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Elkhonon Goldberg's groundbreaking The Executive Brain was a classic of scientific writing, revealing how the frontal lobes command the most human parts of the mind. Now he offers a completely new book, providing fresh, iconoclastic ideas about the relationship between the brain and the mind. In The New Executive Brain, Goldberg paints a sweeping panorama of cutting-edge thinking in cognitive neuroscience and neuropsychology, one that ranges far beyond the frontal lobes. Drawing on the latest discoveries, and developing complex scientific ideas and relating them to real life through many fascinating case studies and anecdotes, the author explores how the brain engages in complex decision-mak...
This textbook is an introduction to Systems and Theoretical/Computational Neuroscience, with a particular emphasis on cognition. It consists of three parts: Part I covers fundamental concepts and mathematical models in computational neuroscience, along with cutting-edge topics. Part II explores the building blocks of cognition, including working memory (how the brain maintains and manipulates information "online" without external input), decision making (how choices are made among multiple options under conditions of uncertainty and risk) and behavioral flexibility (how we direct attention and control actions). Part III is dedicated to frontier research, covering models of large-scale multi-...
The papers appearing in this proceedings volume cover a broad range of subjects, owing to the highly cross-disciplinary character of the workshop, and include: experiments and models concerning the dynamics of the neural activity in the cortex (DMS experiments, attractor dynamics in the cortex, spontaneous activity…); hippocampus, space and memory; theoretical advances in neural network modeling; information processing in neural networks; applications of neural networks to experimental physics, particularly to high energy physics; digital and analog hardware implementations of neural networks; etc.
An exciting, new framework for interpreting the philosophical significance of neuroscience. All science needs to simplify, but when the object of research is something as complicated as the brain, this challenge can stretch the limits of scientific possibility. In fact, in The Brain Abstracted, an avowedly “opinionated” history of neuroscience, M. Chirimuuta argues that, due to the brain’s complexity, neuroscientific theories have only captured partial truths—and “neurophilosophy” is unlikely to be achieved. Looking at the theory and practice of neuroscience, both past and present, Chirimuuta shows how the science has been shaped by the problem of brain complexity and the need, i...
The Oxford Handbook of Human Memory provides an authoritative overview of the science of human memory, its application to clinical disorders, and its broader implications for learning and memory in real-world contexts. Organized into two volumes and eleven sections, the Handbook integrates behavioral, neural, and computational evidence with current theories of how we learn and remember. Overall, The Oxford Handbook of Human Memory documents the current state of knowledge in the field and provides a roadmap for the next generation of memory scientists, established peers, and practitioners.
Based upon the most advanced human-made technology on this planet, CMOS integrated circuit technology, this dissertation examines the design of hardware components and systems to establish a technological foundation for the application of future breakthroughs in the intersection of AI and neuroscience. Humans have long imagined machines, robots, and computers that learn and display intelligence akin to animals and themselves. To advance the development of these machines, specialised research in custom-built hardware designed for specific types of computation, which mirrors the structure of powerful biological nervous systems, is especially important. This dissertation is driven by the quest ...
This book constitutes the refereed proceedings of the Second International Symposium on Brain, Vision and Artificial Intelligence, BVAI 2007. Coverage includes: basic models in visual sciences, cortical mechanism of vision, color processing in natural vision, action oriented vision, visual recognition and attentive modulation, biometric recognition, image segmentation and recognition, disparity calculation and noise analysis, meaning-interaction-emotion, and robot navigation.
Neurons in the brain communicate by short electrical pulses, the so-called action potentials or spikes. How can we understand the process of spike generation? How can we understand information transmission by neurons? What happens if thousands of neurons are coupled together in a seemingly random network? How does the network connectivity determine the activity patterns? And, vice versa, how does the spike activity influence the connectivity pattern? These questions are addressed in this 2002 introduction to spiking neurons aimed at those taking courses in computational neuroscience, theoretical biology, biophysics, or neural networks. The approach will suit students of physics, mathematics, or computer science; it will also be useful for biologists who are interested in mathematical modelling. The text is enhanced by many worked examples and illustrations. There are no mathematical prerequisites beyond what the audience would meet as undergraduates: more advanced techniques are introduced in an elementary, concrete fashion when needed.
A classical view of neural computation is that it can be characterized in terms of convergence to attractor states or sequential transitions among states in a noisy background. After over three decades, is this still a valid model of how brain dynamics implements cognition? This book provides a comprehensive collection of recent theoretical and experimental contributions addressing the question of stable versus transient neural population dynamics from complementary angles. These studies showcase recent efforts for designing a framework that encompasses the multiple facets of metastability in neural responses, one of the most exciting topics currently in systems and computational neuroscience.
A comprehensive, integrated, and accessible textbook presenting core neuroscientific topics from a computational perspective, tracing a path from cells and circuits to behavior and cognition. This textbook presents a wide range of subjects in neuroscience from a computational perspective. It offers a comprehensive, integrated introduction to core topics, using computational tools to trace a path from neurons and circuits to behavior and cognition. Moreover, the chapters show how computational neuroscience—methods for modeling the causal interactions underlying neural systems—complements empirical research in advancing the understanding of brain and behavior. The chapters—all by leaders...