination processes, these studies contribute to neuroscientific progress; in addition, they emphasize the potential of targeted physical and pharmacological interventions to mitigate or reverse the effects of demyelinating conditions. As research continues to evolve, these insights hold the promise of improving diagnostic, therapeutic, and preventive strategies in neurology, thereby bettering patient outcomes in the face of debilitating neurological diseases. This underscores the critical importance of ongoing research in myelin biology as a cornerstone for advancing our approach to neurological health and disease management.

Author contributions

QQ: Methodology, Software, Writing – original draft, Writing – review & editing. BH: Conceptualization, Software, Supervision, Writing – original draft, Writing – review & editing.

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. QQ was supported by a Veteran Affair RR&D Career Development Award (1IK1RX003985-01A1). BH was supported by a National Institute of Neurological Disorders and Stroke grant (R01NS124813).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Balakrishnan, A., Belfiore, L., Chu, T. H., Fleming, T., Midha, R., Biernaskie, J., et al. (2020). Insights into the role and potential of Schwann cells for peripheral nerve repair from studies of development and injury. Front. Mol. Neurosci. 13:608442. doi: 10.3389/fnmol.2020.608442

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Harlow, D. E., Honce, J. M., and Miravalle, A. A. (2015). Remyelination therapy in multiple sclerosis. Front. Neurol. 6:257. doi: 10.3389/fneur.2015.00257

Laule, C., Vavasour, I. M., Kolind, S. H., Li, D. K., Traboulsee, T. L., Moore, G. R., et al. (2007). Magnetic resonance imaging of myelin. Neurotherapeutics . 4, 460–484. doi: 10.1016/j.nurt.2007.05.004

Mehndiratta, M. M., and Gulati, N. S. (2014). Central and peripheral demyelination. J. Neurosci. Rural Pract. 5, 84–86. doi: 10.4103/0976-3147.127887

Momenzadeh, S., and Jami, M. S. (2021). Remyelination in PNS and CNS: current and upcoming cellular and molecular strategies to treat disabling neuropathies. Mol. Biol. Rep. 48, 8097–8110. doi: 10.1007/s11033-021-06755-6

Nave, K. A. (2010). Myelination and support of axonal integrity by glia. Nature . 468, 244–252. doi: 10.1038/nature09614

Sock, E., and Wegner, M. (2019). Transcriptional control of myelination and remyelination. Glia . 67, 2153–2165. doi: 10.1002/glia.23636

Yu, Q., Guan, T., Guo, Y., and Kong, J. (2023). The initial myelination in the central nervous system. ASN Neuro 15:17590914231163039. doi: 10.1177/17590914231163039

Keywords: myelination, remyelination, demyelination, glial cells, oligodendrocytes, Schwann cells, neuron, axon

Citation: Qiu Q and Hu B (2024) Editorial: 15 years of frontiers in cellular neuroscience: myelination and remyelination processes. Front. Cell. Neurosci. 18:1463579. doi: 10.3389/fncel.2024.1463579

Received: 12 July 2024; Accepted: 26 July 2024; Published: 09 August 2024.

Edited and reviewed by: Marie-Ève Tremblay , University of Victoria, Canada

Copyright © 2024 Qiu and Hu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Bo Hu, bhu@houstonmethodist.org

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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The Center for Global Mental Health Research Webinar Series 2023: Real-World Opportunities and Challenges: Using NIMH's Research Domain Criteria (RDoC) Framework in Global Mental Health Research

September 20, 2023

LEONARDO CUBILLOS : Good morning, good afternoon, and good evening to all of you joining this exciting webinar. We appreciate you taking the time to participate and learn along with us. Welcome to today’s webinar. The title of the webinar is Real World Opportunities and Challenges: Using NIMH’s Research Domain Criteria, RDOC, Framework in Global Mental Health Research.

My name is Leonardo Cubillos, and I am the Director of the Center for Global Mental Health Research. Today’s webinar is the third of the 2023 webinar series in the Center for Global Mental Health Research, and will be the last we will host this year.

And today we will discuss what is RDOC, what is that thing called the Research Domain Criteria Framework, and how can we use that to advance diagnosis, prevention, intervention, and cures in global mental health research, and potentially in global mental health services, real world services.

We will hear from our NIMH RDOC team that I will be introducing in a second. And you will also hear from different researchers who are working in using RDOC in different parts of the world. So we will hear the concept and the framework, and we will also learn from the applications in different parts of the world.

As mentioned at the beginning, this webinar is recorded and will be archived and made available on our website. You will find the website where you can find them at the end of today’s webinar.

Without further ado I would like to welcome my NIMH colleagues who are leading the RDOC framework, the RDOC team. There are a number of them here joining us. I will not introduce all of them, because my Colleague Rebecca Berman will be taking the lead in presenting both the concept of RDOC as well as very importantly the team members who have conceptualized and led this effort. So colleagues from NIMH and colleagues in the research arena who are joining here today, thank you for your time. Thank you. Over to you.

REBECCA BERMAN : Thanks, Leo. We really appreciate this chance to talk about the RDOC framework and be part of this conversation. Let me share my screen. This is going to take another minute I think. And I’m not great at multitasking. But maybe the rest of the RDOC team, while I’m doing this, can just come on and give a brief hello. Bruce Cuthbert, Sarah Morris, Jenni Pacheco and Syed Rizvi.

SARAH MORRIS : Good morning everybody. I’m so glad to have everyone joining the webinar today. We’ve had a great time planning this, and are really happy to see it come to fruition. I’m Sarah Morris, and I’m the Deputy Director of the RDOC Unit here at NIMH, and also a Branch Chief in the Division of Translational Research.

BRUCE CUTHBERT : Hello everyone. I am Bruce Cuthbert, I am Head of the RDOC Unit, and have been leading this effort since I rejoined NIMH in 2009.

JENNI PACHECO: I am Jenni Pacheco, I’m a Scientific Program Manager with the RDoC Unit, and also a program officer in the Division of Translational Research.

SYED RIZVI : Hi, I am Syed Rizvi, the RDoC administrator.

REBECCA BERMAN : And I am Rebecca Berman, I’m a Scientific Program Manager, I joined the RDoC team last year. And hopefully this slide is now visible. So today’s webinar will have four main parts. I will give a brief introduction to the Research Domain Criteria or RDoC framework. Then we are really excited to have with us two groups of researchers that can speak directly to the experience of trying to integrate RDoC principles in global mental health research.

First we’ll hear from Drs. Stein, Wootton and Majara about their work in South Africa, and that will be followed by a presentation from Drs. Patel and Bhavnani on their work in India. And we hope to have time at the end for your questions, as Jeremy mentioned earlier you can put those into the chat.

So here is my title, an introduction to the framework, and I will offer some potential synergies. I want to acknowledge the RDoC team. You had a chance to just meet them now. And I have no disclosures to report.

So what is the Research Domain Criteria initiative? Put in some really simple terms, this is a framework for doing research that explores new ways of classifying and understanding mental disorders. Critically it is not limited to diagnostic categories. And instead, it is based in functional systems that we can measure. And in this introduction I hope to convey the why, the what and the how of RDOC. So why was this framework developed, I’ll tell you more about what it involves, and I will give you some examples about how researchers can use RDoC in their studies.

So, why RDoC? This initiative was launched in 2010 to help address some of the limitations to using diagnostic approaches in research. And so you may be familiar with the DSM, the Diagnostic Statistical Manual, or the ICD, International Classification of Diseases. These are established standards, and really valuable for a range of purposes, but they can have limitations in some contexts, including for research. So I will highlight three of the challenges that can be present in using these diagnostic approaches.

One is that these current diagnostic systems remain based on clinical symptoms and signs, what a patient can report or a clinician can notice. And often this gives an incomplete picture of what is going on with an individual, particularly because these things may happen only within say a single visit. So offering some limited information.

