Computational Neuroscience Series

Computational neuroscience is an approach to understanding the development and function of nervous systems at many different structural scales, including the biophysical, the circuit, and the systems levels. Methods include theoretical analysis and modeling of neurons, networks, and brain systems and are complementary to empirical techniques in neuroscience. Areas and topics of particular interest to this book series include computational mechanisms in neurons, analysis of signal processing in neural circuits, representation of sensory information, systems models of sensorimotor integration, computational approaches to biological motor control, and models of learning and memory. Further topics of interest include the intersection of computational neuroscience with engineering, from representation and dynamics, to observation and control.Editors: Terrence J. Sejnowski (Salk Institute) and Tomaso Poggio (MIT)

Series editor: Terrence J. Sejnowski and Tomaso Poggio

Neural Control Engineering

Steven J. Schiff

Nov 01, 2022

From Neuron to Cognition via Computational Neuroscience

Michael A. Arbib, James J. Bonaiuto

Nov 11, 2016

The Computational Brain

Patricia S. Churchland, Terrence J. Sejnowski

Nov 04, 2016

Case Studies in Neural Data Analysis

Mark A. Kramer, Uri T. Eden

Nov 04, 2016

Visual Cortex and Deep Networks

Tomaso A. Poggio, Fabio Anselmi

Sep 23, 2016

Principles of Brain Dynamics

Mikhail I. Rabinovich, Karl J. Friston, Pablo Varona

Jul 06, 2012

Biological Learning and Control

Reza Shadmehr, Sandro Mussa-Ivaldi

Jan 27, 2012

Visual Population Codes

Nikolaus Kriegeskorte, Gabriel Kreiman

Oct 28, 2011