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How We Remember
Episodic memory proves essential for daily function, allowing us to remember where we parked the car, what time we walked the dog, or what a friend said earlier. In this book, Hasselmo presents a new model describing the brain mechanisms for encoding and remembering an episode as a spatiotemporal trajectory.
Advances in Neural Information Processing Systems 8
The past decade has seen greatly increased interaction between theoretical work in neuroscience, cognitive science and information processing, and experimental work requiring sophisticated computational modeling. The 152 contributions in NIPS 8 focus on a wide variety of algorithms and architectures for both supervised and unsupervised learning. They are divided into nine parts: Cognitive Science, Neuroscience, Theory, Algorithms and Architectures, Implementations, Speech and Signal Processing, Vision, Applications, and Control. Chapters describe how neuroscientists and cognitive scientists use computational models of neural systems to test hypotheses and generate predictions to guide their ...
How We Remember
A novel perspective on the biological mechanisms of episodic memory, focusing on the encoding and retrieval of spatiotemporal trajectories. Episodic memory proves essential for daily function, allowing us to remember where we parked the car, what time we walked the dog, or what a friend said earlier. In How We Remember, Michael Hasselmo draws on recent developments in neuroscience to present a new model describing the brain mechanisms for encoding and remembering such events as spatiotemporal trajectories. He reviews physiological breakthroughs on the regions implicated in episodic memory, including the discovery of grid cells, the cellular mechanisms of persistent spiking and resonant frequ...
The Neurobiology of Computation
This volume includes papers presented at the Third Annual Computation and Neural Systems meeting (CNS*94) held in Monterey California, July 21 - July 26, 1994. This collection includes 71 of the more than 100 papers presented at this year's meeting. Acceptance for meeting presentation was based on the peer review of preliminary papers by at least two referees. The papers in this volume were submitted in final form after the meeting. As represented by this volume, CNS meetings continue to expand in quality, size and breadth of focus as increasing numbers of neuroscientists are taking a computational approach to understanding nervous system function. The CNS meetings are intended to showcase t...
From Neuron to Cognition via 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...
Space,Time and Memory in the Hippocampal Formation
The discovery of new cell types, such as grid and time cells, in the hippocampus has been accompanied by major anatomical and theoretical insights in the recent years. This book provides comprehensive, up-to-date information about the hippocampal formation and especially the neural basis of episodic memory, spatial location (the formation of the cognitive map) and temporal representation. The first part of the book describes the information flow from pre-hippocampal areas into the hippocampus, the second part discusses the different types of hippocampal processing and finally, the third part depicts the influence that the hippocampal processing has on other brain structures that are perhaps more closely tied to explicit cognitive or behavioral output. This book is intended for neuroscientists, especially for those who are involved in research on the hippocampus, as well as for behavioral scientists and neurologists.
Computational Neuroscience
This volume includes papers presented at the Fifth Annual Computational Neurosci ence meeting (CNS*96) held in Boston, Massachusetts, July 14 - 17, 1996. This collection includes 148 of the 234 papers presented at the meeting. Acceptance for mceting presenta tion was based on the peer review of preliminary papers originally submitted in May of 1996. The papers in this volume represent final versions of this work submitted in January of 1997. As represented by this volume, computational neuroscience continues to expand in quality, size and breadth of focus as increasing numbers of neuroscientists are taking a computational approach to understanding nervous system function. Defining computa tional neuroscience as the exploration of how brains compute, it is clear that there is al most no subject or area of modern neuroscience research that is not appropriate for computational studies. The CNS meetings as well as this volume reflect this scope and di versity.
Neural Networks and Psychopathology
Research on connectionist models is one of the most exciting areas in cognitive science, and neural network models of psychopathology have immediate theoretical and empirical appeal. The contributors to this study review theoretical, historical and clinical issues, including the contribution of neural network models to diagnosis, pharmacotherapy and psychotherapy. Models are presented for a range of disorders, including schizophrenia, obsessive-compulsive disorder, dissociative phenomena, autism and Alzheimer's disease. This book will appeal to a broad audience. On the one hand, it will be read with interest by psychiatrists, psychologists and other clinicians and researchers in psychopathology. On the other, it will appeal to those working in cognitive science and artificial intelligence, and particularly those interested in neural network or connectionist models.
The Neural Circuit for Spatial Representation
How do we find our way? The discovery of medial entorhinal cortex grid cells in 2005 stimulated a wide variety of experimental, theoretical and computational work aimed at elucidating the neural circuit underlying spatial representations in the entorhinal cortex. However, grid cells act in concert with place cells, head direction cells and border cells, each playing a part in the spatial navigation circuit. The aim of this Research Topics is to solicit contributions from leading researchers in the field of spatial navigation and spatial memory to present new experimental data, computational modeling or discussion on mechanisms underlying the neural encoding of space in the parahippocampal cortices.
A Computational Model of Grid Cells based on a Recursive Growing Neural Gas
The entorhinal cortex of rat contains neurons, called "grid cells", that exhibit a very peculiar behavior. Discovered about a decade ago, the activity of these cells was found to correlate with the allocentric position of the animal by forming a regular, hexagonal lattice of firing fields across the entire environment. Due to this unusual behavior and the proximity of the entorhinal cortex to other brain regions that also contain cells with spatially correlated activity grid cells are commonly recognized as an important element of a neuronal system for navigation. Existing computational models of grid cells share this view and typically describe the behavior of grid cells as a path integrati...