Second, these diagnostic systems encourage us to think about disorders as distinct categories. Healthy versus sick. Whereas we know that many mental health issues exist along a continuum, from normal to abnormal.

And lastly, I think it is well recognized that these diagnostic categories represent relatively broad syndromes. So this introduces problems both with comorbidity, which is having more than one diagnosis. So an individual may have for example a diagnosis of both depression and anxiety.

And on the flipside, there can be issues with heterogeneity, having a lot of variability within a diagnostic category. And I just want to offer one brief concrete example of this heterogeneity, which comes from the criteria for major depressive disorder. So these are simplified phrasings of the nine criteria for depression diagnosis. To receive that diagnosis one has to have five of these nine criteria.

So you can see that you can get a diagnosis of depression with these five, and another person may have these other five symptoms. So almost entirely non-overlapping. So you can have relatively different symptomatology but have that same label. You can imagine if you’re doing research to understand what’s going on in depression, or how you might want to intervene for a given individual, this can be a real barrier.

So together these challenges with the diagnostic systems make it hard to both discover the causes of psychopathology and to predict individual outcomes and find effective interventions. RDoC was introduced as a way to help address some of these problems from a research perspective.

So that’s the why of RDoC, and now turning to what it is. This graphic is representing the four components of the RDoC framework. It is a diagnosis agnostic approach to mental health research. It’s based in, as we see in this light blue color, functional domains that have their foundations in basic biobehavioral science. I’ll go into this in more detail on the next slide, but the idea is that these are functions that you can measure across a range of disorders, and also in the general population.

A second component is that RDOC encourages the use of multiple integrative measures. Those are shown and called these units of analysis. So it can range from genetics, brain function, behavior, environmental measures, and including self-report.

Third, RDoC emphasizes that there is an important role in understanding development across the lifespan. Not just early development, as a real opportunity for things like early intervention and prevention, but understanding changes over time and in relation to aging.

And fourth, RDoC recognizes that all this happens within the context of environment, so there is an important need to understand environmental influences, including both the physical and cultural environment, and things like social determinants of health.

So on the next slide I am going to explain a little bit more about these functional domains. The domains are shown here in the center. At the moment there are six functional domains that have been proposed. And on the outside in these boxes are different examples of sub-processes, or more specific functions, for each of the domains. These are called constructs. These domains and constructs were proposed in a series of consensus workshops that took place after RDoC was launched in 2010.

And the idea again is that they are meant to represent basic functions. So we have things like social processes, cognition, sensory motor function. Up at the top we have systems related to how the body regulates itself, so things like sleep and arousal. And then over on the left you see what are called the valence systems, which have to do with affect and emotion. So on the positive side we have things like how we respond to reward, and on the negative things like fear and anxiety.

So how could we use these domains and constructs to study mental health and psychopathology? So now we’re moving into the how part. And shown on the next slide, these are some examples of using domains and constructs to measure psychopathology. There is kind of a lot here, so I am just going to focus on this top part, this top example from cognitive systems, and really just on this first concept or construct of working memory.

So working memory is something that we know can be impaired in multiple disorders in mental health. For example, it’s prominent in schizophrenia, but it can also be prominent in depression. And it’s also true that people who have a diagnosis of either depression or schizophrenia may not have working memory impairment. So by studying working memory we may have an opportunity to get more insight into the nature of these disorders, and also have a chance at understanding ways to have more tailored intervention.

So another part of this slide emphasizes that for example in the construct of memory impairment you could measure this in multiple different ways. And so this graphic in the top right represents what we call the units of analysis, different modalities that you could use to measure memory impairment.

For example, you can use a working memory task. You might look at genetics or brain function related to working memory performance. You can ask patients to self-report on their perceived difficulties with memory or ask a caregiver to make an assessment as well.

And by bringing these different measures together the idea is that we can get a more complete picture of what an individual is experiencing and how we might tailor an intervention. So it is similar to other areas of medicine where we can integrate multiple measures to improve both assessment and care.

So on the next slide I’m going to give an example of a research study that illustrates these RDoC principles in practice. This comes from a study called the Bipolar-Schizophrenia Network on Intermediate Phenotypes. It’s called B-SNIP for short. And in this study they looked at patients who had diagnoses of schizophrenia, schizoaffective disorder, and psychotic bipolar disorder.

But rather than looking at each of these diagnostic categories separately, they combined them into one group, because all of these individuals experience psychosis. And then they asked can we understand or classify these patients in a different way, by combining multiple measures to assess them.

And what they found is that by using a combination of cognitive and sensory motor measures, they were able to cluster these patients into three new groups, that’s shown in the upper corner, with the red, green, and blue. And they define these as biotypes.

And what they found was that these clusters were validated using another set of independent measures that they collected on the same subject, having to do with brain function and structure and genetic heritability. And they’ve since replicated this finding in a new set of individuals.

And in addition, they’re now running a clinical trial to ask whether these biotypes can predict responsiveness to the antipsychotic drug clozapine. And in addition to this clinical trial they are also doing some studies asking whether the biotypes can predict how well a given patient may respond to coordinated specialty care in a community setting. So really a nice example from this group of taking multiple measures and looking across diagnostic boundaries to ask if there are ways we can better understand and offer some interventions.

So for the sake of time I’m going to not walk through this example, but I just want to point out that this is another way to use RDoC principles, looking at variability within a disorder, in this case ADHD. And this one is also a nice example because it uses relatively simple measures, asking about temperament and cognition.

So to distill out some of these ways that you can use RDoC principles in research, as I’ve described one way is to use new research designs or sampling methods that go beyond just patient and control, whether that’s looking across diagnoses or at variability within a category. You can also be looking at expanded control groups, like family members or less healthy controls, or sub-threshold symptomology.

Another principle is to consider this range of functionality, looking at a continuum rather than just the categories. To integrate multiple measures, as we have given some examples of. And lastly to consider this in the context of neurobehavioral processes or functions. And for more details and examples, I recommend this paper that the RDoC group published last year: Revisiting the Seven Pillars of RDoC. It’s a great resource.

So I’ll close with a few benefits and challenges. These are not specific to global mental health research, but that can be relevant. One is that RDoC offers a flexible research framework. So because it’s not limited to the traditional disease categories, researchers can pursue the ideas that are most relevant for the communities they’re working with.

And secondly, it is an opportunity to develop or bring together meaningful measures. Again, the idea of using different measures and modalities as a way of helping to understand different patient populations and who might benefit from particular interventions. So really moving toward more personalized medicine.

Potential challenges. There are potential limitations of a neurobehavioral model. So these currently defined functions and constructs are a work in progress. They may not be valid in all settings. So it’s important to take that into account and be flexible.

And secondly I think there is an expectation that RDOC studies have to be resource intensive, and many historically have involved complex or costly measures. It’s not a requirement, for example neural measures are not needed, you don’t need to get EEG or Magnetic Resonance Imaging or something costly. However, I think resources are still going to be a factor, and this is an important place for conversation and discussion.

So to close with some potential synergies, bringing back of the framework. Areas of mutual interest and benefit include the role of development in lifespan, early detection and prevention are things where the global community has deep and broad expertise, and I think there is real potential here in this space. And similarly, with environmental influences, whether it’s physical or cultural environment or social determinants, this is another area for potential synergy that can have an impact not just in the global space but also domestically.

And finally, the idea that together we can arrive at expanded views of fundamental functions and measures that are really clinically meaningful for the people we are serving. So with that I thank you for your attention, thanks to the RDoC Unit. And I think we may have time for a few questions for clarification on the concept. And if we don’t get a chance to address them here you are always welcome to email us at [email protected] . I’m going to stop sharing my slides, although I do want to show a slide later to introduce our speakers.

LEONARDO CUBILLOS: Thank you. At the moment we have not yet received questions. To all participants around the world, please remember that you can type your questions in the Q&A box. Some of them we can answer live, some of them we will write the responses. But at the moment, we just received one. Jared says are the slides available. The reporting of the slides will be made available. Are the slides themselves available?

