An Introductory Course in Computational Neuroscience Book [PDF] Download

Download the fantastic book titled An Introductory Course in Computational Neuroscience written by Paul Miller, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "An Introductory Course in Computational Neuroscience", which was released on 02 October 2018. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Science genre.

Summary of An Introductory Course in Computational Neuroscience by Paul Miller PDF

A textbook for students with limited background in mathematics and computer coding, emphasizing computer tutorials that guide readers in producing models of neural behavior. This introductory text teaches students to understand, simulate, and analyze the complex behaviors of individual neurons and brain circuits. It is built around computer tutorials that guide students in producing models of neural behavior, with the associated Matlab code freely available online. From these models students learn how individual neurons function and how, when connected, neurons cooperate in a circuit. The book demonstrates through simulated models how oscillations, multistability, post-stimulus rebounds, and chaos can arise within either single neurons or circuits, and it explores their roles in the brain. The book first presents essential background in neuroscience, physics, mathematics, and Matlab, with explanations illustrated by many example problems. Subsequent chapters cover the neuron and spike production; single spike trains and the underlying cognitive processes; conductance-based models; the simulation of synaptic connections; firing-rate models of large-scale circuit operation; dynamical systems and their components; synaptic plasticity; and techniques for analysis of neuron population datasets, including principal components analysis, hidden Markov modeling, and Bayesian decoding. Accessible to undergraduates in life sciences with limited background in mathematics and computer coding, the book can be used in a “flipped” or “inverted” teaching approach, with class time devoted to hands-on work on the computer tutorials. It can also be a resource for graduate students in the life sciences who wish to gain computing skills and a deeper knowledge of neural function and neural circuits.


Detail About An Introductory Course in Computational Neuroscience PDF

  • Author : Paul Miller
  • Publisher : MIT Press
  • Genre : Science
  • Total Pages : 405 pages
  • ISBN : 0262038250
  • PDF File Size : 45,7 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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An Introductory Course in Computational Neuroscience

An Introductory Course in Computational Neuroscience
  • Publisher : MIT Press
  • File Size : 48,5 Mb
  • Release Date : 02 October 2018
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A textbook for students with limited background in mathematics and computer coding, emphasizing computer tutorials that guide readers in producing models of neural behavior. This introductory text teaches students to

Computational Neuroscience

Computational Neuroscience
  • Publisher : Springer Science & Business Media
  • File Size : 29,8 Mb
  • Release Date : 23 May 2013
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Computational Neuroscience - A First Course provides an essential introduction to computational neuroscience and equips readers with a fundamental understanding of modeling the nervous system at the membrane, cellular, and

Fundamentals of Computational Neuroscience

Fundamentals of Computational Neuroscience
  • Publisher : Oxford University Press
  • File Size : 25,5 Mb
  • Release Date : 20 May 2024
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The new edition of Fundamentals of Computational Neuroscience build on the success and strengths of the first edition. Completely redesigned and revised, it introduces the theoretical foundations of neuroscience with

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From Neuron to Cognition via Computational Neuroscience
  • Publisher : MIT Press
  • File Size : 27,9 Mb
  • Release Date : 04 November 2016
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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

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Biophysics of Computation
  • Publisher : Oxford University Press
  • File Size : 46,6 Mb
  • Release Date : 28 October 2004
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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, dendrites, and voltage-dependent ionic currents.

Neuronal Dynamics

Neuronal Dynamics
  • Publisher : Cambridge University Press
  • File Size : 22,6 Mb
  • Release Date : 24 July 2014
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This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.

Dynamical Systems in Neuroscience

Dynamical Systems in Neuroscience
  • Publisher : MIT Press
  • File Size : 26,7 Mb
  • Release Date : 22 January 2010
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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. In

MATLAB for Neuroscientists

MATLAB for Neuroscientists
  • Publisher : Academic Press
  • File Size : 22,9 Mb
  • Release Date : 09 January 2014
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MATLAB for Neuroscientists serves as the only complete study manual and teaching resource for MATLAB, the globally accepted standard for scientific computing, in the neurosciences and psychology. This unique introduction

Neural Control Engineering

Neural Control Engineering
  • Publisher : MIT Press
  • File Size : 55,9 Mb
  • Release Date : 01 November 2022
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How powerful new methods in nonlinear control engineering can be applied to neuroscience, from fundamental model formulation to advanced medical applications. Over the past sixty years, powerful methods of model-based