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Computational Neuroscience and Cognitive Modelling
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Computational Neuroscience and Cognitive Modelling
A Student's Introduction to Methods and Procedures


March 2014 | 240 pages | SAGE Publications Ltd

"For the neuroscientist or psychologist who cringes at the sight of mathematical formulae and whose eyes glaze over at terms like differential equations, linear algebra, vectors, matrices, Bayes’ rule, and Boolean logic, this book just might be the therapy needed."

- Anjan Chatterjee, Professor of Neurology, University of Pennsylvania


"Anderson provides a gentle introduction to computational aspects of psychological science, managing to respect the reader’s intelligence while also being completely unintimidating. Using carefully-selected computational demonstrations, he guides students through a wide array of important approaches and tools, with little in the way of prerequisites...I recommend it with enthusiasm."
- Asohan Amarasingham, The City University of New York


This unique, self-contained and accessible textbook provides an introduction to computational modelling neuroscience accessible to readers with little or no background in computing or mathematics. Organized into thematic sections, the book spans from modelling integrate and firing neurons to playing the game Rock, Paper, Scissors in ACT-R. This non-technical guide shows how basic knowledge and modern computers can be combined for interesting simulations, progressing from early exercises utilizing spreadsheets, to simple programs in Python. Key Features include:
  • Interleaved chapters that show how traditional computing constructs are simply disguised versions of the spread sheet methods.
  • Mathematical facts and notation needed to understand the modelling methods are presented at their most basic and are interleaved with biographical and historical notes for contex.
  • Numerous worked examples to demonstrate the themes and procedures of cognitive modelling.

 An excellent text for postgraduate students taking courses in research methods, computational neuroscience, computational modelling, cognitive science and neuroscience. It will be especially valuable to psychology students.

 
Chapter 1: Introduction
 
PART 1: Modeling Neurons
 
Chapter 2: What is a Differential Equation?
 
Chapter 3: Numerical Application of a Differential Equation
 
Chapter 4: Intermezzo: Computing With Loops
 
Chapter 5: Integrate & Fire
 
Chapter 6: Intermezzo: Computing With If Statements
 
Chapter 7: Hodgkin & Huxley: The Men and Their Model
 
Chapter 8: Intermezzo: Computing With Functions
 
PART 2: Neural Networks
 
Chapter 9: Neural Network Mathematics: Vectors and Matrices
 
Chapter 10: Intermezzo: Interactive Computing
 
Chapter 11: An Introduction to Neural Networks
 
Chapter 12: Intermezzo: Interactive Exploration of the Delta Rule with Octave
 
Chapter 13: Auto-associative Memory and the Hopfield Net
 
PART 3: Probability and Psychological Models
 
Chapter 14: What are the Odds?
 
Chapter 15: Decisions as Random Walks
 
Chapter 16: Intermezzo: Programming Psychophysical Experiments with Python
 
PART 4: Cognitive Modeling as Logic and Rules
 
Chapter 17: Boolean Logic
 
Chapter 18: Intermezzo: Computing With Functional Languages
 
Chapter 19: Production Rules and Cognition
 
Chapter 20: Intermezzo: Functional Coding of a Simple Production System
 
Chapter 21 ACT-R: A Cognitive Architecture
 
Chapter 22: Agent Based Modeling
 
Chapter 23: Concluding Remarks

For the neuroscientist or psychologist who cringes at the sight of mathematical formulae and whose eyes glaze over at terms like differential equations, linear algebra, vectors, matrices, Bayes’ rule, and Boolean logic, this book just might be the therapy needed. Britt Anderson guides the reader into the world of computational methods; writing lucidly and grounding this journey with elegantly constructed exercises. His slender book is an invitation to use tools that will help students and scientists think about neural and psychological mechanisms with rigor and precision.

Anjan Chatterjee
Professor of Neurology, University of Pennsylvania

 

The neural and cognitive sciences are increasingly quantitative and computational subjects, and curriculums are now attempting to reflect this emerging reality. Accordingly, an important educational challenge is to inform undergraduate students of the significance of computational thinking, while also preparing them to appreciate and criticize it. An Invitation to Computational Neuroscience and Cognitive Modeling achieves this difficult goal wonderfully. Anderson provides a gentle introduction to computational aspects of psychological science, managing to respect the reader’s intelligence while also being completely unintimidating. Using carefully-selected computational demonstrations, he guides students through a wide array of important approaches and tools, with little in the way of prerequisites. As well as a very practical introduction to computer programming, there is impressive coverage of dynamical systems models of neurons, neural network models of memory, probabilistic models of decision-making, and mathematical models of thought. I recommend it with enthusiasm.

Asohan Amarasingham
The City University of New York

Really good one for introduction. I recommended it especially to first-term master's students.

Mr Adam Schweda
Psychology, Heinrich-Heine-University Dusseldorf
April 29, 2016

The authors try to cover a variety of different topics ranging from theoretical neuroscience, to applied computational neuroscience and cognitive modeling.
In the end, this broad approach may provide as a very rough overview, but doesn't leave the reader with much knowledge that is really applicable.
Also, I don't really see the use of Python as a plus; the language is less intuitive to understand than MATLAB, and (although many people don't like to hear it) far away from becoming a standard in our field (which MATLAB still is).

Professor Rene Huster
Psychology Dept, University of Oslo
November 30, 2015

This text would be recommended for M-Level students as a step by step guide to computational neuroscience.

Anderson shares his journey towards developing an understanding in this area which will be of great support to students who are keen to learn more about computation modelling methods and procedures.

Mr Jonathan Reid
School of Education, Oxford Brookes University
March 4, 2015

For instructors

This book is not available as a review copy. For more information contact your local sales representative.

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ISBN: 9781446249307
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