REBECCA BERMAN : Yes. We can share the slides. I believe so. I will probably have to run it by clearance, but it will be fine.

LEONARDO CUBILLOS: John asks what has the level of adoption across the world been. And then kind of a related vein Jared who asks do you have studies in Africa.

REBECCA BERMAN : You will be hearing from our speakers in just a moment on work in South Africa. I think, in terms of the adoption of RDoC principles, this is something we found difficult to quantify even for studies funded by NIMH. But I think it is, I would speculate that it is safe to say that we have more to do in the global setting, which is partly why we are so excited to be part of the webinar today and have the guests with us today that we do.

LEONARDO CUBILLOS : I will add to that response, Becky, that those of us working specifically in global mental health research believe that RDoC has a tremendous untapped potential to advance as I said earlier prevention, intervention, and there’s a link here. So we welcome this webinar tremendously. Ritha asks do you have data on lessons learned by using this framework. That I would argue Ritha we’ll be hearing more from our presenters. Scanning through the question, Rama Krishnan(ph.) asks where can we find the entire series reporting? And I am going to type for everyone’s benefit a URL where you can find them. I just pasted it for everyone. Michael Goodwin asks are there any ways you imagine the RDoC framework being deployed differently in the global setting US based settings (inaudible).

REBECCA BERMAN : I think that is a great question. I think that would be better addressed in our later Q&A with all of our speakers who can likely speak to that with a much clearer and direct sense. And given the time, unless there is something that would help clarify on the framework, I think we could go ahead and introduce the speakers.

LEONARDO CUBILLOS : I will ask just one additional question. David Batenkiber(ph.) asks are there specific grant opportunities related to RDoC.

REBECCA BERMAN : I believe there are at present, someone can correct me, we have some related to computational methods. Those can be found on the RDoC website. And Syed, thank you for putting that in the chat. There is a link within that website for current funding opportunities. We had one that just closed recently but I think if we have an opportunity to talk more about later, is really moving in the direction of trying to find more scalable and low burden assessments that use behavior in combination with clinical records data. That’s called Impact MH. We may be able to get a link up about the Director’s Blog on that project.

LEONARDO CUBILLOS : And to query for additional or new information in RDoC, you can always email the RDoC team. Over to you, Becky.

REBECCA BERMAN : I want to now introduce our speakers. I hope you can see this slide. We are again really honored to have with us today these two groups. I’m going to introduce right now, and go into more detail on the speakers for this first presentation, and then I will come back in, probably without a slide, and just introduce the second set.

So in this first set, we have Dan Stein. Dr. Stein is a professor and Chair of the Department of Psychiatry and Mental Health at the University of Cape Town, and Director of the South African Medical Research Council’s Unit on Risk and Resilience in Mental Disorders. He is interested in research on anxiety and related disorders, in building mental health research capacity in the African context, and in work at the intersection of philosophy and psychiatry.

Also in this group we have Dr. Olivia Wootton. She is a medical doctor and PhD candidate at University of Cape Town, and her research focuses on the contribution of common genetic variants to cognitive function, both in the general population and in those living with schizophrenia. She is especially interested in the clinical relevance of neurogenetic research and on prognostic and diagnostic assessments, as well as treatment strategies.

And we’ll also hear from Dr. Lerato Majara, who is a postdoctoral research fellow on the Neuropsychiatric Genetics in African Populations, called NeuroGAP project. And she’s a member of the Global Initiative Of Neuropsychiatric Genetics Education and Research or the GINGER Program at the Harvard School of Public Health. And her expertise is in the genetics of psychiatric disorders and polygenic risk across and within different African populations. So at this point I will turn this over to Dan. Thank you very much.

DAN STEIN : Thanks for that introduction and for the invitation to be here. It is a fascinating topic. So what I’ll do for this talk is address some of the conceptual issues, actually very much in line with what Rebecca has talked about, one or two practical exemplars, then Olivia and Lerato will speak to their work.

I think one can easily contrast global mental health with what Tom Insel has called Clinical neuroscience. They have quite different perspectives and principles and contrasting approaches to diagnosis, etiology, and treatment.

Global mental health would emphasize that mental disorders are a major contributor to the burden of disease worldwide, and that there is a large treatment gap, particularly in low- and middle-income countries. There is a need for more research on how to provide, and importantly to scale up services in these settings, as well as under-resourced settings in general.

Clinical neuroscience on the other hand says that psychiatry can be thought of in terms of a focus on brain disorders, and that if we understand the biobehavioral underlying functional systems that Rebecca referred to, we will have new approaches to understanding assessment, new approaches to understanding etiology and intervention. And importantly there is a key need for more translational research, moving from bench to bed.

So one you could argue is founded in individual biology. The other is focused on public mental health. One emphasizes basic research. The other implementation research. And one is funded by tens of thousands of dollars, the other by tens of millions. And in a sense they are quite opposing.

On the other hand, there are important synergies, as Rebecca mentioned. Both have a long history, and an important role. And it’s interesting that consensus views emphasize the need for both. So this particular article which came out a few years ago which Vikram was involved in and I was involved in, led by Pamela, really emphasized the importance of both public mental health and clinical neuroscience.

And we can see that if we think about diagnosis, because of course there is a potential contrast between ICD-11 and the RDoC approach to assessment. But at the current stage there does seem a need to employ both approaches. And in this article my colleagues and I emphasize that we need to be careful about talking about paradigm shifts in psychiatry research. What we need is, we would argue, incremental integration.

Similarly, when it comes to etiology, there is potentially a contrast between biological mechanisms and social determinants. But the reality is, I think we can all agree that the causes of mental disorder are complex and multi-level. I love the work of Ken Kendler in particular, who writes beautifully about pluralism.

And then finally, in terms of intervention, I have contrasted discovery and implementation science, but of course both are important, as this article emphasizes.

In the South African setting, one practical example that I would like to speak to briefly is the Drakenstein Child Health Study. This is a birth cohort study in a peri-urban area that is representative of many under-resourced communities in the Global South, and perhaps also some under-resourced communities elsewhere.

And we think that it is important to assess a range of biological and psychosocial factors, very much in line with the principles of RDoC as Rebecca mentioned them. And this range of factors contributes to various dimensions of neurodevelopment and psychopathology. Again, Rebecca’s slide comes to mind where she talks about multiple integrated measures, the importance of development across the lifespan, and the importance of looking at environmental and social determinants.

And so the papers that have come out of this birth cohort I would propose to you sort of exemplify this kind of integrative approach, addressing both biology and social determinants, looking at things across the lifespan, and using a range of different measures.

Another study that we’ve been involved with is one of the neurocircuitry of obsessive-compulsive disorder. These are both NIH funded, I should mention. The Drakenstein is NIH funded, and this is NIH funded. In five different countries, including three in the global south. And again, our emphasis is a range of biological and psychosocial factors which we think contribute to variability in brain circuitry and neuropsychological dimensions.

The question was raised how do you do this kind of work in the global south? And it’s not easy, I think. We worked incredibly hard to ensure harmonization of multiple measures, both measures of social determinants as well as biological measures require harmonization across the different sites. And in this slide, you’ll see some of the papers on that.

We will focus the rest of our talk on schizophrenia in the Xhosa population of South Africa, the Neuro-Gap Study, which again is NIH funded. And this looks at the genetics of severe mental disorders, ranging across schizophrenia and bipolar disorder. And here while genetics is a key focus, we also assess environmental factors, and neuropsychological assessment starts to include an RDoC approach.

There are actually two studies. The one is a Neuro-Gap Study, but Dr. Wootton will actually be talking to the SAX Study, both are NIH funded. So it turns out that much of what I’ve been saying comes from an article that Vikram and I wrote a while ago now, which addressed this issue of global mental health and neuroscience. And we argued that the Global South is well placed to address the synergy between global mental health and clinical neuroscience. We love it when Cape Town is right there at the top of the world.

