Memory And Sleep: A Computational Understanding - Hardcover

Chen, Zhe Sage

Hardcover

ISBN 10: 9819829046 ISBN 13: 9789819829040

Publisher: WSPC, 2026

Synopsis

The book provides a general introduction to memory and sleep, focusing on computational understanding of the concepts. It includes both fundamental and advanced topics about the process of learning in biological and computational systems, neurotechnology, NeuroAI, and neuroethics.

It systematically covers major categories of memory; neural substrates of memory; brainwaves and their relationship to memory; the role of sleep in memory; dreaming; and memory consolidation.

It includes important historical accounts and anecdotes of scientific discoveries. It has fifty-eight illustrations, and hundreds of notes and references.

It bridges the gap between memory and computation. It provides novel computational perspectives of brain disorders and mental illnesses. It includes discussions on many computational models such as the attractor network, predictive coding, Bayesian inference, and reinforcement learning. It provides documented clinical observations and patient stories of memory-related diseases (such as amnesia).

It discusses stem cells, organoids, memory manipulation, closed-loop neural interfaces, cutting-edge AI, neurotechnology, and their roles in future memory research.

About this title

About the Author

Zhe Sage Chen is a Professor at the New York University Grossman School of Medicine, with joint appointment at the Departments of Psychiatry and Neuroscience, and Department of Biomedical Engineering at the NYU Tandon School of Engineering. He is the Director of Computational Psychiatry Program at NYU, and the Director of Computational Neuroscience, Neuroengineering and Neuropsychiatry Laboratory. His research interests include computational neuroscience, computational psychiatry, neural engineering, neural signal processing, machine learning, and Bayesian statistics, in which he has published more than 150 peer-reviewed articles. He is the lead author of the book Correlative Learning (Wiley, 2007) and the editor of two books: Advanced State Space Methods for Neural and Clinical Data (Cambridge University Press, 2015) and Dynamic Neuroscience (Springer, 2018). Professor Chen is a Senior Member of the IEEE and currently serves as the Associate Editor for the Journal of Neural Engineering, IEEE Transactions on Neural Systems and Rehabilitation Engineering, and Frontiers in Computational Neuroscience. Previously, he was with the Editorial Board for the Neural Networks. Professor Chen has received several awards (e.g., Mathematical Bioscience Institute Early Career Award, Oracle for Research Award, IEEE Walter Karplus Summer Research Award, etc) and is the lead principal investigator for multiple research grants funded by the US National Science Foundation (NSF), National Institutes of Health (NIH), and the BRAIN Initiatives. His article has won the 2012 Brain Corporation Prize in Computational Neuroscience (3rd place).

Edition details

• Publisher: WSPC
• Publication date: 2026
• Language: English
• ISBN 10: 9819829046
• ISBN 13: 9789819829040
• Binding: Hardcover
• Number of pages: 356