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Theoretical Neuroscience
Theoretical neuroscience provides a quantitative basis for describing what nervous systems do, determining how they function, and uncovering the general principles by which they …
Methods in Neuronal Modeling
Much research focuses on the question of how information is processed in nervous systems, from the level of individual ionic channels to large-scale neuronal networks, and from …
Biological Learning and Control
A novel theoretical framework that describes a possible rationale for the regularity in how we move, how we learn, and how our brain predicts events.In Biological Learning and …
Biophysics of Computation
Neural network research often builds on the fiction that neurons are simple linear threshold units, completely neglecting the highly dynamic and complex nature of synapses, …
Sensory Cue Integration
This book provides an introduction into both computational models and experimental paradigms that are concerned with sensory cue integration both within and between sensory …
The Computational Neurobiology of Reaching and Pointing
An introduction to the computational biology of reaching and pointing, with an emphasis on motor learning.Neuroscience involves the study of the nervous system, and its topics …
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 …
23 Problems in Systems Neuroscience
The complexity of the brain and the protean nature of behavior remain the most elusive area of science, but also the most important. van Hemmen and Sejnowski invited 23 experts …
Fast Oscillations in Cortical Circuits
The study of cortical oscillations is of great interest to those working in many areas of neuroscience. A fast coherent EEG rhythm called gamma or "40 Hz" has been implicated in …
Unsupervised Learning
Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most …
Visual Cortex and Deep Networks
A mathematical framework that describes learning of invariant representations in the ventral stream, offering both theoretical development and applications.The ventral visual …
Case Studies in Neural Data Analysis
A practical guide to neural data analysis techniques that presents sample datasets and hands-on methods for analyzing the data.As neural data becomes increasingly complex, …