So, in conclusion, global mental health and clinical neuroscience have certainly advanced, but a huge amount of more progress is needed. And there are wonderful opportunities for synergy. I’m now going to hand over to Olivia, who will talk about the SAX study, Schizophrenia and Xhosa, looking at cognitive systems and psychoses, and as Rebecca mentioned she is on the MD PhD track. Over to you, Olivia.

OLIVIA WOOTTON : Thanks very much Dan. Good afternoon, everyone. I will be continuing this talk by focusing in on cognitive systems and psychosis research in the South African context. So, cognition is one of the major domains of functioning defined by the RDoC framework.

And cognitive impairment is a feature of schizophrenia and major determinant of functional outcomes in the disorder. We know that environmental and genetic factors contribute towards cognitive impairment in the disorder. However, understanding how these factors interact, as well as when these factors exert their effects, remains limited.

And over the past couple years there has been increasing interest in identifying potentially modifiable risk factors for cognitive impairment in order to improve functional outcomes and mitigate disability associated with schizophrenia.

Now, when it comes to low- and middle-income countries, two things come to mind which are important within the context of global mental health and RDoC. The first is that there is a lack of regionally representative data, which means that not only is it difficult to assess the disability caused by cognitive impairment in the disorder, but there is also a lack of data with which to inform early interventions and preventative strategies.

So there’s a need to improve the availability and the utility of cognitive assessments, and this includes steps such as the gathering of normative data, as well as training and capacity development, and establishing the psychometric properties of known cognitive assessments in different contexts.

So as Dan alluded to earlier, the Genomics of Schizophrenia in the South African Xhosa People Study, or the SAX study, provided a great opportunity to collect neuropsychological data while also investigating the genetic basis of schizophrenia in the Xhosa population of South Africa.

So not only was genetic data collected during the study, but we also collected data on cognitive function as well as the social determinants of health. So this study recruited participants from two regions in South Africa, the western and the eastern cape, and it’s run in two phases.

The first phase ran from 2013 to 2018, during which just under 3000 participants were recruited. And the second phase is currently ongoing and started in 2018. And we’re planning to enroll an additional 2500 participants. And cases for this study are defined as individuals with schizophrenia or schizoaffective disorder.

So a neuropsychological assessment that we’re administering as part of the SAX study is the University of Pennsylvania Computerized Neurocognitive Battery, which is a web-based tool that provides a reliable, efficient battery of cognitive assessments. And this computerized neurocognitive battery was designed to assess the cognitive domains and their underlying brain networks through the application of neurobehavioral probes that have been validated with functional neuroimaging.

So the PennCNB has a core battery which consist of 17 tests across six neurobehavioral domains that correspond to certain RDoC constructs. And this core battery has demonstrated adequate psychometric properties in multiple studies in Western settings. But over the past few years there have been efforts to validate this battery and adapt it for use in other contexts. And one of these adapted batteries is the Xhosa CNB, which consists of 10 tests across five domains that are known to be associated with schizophrenia.

So the process of adapting and validating the PennCNB for use in the SAX study is described in this paper by Jacob Scott and colleagues, and it started with the translation and adaptation of the battery, which included steps such as running the battery past our Community Advisory Board to ensure acceptability. Translating the tests following the WHO translation guidelines. And adaptation of the tests based on feedback from our administrators as well as a select group of participants. And this included steps such as increasing the number of practice trials as well as modifying instructions to improve understanding amongst participants.

The next step was to assess the feasibility of administering a computerized cognitive battery in the South African healthcare setting. And this included ensuring that there are resources available to facilitate the standardized administration of the test, as well as assessing tolerability and completion rates.

And lastly, the validity of the adaptive battery was assessed. And this included factor analysis to test for structural validity, as well as assessing construct validity by testing whether or not known predictors of CNB performance remain significant within the SAX sample.

So as I mentioned, this is the paper by Jacob Scott and colleagues. But to summarize, most tests were well tolerated within the South African setting and were administered successfully to over 90 percent of participants. Factor analysis confirmed the psychometric validity of the battery, with most tests loading on the expected cognitive domain. And lastly, there was evidence of concurrent validity with sex, age, and diagnostic group differences in the SAX sample being consistent with those that have been observed in other studies.

So lastly, the collection of neuropsychological data as part of the SAX study has provided an opportunity for multiple further investigations that are in various stages. So some are in manuscript and preparation, and others have been published already. But the studies focus on two main areas. This is the relationship between cognitive functions and environmental factors, which we know is one of the focuses of RDoC.

So we’ve got groups looking at the relationship between early childhood adversity and cognitive function. Another group of researchers looking at the relationship between early childhood adversity, social cognition and aggression in schizophrenia. And lastly, for my PhD I was able to look at the relationship between demographic and clinical predictors of impaired cognitive performance in schizophrenia in the SAX sample.

So all of this research has been able to add to this vast body of literature on neuropsychological function in schizophrenia in a low- and middle-income setting, and ultimately can hopefully be used to help inform health policy and prevention strategies.

The second set of research studies involve the integration of multiple units of analysis. So we have opportunities to integrate the genomic data with the behavioral data, which can provide insight into the biological underpinnings of cognitive dysfunction in schizophrenia, and we can take a more dimensional approach to examining the biology of schizophrenia.

So as Rebecca alluded to earlier, instead of looking at schizophrenia as a group we can look at possibly participants with intact cognitive function versus those with impaired cognitive function. And there are efforts underway to explore the genetic basis of these different groups, and to better understand the biology.

And the last thing I would like to mention is that we now have the opportunity to compare and integrate the data that was collected in the SAX study with cognitive data from other genetic studies. So as part of the Ancestral Populations Network, which is funded by the NIMH, we’re now looking to take a transdiagnostic approach to studying the genetic basis of cognitive function across different phenotypes.

So we’re looking at cognitive function in schizophrenia, bipolar disorder, MDD, et cetera. And it’s going to be very interesting to see where that takes us. So the last thing left to do is to say thank you to the research team, the collaborators and steering committee, as well as the research participants. And I’ll now be handing over to Dr. Majara to continue the presentation. Thanks.

LERATO MAJARA : Good morning. I’m going to be talking about uncovering the genetic diversity and variation in the genomes of South African populations, a project called GNOMSA. And I should say up front that as far as the RDoC framework goes, my presentation will be focused on genetics as a unit of analysis. And some of the work that I’m going to be showing here hasn’t been published yet, and is part of a manuscript that is in preparation.

So by and large African populations have been excluded from genetic studies. And as is shown here in this figure on the left, showing the number of participants in GWAS studies by the millions on the Y axis, and over time on the X axis, and populations are color coded, and the African populations are coded in this purple color. And as you can see, up until recent years, the number of African populations and I guess other underrepresented populations is very slowly rising. So the purple here you can see is a very small sliver of the total number of participants.

Things are starting to change a little bit, with ongoing efforts such as studies that Olivia and Dan have spoken about being the SAX study, (inaudible) Child Health Study as well as NeuroGAP. I just wanted to emphasize the NeuroGAP study here. It is the largest study of its kind on the continent, having recruited over 32,000 individuals across Ethiopia, Uganda, Kenya, and South Africa. And in it several phenotypes have been assessed and environmental risk factors assessed as well. So the scale in terms of participant numbers and phenotypes provides an opportunity for the implementation of the RDoC framework in this study.

So these are my acknowledgments. I would like to acknowledge my lab mates, the Neurosciences Institute, the Gabriel Grants that has provided the funding for this project, and study participants in general. Thank you very much.

REBECCA BERMAN : Thank you. That was fantastic. Thank you all three of you for those really excellent presentations. And a reminder to the audience, if you have questions for these presenters, please put them in the Q&A function, and we hope to have time to address those at the end.

