The Emerging Intersection between Control Theory and Neuroscience
by Steven J. Schiff
ISBN: 9780262546713
Publisher: The MIT Press
Pub Date: November 1, 2022
How powerful new methods in nonlinear control engineering can be applied to neuroscience, from fundamental model formulation to advanced medical applications.
A textbook for students with limited background in mathematics and computer coding, emphasizing computer tutorials that guide readers in producing models of neural behavior.
Explains the relationship of electrophysiology, nonlinear dynamics, and the computational properties of neurons, with each concept presented in terms of both neuroscience and mathematics and illustrated using geometrical intuition.
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.
An argument that the complexities of brain function can be understood hierarchically, in terms of different levels of abstraction, as silicon computing is.
Edited by Kenji Doya, Shin Ishii, Alexandre Pouget and Rajesh P.N. Rao
ISBN: 9780262516013
Publisher: The MIT Press
Pub Date: January 21, 2011
Experimental and theoretical neuroscientists use Bayesian approaches to analyze the brain mechanisms of perception, decision-making, and motor control.
A mathematical framework that describes learning of invariant representations in the ventral stream, offering both theoretical development and applications.
Computational and Mathematical Modeling of Neural Systems
by Laurence F. Abbott and Peter Dayan
ISBN: 9780262041997
Publisher: The MIT Press
Pub Date: October 26, 2001
Theoretical neuroscience provides a quantitative basis for describing what nervous systems do, determining how they function, and uncovering the general principles by which they operate. This text...
Computation, Representation, and Dynamics in Neurobiological Systems
by Chris Eliasmith and Charles H. Anderson
ISBN: 9780262550604
Publisher: The MIT Press
Pub Date: August 20, 2004
For years, researchers have used the theoretical tools of engineering to understand neural systems, but much of this work has been conducted in relative isolation. In Neural Engineering, Chris...
