# What are some books for Computational Neuroscience

## Computational Neuroscience

2013 | book

### A first course

### about this book

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 network level. The book, which grew out of a lecture series held regularly for more than ten years to graduate students in neuroscience with backgrounds in biology, psychology and medicine, takes its readers on a journey through three fundamental domains of computational neuroscience: membrane biophysics, systems theory and artificial neural networks. The required mathematical concepts are kept as intuitive and simple as possible throughout the book, making it fully accessible to readers who are less familiar with mathematics. Overall, Computational Neuroscience - A First Course represents an essential reference guide for all neuroscientists who use computational methods in their daily work, as well as for any theoretical scientist approaching the field of computational neuroscience.

### Table of Contents

### Frontmatter

### Excitable Membranes and Neural Conduction

### Receptive Fields and the Specificity of Neuronal Firing

### Fourier Analysis for Neuroscientists

- Sinusoidal inputs to linear, translation-invariant systems yield sinusoidal outputs, differing from the input only in amplitude and phase but not in frequency or overall shape. Sinusoidals are therefore said to be the “eigen-functions” of linear shift invariant systems. Responses to sinusoidal inputs or combinations thereof are thus reduced to simple multiplications and phase shifts. This is the mathematical reason for the prominent role of sinusoidals in scientific computing.
- The second idea of this chapter is that any continuous function (and also some non-continuous functions) can be represented as linear combinations of sine and cosine functions of various frequencies. Alternatively to the use of sine and cosine functions, one may also use sinusoidals with a phase value for each frequency, or complex exponentials from the theory of complex numbers.

### Artificial Neural Networks

### Coding and Representation

### Backmatter

- title
- Computational Neuroscience
- publishing company
- Springer International Publishing
- Print ISBN
- 978-3-319-00860-8
- Electronic ISBN
- 978-3-319-00861-5
- DOI
- https://doi.org/10.1007/978-3-319-00861-5
- Author:
- Hanspeter A Mallot

### premium partner

- New technologies create new problems
- Most mutual fund managers are criminal thieves
- Has China ever closed its border?
- Which animal lives the most pathetic life
- Is alibaba com reliable
- How do I change the language of Google Chromes
- How did you beat the corporate world
- How many multiples of 6 are possible
- Is cloning a cell phone illegal?
- Does a lower blood pressure sharpen a person's memory
- How to make cashew butter
- What is a data protection officer DPO
- Is the mold remediation insured
- AP credit is required for the SAT
- Can a desire be called ethical
- Review of research in robotics
- What does CRM stand for in construction?
- To whom is India's national anthem dedicated
- Are chemical peels safe
- What is a high voltage object
- Is Pakistan pro Burma Myanmar
- Catheter ablation is considered an operation
- What is the comfort of civilization
- What is 1 1 1 1 15