I want to turn now to quickly introduce our next set of speakers, Dr. Vikram Patel who is the Pershing Square Professor of Global Health at Harvard, where he chairs the Department of Global Health and Social Medicine. He leads the Mental Health for All Lab, which focuses on the social determinants of mental health problems and using community resources to prevent and treat them. He is a cofounder of Sangath, an award-winning Indian NGO which has pioneered approaches to mental health equity. And he is also a fellow of the United Kingdom’s Academy of Medical Sciences and a member of the US National Academy of Medicine.

And following his opening remarks here we’ll hear from Dr. Supriya Bhavnani, who is a coprincipal investigator in the child development group at Sangath India. She leads a translational neuroscience research program using a whole range of tools to assess development. And her research also investigates the determinants of development, with a focus on psychosocial adversities. She has been a recipient of the INSPIRE Faculty Award and Innovative Young Biotechnologist Award from the Government of India. We are so excited to have both of you with us. Go ahead, thank you.

VIKRAM PATEL : Thank you Rebecca. I’m just going to give some introductory remarks, and Supriya is going to do the presentation of our work. Let me just start by amplifying what the previous presentations have spoken about, which is the very important role of adversities in early childhood, and mental health across the life course.

The question is really how is this association mediated? And there is now very robust evidence that much of this effect is mediated through impaired early life brain development, particularly cognitive and social development. We have very good evidence from the Global South that not only are adversities in childhood related to poverty extremely common, but also that learning loss, which is a very important proxy for early life brain development, is very prevalent, particularly for example in South Asia, where the work that you hear about has been conducted.

In a recent review paper in Nature Medicine, led by Sophie Bhutan including Supriya and myself, we document the various pathways through which adversities in early childhood lead to poorer health and mental health in particular across the life course. And I think it really reflects a very good example of how these old divisions between social and biological can be dissolved when we think about these different pathways.

So how do we actually interrupt this pathway? Obviously, from a primary prevention perspective, we want to really make sure every child grows up in a nurturing environment. But that is of course something that we cannot guarantee. So while a large proportion of children grow up in adversity, we need to figure out when their development is faltering so we can intervene early.

The problem has been that we only identify a child who is having difficulties with their development when they wind up in school and start failing in school for one reason or the other, or when they develop mental or behavioral problems. Even then the actual assessment of these problems is extremely time consuming, it requires very expensive, often proprietary cognitive assessment tests, and requires highly skilled personnel to do this, which means the overwhelming majority of children who have faltering development or emerging disorders go unrecognized.

This is the background to the work you’re going to hear about now, which was really driven by the need to develop a dimensional assessment for early life cognitive development that was scalable and that could help us both in identifying children whose development was faltering so that we could institute early interventions, but also to identify phenotypic disorders that are associated with child development and mental health.

I’m now going to hand over to Supriya. And suffice to say the entire program has been led by Sangath(ph.) but has involved as she will describe to us, a collaboration between very many diverse disciplines working in institutions around the world. Supriya, over to you.

SUPRIYA BHAVNANI : Thanks, Vikram. The title of our presentation is Assessing Domains of Neurodevelopment in Early Childhood using Digital Tools. The design, delivery, and evaluation of the DEEP and START tools in India. And with the introduction that Vikram has given I should be able to go quite quickly through some of my first few slides.

So Vikram alluded to the importance of brain development and how it impacts lifelong health, and has also introduced to you the idea that a large number of the children, particularly in low- and middle-income countries, face adversities in their growing years, in the years which are crucial to determine how they will do as they grow older both in their education, through their professional life.

And oftentimes faltering in early development leads to the perpetuation of a vicious cycle of disadvantage, where children who grew up in disadvantage end up not being able to provide for their own children. This is a sort of self-perpetuating cycle. So the need to disrupt this cycle and really identify children whose development needs further support has led us to our research program, which I will tell you a bit more about.

So I will skip through this slide, it is really reiterating the same points that Vikram has made and I’ve just made. But just to say that we do acknowledge that a large number of these different processes in the body contribute to this impact of adversities on physical and mental health. And the one that we focus on is the developing brain.

So, Vikram alluded as well to this detection gap. So we know that there are a number of children that are faltering in their development, but we struggle to find these children in the population. And it’s important to say that one of the reasons that happens is because currently our assessment of child development depends on specialists that are administering typically proprietary tools that are very costly, and in settings such as ours in India, this is not a scalable model. These specialists are few and far between, and they’re also often located mostly in urban settings. And so the children that can benefit from early interventions are not identified on time, if at all.

So the guiding principles of the research program that we’ve been doing for the past few years really align with the RDoC framework in a few ways which I will illustrate now. So this is just an image that you’ve seen earlier from Becky’s presentation. And what I have tried to do here is circle in orange how this speaks to the work that we do.

So we focus on development across the lifespan, without limiting ourselves to the first thousand days of childhood. In fact, we don’t even limit ourselves to early childhood. An example of that is the fact that one of the cohorts that this work is based in has actually been with us since 2015, and we have been following up these children from birth up until now, when they’re eight years old, and we’re hoping to continue to go back to them as they become young adults.

So we really look at development across the lifespan, but not just development, but also the environment. So what is the psychosocial environment in the household that this child is growing up in. And we collect a rich adversity data particularly on the happenings of these households.

The tools that I will discuss with you specifically measure the sensory, motor, cognitive and social processes domains that the RDoC has laid out. And while I won’t get into too much detail of some of our other units of analysis, I would like to mention that the work that we do looks at molecular, at behavioral, at neurophysiological and parent report in the case of young children as units of analysis.

So maybe an example of that is that in this same cohort that I just mentioned, which is in a rural part of north India, we have data as diverse as the adversities experienced by these children, the levels of cortisol, which is a marker of stress physiology, and we have measures of development in these children which I will describe in a minute.

The second guiding principle is that of scalability. So given the detection gap that we want to close is largely due to the lack of available tools that have been normed, that have been shown to have evidence of scalability in these populations of the Global South, our aim was to develop tools that can be used by trained non-specialist workers, they don’t need to have training in child development or in mental health.

They are administered within households. So what you’re seeing here is an example of a tool which is being administered in a child’s house in a rural setting. Importantly we also harness digital technology. I think one of the questions had referred to the harnessing of digital technology. So that is one of the guiding principles for our work, because we really feel it is critical to move to scale. And they are also directly measuring child performance.

So we look at measuring children from two and a half to six years. Importantly this is before the age at which they enter school years. These tools can all be administered offline. They’re using low-cost Android devices. And they have no written instructions for the child. The assessor, the non-specialist worker is the one who is guiding the child on how to engage with these tools.

And for each tool the assessor gives the instructions to the child while demonstrating the tool to them. And once the child has understood what to do, we move ahead. So the data itself is getting recorded by the device. And that is an important point, because we don’t depend on the non-specialist judgment of the child’s performance, we let the data be captured by the device and then analyze it. And I’ll tell you a bit more about that as well.

Another guiding principle, it sort of alludes to some of the presentations we heard earlier, is that we need to move away from clinical categories and start to think about curves of development. This is particularly important in early childhood, where the disorders that we are currently leaving children with are heterogeneous, they’re comorbid.

And if we begin to think of development of cognitive, social processes, and sensory motor processes as a continuum, then we can start to imagine drawing curves for development that are quite analogous to growth monitoring, which is routinely done across the world.

I’ll tell you now a bit more about our tools and their components. As I mentioned, the target age range is two and a half to six-year-olds, and the two tools that I will be describing to you today are called the DEEP tool, which is the Developmental Assessment on an E Platform, and the START tool, which is Screening Tools for Autism Risk Using Technology.

These tools are comprised of different components. I would say the units of measurement in this case for us are parent-child interaction, eye tracking, and gamified neuropsychological tests. I will get into each of these a bit more when I describe each tool to you.

