Artificial Intelligence in Neuroscience
eBook - ePub

Artificial Intelligence in Neuroscience

  1. 347 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Artificial Intelligence in Neuroscience

About this book

Provides comprehensive guidance on harnessing artificial intelligence for neuroscience research and clinical applications

The rapid development of artificial intelligence (AI) has created new opportunities for advancing the study of the brain. While recent scholarship has focused on how neuroscience can inform the design of AI systems, there is a growing need for resources that demonstrate how AI can be applied to support neuroscience research and practice. Artificial Intelligence in Neuroscience offers a detailed introduction to AI technologies and their transformative potential for fields ranging from neuroimaging and genetics to mental healthcare and neuro-oncology.

Structured around four major areas, the book begins by exploring the shared history of AI and neuroscience, from single-neuron modeling and action potentials to contemporary learning mechanisms. It then examines how AI can be used as a data analysis tool in genetics, proteomics, histology, cognition, and population health, before turning to clinical applications such as biologically plausible cognitive models, connectionist frameworks, and reinforcement learning. Additional chapters consider emerging applications, including robotics, drug screening, brain-computer interfaces, and language models. The volume concludes with a critical discussion of ethical and privacy issues, ensuring readers are equipped to navigate the responsibilities that accompany technological innovation.

Wide in scope and filled with practical insights, Artificial Intelligence in Neuroscience:

  • Explores the historical intersections between AI and neuroscience to contextualize current innovations
  • Demonstrates applications of AI in neuroimaging, genetics, and population health research
  • Details clinical applications of AI models, including reinforcement learning and connectionist frameworks
  • Highlights novel uses of AI in robotics, brain-computer interfaces, and drug discovery
  • Integrates technical depth with applied case studies for both academic and clinical contexts

Artificial Intelligence in Neuroscience is ideal for graduate students, early career researchers, and established professionals in neuroscience, psychology, computer science, and medicine. It is well-suited for courses in computational neuroscience, AI in healthcare, and neuroinformatics within advanced degree programs in neuroscience, biomedical sciences, data science, and clinical psychology.

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Information

Publisher
Wiley
Year
2026
Print ISBN
9781394278855
Edition
1
eBook ISBN
9781394278862

Table of contents

  1. Cover
  2. Table of Contents
  3. Title Page
  4. Copyright
  5. List of Contributors
  6. About the Editor
  7. Chapter 1: Introduction
  8. Chapter 2: Deep Neural Networks in Brain Networks Study
  9. Chapter 3: Cerebrovascular Disease and Cognitive Function
  10. Chapter 4: Multilayer Networks in Neuroimaging
  11. Chapter 5: Artificial Intelligence–inspired Subtype Analysis for Brain Imaging
  12. Chapter 6: Computer-aided Diagnosis Systems in Neuroscience Based on Responsible Artificial Intelligence
  13. Chapter 7: Artificial Intelligence in Neurodegenerative Disorders
  14. Chapter 8: Applications of Machine Learning in the Genetics of Brain Disorders
  15. Chapter 9: Multiscale AI for Precision Neuro-oncology
  16. Chapter 10: Using AI to Detect Alzheimer’s Disease from Speech: The Ethical Questions
  17. Chapter 11: Privacy-preserving AI Methods to Protect Patient Privacy
  18. Index
  19. End User License Agreement

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Yes, you can access Artificial Intelligence in Neuroscience by Li Su in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Neuroscience. We have over one million books available in our catalogue for you to explore.