Read e-book online Computational Neuroscience and Cognitive Modelling: A PDF

By Britt Anderson

ISBN-10: 1446249301

ISBN-13: 9781446249307

This specific, self-contained and available textbook presents an creation to computational modelling neuroscience available to readers with very little history in computing or arithmetic. equipped into thematic sections, the e-book spans from modelling combine and firing neurons to enjoying the sport Rock, Paper, Scissors in ACT-R. This non-technical consultant exhibits how uncomplicated wisdom and smooth desktops might be mixed for attention-grabbing simulations, progressing from early workouts using spreadsheets, to easy courses in Python.

 

Key positive factors include:

 

- Interleaved chapters that convey how conventional computing constructs are easily disguised models of the spreadsheet methods

- Mathematical proof and notation had to comprehend the modelling tools are offered at their most simple and are interleaved with biographical and ancient notes for context

- quite a few labored examples to illustrate the subjects and systems of cognitive modelling.

 

An very good textual content for upper-level undergraduate and postgraduate scholars taking classes in learn equipment, computational neuroscience / computational modelling, and cognitive technology / neuroscience. it will likely be particularly invaluable to psychology students.

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Read or Download Computational Neuroscience and Cognitive Modelling: A Student's Introduction to Methods and Procedures PDF

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Additional info for Computational Neuroscience and Cognitive Modelling: A Student's Introduction to Methods and Procedures

Sample text

26 Chapter 3 Recall the physical situation we are modelling. We have pulled on a weight attached to a spring and stretched the spring. At some point we release the weight, and the spring slides back and forth. We would like to know where our weight will be (which is equivalent to knowing the length of our spring) at any point in time we should choose. We would like an equation for s( t). Then, we can plug in any value for t that we choose, and we will get back a number for location. We begin with the known equation a( t) = −Ps( t).

Confer with a friend or an instructor if you get stuck, and have some patience and persistence. Exercise: New Value = Old Value + Change in Value × Time 1. Create the following column headings in the spreadsheet program of your choice: P, t, delta t, s, a, v, delta v, delta s 2. Pick some small positive number for P and enter it in the spreadsheet under the “P”; you might want to try 1. Remember: we want to start simple. Later we can explore how our model changes for different values of P. 3. 05, and put that under “delta t”.

1) dt In addition to the formula above, the integrate and fire model includes another assumption that is an essential feature of the model: the reset. Unlike the Hodgkin and Huxley model, the integrate and fire equation will not automatically generate an action potential. For the integrate and fire model we fix a threshold. Whenever our voltage exceeds this threshold we assert that an action potential has happened, and we reset the voltage to the baseline. “Our life is frittered away by detail. ” Henry David Thoreau τ Exploring the Equation We cannot model what we do not understand.

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Computational Neuroscience and Cognitive Modelling: A Student's Introduction to Methods and Procedures by Britt Anderson


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