So I would first like to tell you a little bit about our process. So embarking on a journey of trying to make scalable assessments of child development in these very crucial and rather challenging years of two and a half to six was one that we took on with a variety of experts. And what I mean by that is from the beginning of this project, from the inception of this program we have had clinicians, neuroscientists, public health experts and computer scientists as well as game developers inform the products that we have made. So they’ve informed the DEEP tool and the START tool.

What we decided to do was to adapt methods that have been used in early child development in laboratory settings for decades, and that have actually got a very large and wide base of evidence for picking up these processes, and starting to think about how we can use those in the community.

So what we then did was we created some tool prototypes. We went into communities in India and did some formative work. We used child performance, we used parent feedback of the engagement of the child with our tools, and we used non-specialist worker feedback.

So the person who is actually administering the tool to iteratively inform the development of our tools. And once our tools were developed we went ahead and tested the acceptability, feasibility, and validity of our tools. And I won’t repeat, but really thinking about how these can be done eventually at scale. And today we’re at a place where we are keen to validate these tools in a diverse population.

So, about the DEEP tool. The DEEP tool comprises of 14 games. They are woven together into a narrative in which the index child, along with the moon, which is really popular amongst these little kids, is the protagonist of the story.

And we found that the DEEP tool is very engaging for children. In a population-based study, 98.7 percent of our children attempted all of the games, and it took them on average 25 minutes to complete these games. But that can vary depending on how a child plays, all the way from three minutes to 50 minutes. The reason for that is each of these games has different levels of difficulty.

So if a child is able to successfully complete one difficulty level, they go on to the next, and the next. And if they don’t, they go on to the next game. And we feel that these games are tapping into a range of cognitive constructs of the type that you heard described with the RDOC framework. All games of course require comprehension, they require attention, but some for example specifically target memory or reasoning.

The example that we’ve given here is something we call Grow Your Garden. In this, a child is instructed to touch the apple and not the owl. And what we are recording at the back end is the correct clicks, the incorrect clicks that the child makes, and also the background clicks. And through these variables we are able to for example compute how many levels a child played across our tools, what their accuracy was, what their latency was, which was how long did they take to make their first click.

And for example, how long they took to complete a game level. And you can hopefully see how nuanced the data from a cognitive assessment like this is, as opposed to some of the more traditional assessments, which mark kids really with just a one or a zero for having completed an item.

The method that we chose to evaluate this tool has been to benchmark it against a gold standard called the BSID, which is a clinical assessment for children under three and a half years. And we used a machine learning approach. So you can imagine we get a lot of metrics from our tools, and we really went agnostic to these metrics, and just wanted to see which metrics can best predict cognition, as measured by the DALYs(?).

And with this we had moderate coordination between the DEEP score and the BSID score, and something we alluded to earlier, which is children with more adversities, which you can see in the bottom graph here, actually had a lower DEEP score than children who had a lower amount of adversities in the first year of their life.

But we are acutely aware that we don’t want to limit our analyses to gold standards. They come with their own set of limitations, particularly that of scalability, which we are trying to overcome. So the approach we’re using now is to really see how the data, how the metrics themselves can be used to derive a score, and how those correlate with age.

So this is not yet published, but we are really hopeful, because we can start to see a trajectory coming up here from children between two and a half to six. So you can see as children are growing older their score on this cognitive tool is increasing.

I’ll move now to the START tool. The START tool again comprises gamified assessments. We are looking at a very innovative way of tracking how a child’s visual response to cues is. So this is traditionally done in lab settings with very expensive equipment, using eye trackers.

But what we do is we use the camera of the tablet to take a video of the child while they are looking at our stimuli, and we are then able to use computer vision to see where the child was looking. It’s one of our big examples of innovation of taking lab-based science into households. I’ll talk a bit more about that on the next slide.

So some of the other tasks we have, I won’t go through all of these in the interest of time, but for example you can see pop the bubble, which is really looking at a child simply popping bubbles, but the data is recording the force with which they interacted with the tablet.

And there is published evidence to show that children with autism actually press harder on these tablets than those who are typically developing. And in the preferential looking task, it’s known that children with autism for example tend to look more at non-social images and videos than typically developing children.

So the design that we used to validate the study was a case control design. We had children with autism, intellectual disability, and typically developing children. And really what I would like to focus here on is the images you see on the left, which are showing you the challenges that are overcome to be able to do for example eye tracking in households. You can see the different types of settings in which we’ve had to use it. We’ve had to use a table, a bed, even just a step in a house, depending on the space that was available to us.

And what you’re seeing on the right is that our tools have had pretty high completion rates. The graphs where you don’t have 100 percent in TD are typically where the app has malfunctioned. But the ones in which you are seeing real reductions of completion are the children that have developmental challenges.

And I’m not going to go through this in great detail, but I would just like to say that we have found group differences in the cases of these tasks, in the metrics that we’ve derived from them. This paper is published, so anyone that is interested can go in and see more.

But it’s important to highlight here and bring this back to the RDoC framework, that while we were able to get group differences between typically developing children and children with developmental disorders, we were actually not, each task did not differentiate between ASD and ID. So really also one of the reasons was that we found a lot of comorbidity in this population. So really reminding us that these diagnostic categories that we have focused a lot of our work on might need to be rethought.

And that is what we are doing through the study that these tools are being used on today. So we have integrated these tools in a study called the STREAM study, which is Scalable Transdiagnostic Assessment of Mental Health. It’s an MRC funded project for five years. And the aim of this study is really to generate normative data.

And I think Olivia alluded as well to the lack of normative data, particularly from underrepresented countries such as ours, on domains of cognition, social, and fine motor development. We’re doing this currently through two diverse low resource settings, which is in India and Malawi.

And we also aim to provide evidence of their clinical utility. And importantly we are collecting the environmental determinants of child development, and we are looking at how these tools are sensitive to the impact of these risk factors. So this is a study being done on 4000 children, all the way from zero to six years of age.

Just in conclusion I wanted to just mention the innovations that we’ve made through this research program. We’ve used decades of knowledge from psychology, from neuroscience, and we’ve used child performance-based assessments of these domains and not recorder observations, which is typically done in this age range.

Our delivery is particularly innovative. We’ve used non-specialist workers, we work offline, we go to routine settings like households, and we use tablet computers, particularly Android, which is low cost. And the validity has used two approaches. One is in a population based level as well as against clinical diagnoses.

Finally, where we want to go with this program of work is to continue to validate these tools. I think particular importance is thinking about how these tools are able to predict performance in later childhood. So when children enter school, do assessments in this age range predict a child that might be faltering in school later?

We also have a vision to go to scale. An important part of that is to get collaborations and get global data. We have had some successful collaborations with a team in Nepal, with Malawi. We’ve also had interest in using our tools in the UK. And we of course need to go through the health system to achieve scale in our countries.

But we also envisioned this as tools that can potentially be implemented directly through parents. So really empowering them to measure development in their own children. And finally, we would like to impact outcomes. And one of the ways we would do that would be to link child performance on our tools to targeted interventions.

So this is just an image of what I’ve just described to you, which is a vision for these tools. And finally I would like to acknowledge as Vikram said this is an effort by a very large group of collaborators, and I would like to acknowledge them. I would like to acknowledge our funders. And of course to all of our participating families. Thank you.

LEONARDO CUBILLOS : Thank you very much for these wonderful presentations, one from South Africa, the other from India. Becky, do you want to come back on camera?

REBECCA BERMAN : Sure. And I think at this point we can invite all our speakers to come on camera. Thank you all again. Incredible, inspiring presentations.

LEONARDO CUBILLOS: So we have a few questions that are in the Q&A box. Do you see them, Becky? We may not have enough time to cover all of them. Are there any that you want to prioritize? By the way, I would also like to invite the RDoC team to also join on camera.

REBECCA BERMAN : Certainly. One I think we might want to cover, maybe not exactly this question, but the idea it gets to, a question from Dr. Yared Alemu(ph.) on how some of the researchers are overcoming the lack of digital health technology in low resourced countries. I think really Supriya in your talk you gave some great examples of where it sounds like you’re finding methods to make this very scalable and accessible, and working really in a setting that empowers, as you said has the potential to empower parents directly, and families.

But I would love to hear I think from the speakers thoughts on the potential for these technologies. It’s something that I think has broad interest, but also different considerations, whether it’s around things like what the patient privacy concerns might be, or other issues just in bringing these to scale. I would love to hear from any speakers who would like to address that.

VIKRAM PATEL : I think I will go first. I think privacy is a universal concern with all personal data. So I think that is kind of a given. I feel that that has to be seen as a background topic that has to be a starting point for any conversation on digital data. But I don’t think we should let that question interrupt our efforts to actually use digital data. I think as Supriya has described, the work we have been doing in India is entirely designed to be used offline.

And so the idea behind the internet, access to the internet being a barrier, I think is addressed by engineering, so you actually have as much of the data stored on a device until you are able to connect with the internet, and then let the data be uploaded.

That being said, my last remark is that the level of internet coverage and access to smartphones, at least in South Asia, has absolutely catapulted in the last five years. And in large part that has to do with the fact that all financial services have moved onto the internet.

So almost 80 percent now of all cash transactions in India happen on your phone. This is a monumental shift over the last five years, but what it has therefore meant is that data access has now become almost universal. I won’t say it's fully universal, but nearing universality. And I think that trend will continue very rapidly in the coming years. So it’s a real opportunity for actually using technology enabled methods for the research that we do.

REBECCA BERMAN : Thank you. That is a really important set of points and lessons there. Another question, I think we’ll open this up for any of the speakers, are there ways, this comes from Michael Goodman, are there any ways you imagine the RDoC framework being deployed differently in the global setting versus US-based settings?

DAN STEIN : I guess I can go first there. I think Rebecca you alluded to this in your talk when you were sort of saying RDoC doesn’t have to rely necessarily on brain imaging. But I think there is, obviously in highly resourced places you can rely on those sorts of things, and that is one wonderful opportunity. In low resourced settings we necessarily have to use less expensive methodologies and measures.

And you alluded to that for example in the ADHD study, and the Indian team have demonstrated that that is entirely possible. I think also sort of exciting is the development of for example portable MRI scans, which might allow you to do brain imaging in low resourced settings at relatively inexpensive rates. I see that Supriya is actually a coauthor on an article about the ethics of these kinds of devices.

So once again there are pros and minuses of these kinds of things, and certainly the issue of the scientific value at a population level needs then to be determined. But again maybe creating a whole range of new scientific opportunities. And of course I think always with applicability to the global north as well, rural areas and so forth and so on.

VIKRAM PATEL : Let me just add to what Dan just said, which I completely agree with, is also the use of portable EEG. Although we didn’t describe that, but I think in terms of a very underutilized tool, in large part because of the complexity of assessment of reading EEGs, and a challenge which is now being addressed through automated methods to actually read EEGs.

And of course, the huge technology leap of portable EEG. We have been using portable EEG with thousands of very young children, which you do at their home, and you do it while they’re doing the DEEP game, so you can get them distracted as it were so they don’t tear the leads off. But that’s another really huge potential.

I wanted to also just say one brief remark about the US versus the low-income world. Because most people – this is going to be a provocative and speculative statement. Because most people in low income countries don’t ever get a chance to be diagnosed, because diagnostic, algorithmic skills are actually very rarely accessible in most parts of the world, in fact you might find that this more dimensional approach of characterizing human mental health might have far more likelihood of being taken up, because there is not a huge existing infrastructural edifice of diagnosis driven care that dominates the US landscape. I think paradoxically some of these ideas are more likely to be embraced in the Global South than they are in the Global North. But that is my speculation.

LEONARDO CUBILLOS : I just want to rescue one question that Lina Matsumoto(ph.) asked earlier, that Supriya answered in writing. Lina Masumoto asks where can the participants learn more from the work that you guys are doing in India and South Africa. Supriya, you wrote in the chat box the website to Sungath.in. I’m asking Dan or your team if there is any resource that also participants can go to to learn more of what you are doing.

REBECCA BERMAN : I think we have another question about what type of studies are valued more. Is that something, Sarah, that you can speak to?

SARAH MORRIS: Sure, I can weigh in on that. And then perhaps Leo has some thoughts about that specifically from the global mental health perspective. I would say the short answer is reach out to an NIMH program officer, we can always help you determine whether your research idea or grant application is in alignment with NIMH research priorities. And those research priorities are available on the NIMH website. It’s always good to keep an eye on the funding opportunities that NIMH publishes to get a sense of what ideas and topics are considered high priority. The NIMH Director’s Blog is also a good source of some insights into what NIMH is thinking about. Leo, I don’t know if you want to weigh in on that all.

LEONARDO CUBILLOS : Just two additional points. One is we in the global mental health space are looking for studies that are significant to the context where they are done, not only in the way of addressing access gaps or diagnostics gaps, which was presented by some of our presenters earlier, but that also address and take into account the capacity of those local settings to bring those potential innovations to scale. There are of course many other things we would be happy to meet with potential applicants on.

REBECCA BERMAN : I would just add that this idea of bringing things to scale echoes back to the earlier question about US-based versus more global settings. And I think there is really strong interest in that scalability component, recognizing that there are, as Dan alluded to as well, plenty of places within the US where resources are limited. And so really finding ways to reach more of the population where they’re at, whether that’s using cellphones and some of these digital technologies, or other, more accessible methods, is of great interest within the RDoC framework too.

LEONARDO CUBILLOS : I think we are now at the hour. Thank you Becky and colleagues, from the RDoC team. Dan, Olivia, and Majara, thank you so much for sharing that vital knowledge coming from South Africa and other countries we know are doing a great job. Vikram and Supriya, thank you for presenting what you are doing in India.

Thank you everyone who joined around the world, wherever you are. Have a wonderful rest of the morning, afternoon, or evening. Again, this concludes the 2023 Center for Global Mental Health Research Webinar Series. We will be preparing and launching the 2024 series over the coming months. Have a wonderful rest of your day.

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150 Best Neuroscience Research Topics and Ideas for Students
121 Neuroscience Research Topics (Fresh for 2023)
Neuroscience Research Topics : 100+ Cool Ideas
143 Neuroscience Research Topics For Fantastic Results
150 Best Neuroscience Research Topics and Ideas for Students
120 Neuroscience Research Topics: Explore the World

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Neuroscience Research Topics & Ideas (Includes Free Webinar)
Neuroscience-Related Research Topics. Investigating the neural mechanisms underlying memory consolidation during sleep. The role of neuroplasticity in recovery from traumatic brain injury. Analyzing the impact of chronic stress on hippocampal function. The neural correlates of anxiety disorders: A functional MRI study.
121 Neuroscience Research Topics (Fresh for 2023)
This means you need to choose one of our current topics in neuroscience: Cerebellar Neurons that can help you lose weight. Effects of a meat-based diet. Latest brain mapping technology. CT scans in 2023. Brain implants that can control a computer. An in-depth look at super-agers.
Top 100 in Neuroscience
Top 100 in Neuroscience. This collection highlights our most downloaded* neuroscience papers published in 2021. Featuring authors from around the world, these papers showcase valuable research ...
Neuroscience
Atom. RSS Feed. Neuroscience is a multidisciplinary science that is concerned with the study of the structure and function of the nervous system. It encompasses the evolution, development ...
Research articles
A vagal-brainstem interoceptive circuit for cough-like defensive behaviors in mice. Gannot et al. show that Tac1 neurons in the NTS mediate an airway-vagal-brain pathway that is crucial for ...
Frontiers in Neuroscience
Neural Dynamics for Brain-inspired Control and Computing: Advances and Applications. Mei Liu. Zhongbo Sun. Predrag S. Stanimirović. 495 views. Part of the most cited neuroscience journal series which explores the brain - from the new eras of causation and anatomical neurosciences to neuroeconomics and neuroenergetics.
Neuroscience News Science Magazine
Neuroscience News is an independent open access science magazine. Since 2001, we have featured neuroscience research news from labs, universities, hospitals and news departments around the world. Topics include brain research, AI, psychology, neuroscience, mental health and neurotech.
Neuro Topics
Neuro Topics. Harvard researchers are deeply committed to understanding nervous system development and function, in both healthy and disease states. Basic scientists and clinician-researchers work together across departments, programs and centers to study the nervous system from diverse perspectives, as shown in the overlapping subfields below.
Frontiers in Neuroscience
See all (1,858) Advancements and applications of light sheet fluorescence microscopy in neuroscience: innovations, quantitative analysis, and future directions. Accounting for the relative energy efficiency of biological and artificial intelligence. Advancements in Translational Stroke Research: Spotlight on the Blood-Brain Barrier.
Neuroscience News
A new study suggests that the risk of developing dementia in Parkinson's disease patients may be lower or occur later than previously reported. Researchers analyzed data from two large studies, finding a 9% risk of dementia within 10 years for newly diagnosed patients and a 27% risk for those diagnosed for an average of six years.
Featured News
Overthinking Happiness Can Lower Life Satisfaction. Obsessing over personal happiness can actually decrease life satisfaction, according to new research. In three studies involving over 1,800 participants, individuals who judged their own happiness reported lower well-being, increased negativity, and more disappointment in positive events.
150+ Astonishing Neuroscience Research Topics For Students
Cognitive Neuroscience Research Topics. 71. Neural correlates of language processing and comprehension. 72. The role of attention in perceptual processing. 73. Memory consolidation during sleep and wakefulness. 74. Brain mechanisms of decision-making and risk-taking behavior.
Frontiers in Human Neuroscience
Rajat Emanuel Singh. Catherine Purcell. Jennifer Davies. 226 views. The third most-cited journal in the field of psychology, that bridges research in psychology and neuroscience to advance our understanding of the human brain in both healthy and diseased states.
Top 171+ Neuroscience Research Topics For Students [2024]
Neuroscience research topics offer students insight into the complexities of the brain and nervous system, fostering a deeper understanding of how these intricate systems shape behavior, cognition, and emotions. Improving Healthcare. By studying neuroscience, students gain valuable knowledge about the underlying mechanisms of mental health ...
Neuro Research Guide
Research Topic. Students often feel that the research topic is the decisive factor. For example, you may have a topic that you are already passionate about (e.g., Alzheimer's Disease, Traumatic Brain Injury, or Free Will). While this pre-existing interest can be a great motivator, consider the following: over three semesters and one summer ...
Top 100 in Neuroscience
This collection highlights our most downloaded* neuroscience papers published in 2022. Featuring authors from around the world, these papers showcase valuable research from an international community.
55 Trending Neuroscience Dissertation Topics- ResearchProspect
On a broad scale, the topic covers numerous behavioural, computational, cellular, evolutionary, functional, molecular, and therapeutic facets of the nervous system. Many students have trouble coming up with fascinating neuroscience research project topics. Choosing a topic for the dissertationis a crucial step in the dissertation writing process.
Growing Brains, Nurturing Minds—Neuroscience as an Educational Tool to
Nevertheless, neuroscience research indicates that meaning-making and cognitive performance benefit from the interplay between extrinsic and intrinsic oriented attention and processing [56,75]. ... Among the topics and burning issues of teens and young adults that neuroscience can offer insights into are selective and leaky attention , ...
Artificial Intelligence News
The research found that AI assistance boosts novelty and usefulness, making stories more enjoyable and less boring. However, it also warns that widespread use of AI may reduce the diversity and uniqueness of creative works. The findings highlight both the potential and risks of using AI in creative writing. Read More.
Study shows new, more precise way to deliver medicine to the brain
A "Behind the Paper" blog on the study -- by Houston Methodist research scientist and co-author Jesus G. Cruz-Garza -- explains how ECED can infuse macromolecules into the brain from a hydrogel ...
Undergraduate Research in Neuroscience
Apply directly to a neuroscience faculty lab. This is the most common way that students find a research position in a neuroscience lab. Here are tips on how to proceed: Check out the Neuroscience Department faculty page, or the broader Helen Wills Neuroscience Institute faculty page, to determine which labs you are interested in. Before ...
Top 100 in Neuroscience
Top 100 in Neuroscience. This collection highlights our most downloaded* neuroscience papers published in 2020. Featuring authors from around the world, these papers showcase valuable research ...
Innovative 3D gold microelectrode arrays enhance understanding of
Understanding the dynamics of neuronal communication is crucial for advancing neuroscience research and developing effective therapies for neurological disorders. Topics. Week's top; Latest news ...
Frontiers
Articles in this Research Topic. Modern neuroimaging techniques provide crucial insights into myelin dynamics in the human brain, both under normal and pathological conditions (Laule et al., 2007).The review by Kujawa et al. presents new magnetic resonance imaging (MRI) techniques and biophysical models to map myelin in vivo, highlighting the potential of physical exercise to influence ...
Most Popular News
Hyper Brain, Hyper Body: The Trouble With High IQ. A study suggests that people with high IQs face a greater risk of psychological and physiological disorders compared to the general population. Drawing from a survey of 3,715 Mensa members with IQs above 130, the researchers found notably higher rates of mood disorders, ADHD, and autoimmune ...
The Center for Global Mental Health Research Webinar Series 2023 ...
This webinar discussed the National Institute of Mental Health's Research Domain Criteria (RDoC) initiative and its potential to inform (and be informed by) global mental health research. RDoC is a research framework that encourages the investigation of mental disorders from a perspective of basic functional dimensions (e.g., cognitive control), using many types of information - from ...
Cognitive neuroscience
Cognitive neuroscience is the field of study focusing on the neural substrates of mental processes. It is at the intersection of psychology and neuroscience, but also overlaps with physiological ...
Michelle Monje, MD, PhD
The Milan Gambhir Professor in Pediatric Neuro-Oncology has been awarded 11th annual Ross Prize in Molecular Medicine from the Feinstein Institutes for Medical Research. The prize, which includes a $50,000 award, is in recognition of Monje's contributions to research relating to the neuroscience of cancer and its implications for therapy.
Neurology News
A new study finds that 40Hz light and sound therapy helps maintain myelin, a crucial brain structure, in Alzheimer's patients. This therapy, which protects neurons and supports brain function, could offer new treatment avenues for neurodegenerative diseases. Researchers discovered that this stimulation enhances neural connections and reduces ...
Writing, Imitation, and Performance Insights from Neuroscience Research
This book reconsiders imitation as a valuable pedagogical approach in Writing Studies. Countering concerns about product-oriented teaching, formulaic writing, paternalistic or elitist pedagogy, and plagiarism, the book maintains that the use of imitation can offer a writer greater insight and help to develop a clear writerly identity. Positing that writers often use imitation as a step toward ...

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150+ Astonishing Neuroscience Research Topics For Students In 2023

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Brain Development and Plasticity

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Neurobiology of Mental Disorders

Neuropharmacology and Drug Development

Neuroimaging Techniques

Neurogenetics and Epigenetics

Neuroethics and Neurolaw

Neurobiology of Learning and Memory

Neuroimmunology

Computational Neuroscience

Neuroengineering and Brain-Computer Interfaces

Neurobiology of Sleep and Circadian Rhythms

Neurobiology of Sensory Systems

Neurobiology of Motivation and Reward

Neurobiology of Aging and Neurodegeneration

How to Choose a Neuroscience Research Topic?

Resources for Students Interested in Neuroscience

Wrapping Up

1. What are some career options in neuroscience research?

2. What are some current challenges and future directions in neuroscience research?

3. What are some emerging trends or areas of interest in neuroscience research?

4. What are some reputable journals and databases for neuroscience research?

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