<p>It's a rapidly developing field, so that some areas are incredibly well represented in the books to the point of being standard - like the neuronal dynamics (e.g. by Paninski, Naud, Kistner, Gerstner or e.g. by Izhikevich), some less, like neural coding (e.g. by Doia, Ishii, Pouget, Rao) and vision (e.g. by Rolls, Deco), some almost aren't, like motor control(?) or neuroanatomy(?), and some has yet to generate sufficient volume of theoretical work explaining  experimental data (before it can start condensating in textbooks), like. Maybe try </p>

<p>Trappenberg - Fundamentals of Computational Neuroscience 2ed</p>

<p>It's pedagogically sound, yet not exhaustive nor particularly long to get through. This will help to have an initial overview of some topics, and build some taste for further reading interest (as the book really tries hard to give you a primer on a variety of topics and methods, and gives references). It has some code examples that you may rewrite in you favorite language. In addition, you may benefit from free browsing of Scholarpedia for reviews written by active researchers, and form your own idea of what "Computational Neuroscience" is.</p>

CC BY-SA 4.0
2018-10-14T10:28:28.033Z
I really appreciate the feedback. With regards to, specifically, computational neuroscience, do you know what maths might be a prerequisite before attempting to get through the book you've suggested?
A. Sheikh
CC BY-SA 4.0
2018-10-14T13:21:57.657Z
Most basic facts from linear algebra, calculus, probability, differential equations, numerical integration of differential equations and information theory, all of this with the focus on applied calculation (computational science, electrical engineering, statistical physics flavor). A couple of models are more than that, but you'll know it when you see it.
compephys
CC BY-SA 4.0
2018-10-14T01:44:59.513Z
2018-10-14T01:44:59.513Z
compephys
<p>I have just finished reading 'Neuroscience: Exploring the Brain' 3rd Edition, Bear et al. I am also planning on pursuing a neuroscience degree beginning fall 2019 and was wondering what other reading material I could use in preparation for such a degree. More specifically, I'm interested in computational neuroscience. What series of books is recommended to read for someone in my situation?</p>

CC BY-SA 4.0
2018-10-14T15:07:37.460Z
Do you know if you're more interested in simulations of simple neurons+large networks or detailed neurons+smaller circuits?
Justas
CC BY-SA 4.0
2018-10-16T08:40:25.830Z
I would say at the moment I am more interested in simple neurons + large networks. Although, I am not educated in the subject matter nearly enough to really understand all the differences between the two simulations you've mentioned.
A. Sheikh
CC BY-SA 4.0
2018-10-16T21:49:31.980Z
For simpler spiking neuron models, take a look at Gerstner's online book: https://lcn.epfl.ch/~gerstner/SPNM/SPNM.html Then for even simpler rate-based/connectionist models take a look at O'Reilly's online book: https://grey.colorado.edu/CompCogNeuro/index.php/CCNBook/Main
Justas
CC BY-SA 4.0
2018-10-17T08:38:26.500Z
@Justas - feel free to turn this into an answer; looks OK to me.
AliceD
CC BY-SA 4.0
2018-10-18T02:23:10.473Z
I really like [Spikes](https://mitpress.mit.edu/books/spikes)
StrongBad
<neuroscience><reference-request>
Reading material for graduate neuroscience program
A. Sheikh
# Reading material for graduate neuroscience program

(Asked by: username_0 on 2018-10-10)

I have just finished reading 'Neuroscience: Exploring the Brain' 3rd Edition, Bear et al. I am also planning on pursuing a neuroscience degree beginning fall 2019 and was wondering what other reading material I could use in preparation for such a degree. More specifically, I'm interested in computational neuroscience. What series of books is recommended to read for someone in my situation?

**Tags:** neuroscience, reference-request

> **Comments:**
> **username_1**: Do you know if you're more interested in simulations of simple neurons+large networks or detailed neurons+smaller circuits?  
> **username_0**: I would say at the moment I am more interested in simple neurons + large networks. Although, I am not educated in the subject matter nearly enough to really understand all the differences between the two simulations you've mentioned.  
> **username_1**: For simpler spiking neuron models, take a look at Gerstner's online book: https://lcn.epfl.ch/~gerstner/SPNM/SPNM.html Then for even simpler rate-based/connectionist models take a look at O'Reilly's online book: https://grey.colorado.edu/CompCogNeuro/index.php/CCNBook/Main  
> **username_2**: @username_1 - feel free to turn this into an answer; looks OK to me.  
> **username_3**: I really like [Spikes](https://mitpress.mit.edu/books/spikes)  

---

## 1 answers

### Answer by username_4 on 2018-10-14. Score: 1 | Accepted answer

It's a rapidly developing field, so that some areas are incredibly well represented in the books to the point of being standard - like the neuronal dynamics (e.g. by Paninski, Naud, Kistner, Gerstner or e.g. by Izhikevich), some less, like neural coding (e.g. by Doia, Ishii, Pouget, Rao) and vision (e.g. by Rolls, Deco), some almost aren't, like motor control(?) or neuroanatomy(?), and some has yet to generate sufficient volume of theoretical work explaining experimental data (before it can start condensating in textbooks), like. Maybe try

Trappenberg - Fundamentals of Computational Neuroscience 2ed

It's pedagogically sound, yet not exhaustive nor particularly long to get through. This will help to have an initial overview of some topics, and build some taste for further reading interest (as the book really tries hard to give you a primer on a variety of topics and methods, and gives references). It has some code examples that you may rewrite in you favorite language. In addition, you may benefit from free browsing of Scholarpedia for reviews written by active researchers, and form your own idea of what "Computational Neuroscience" is.

> **Comments:**
> **username_0**: I really appreciate the feedback. With regards to, specifically, computational neuroscience, do you know what maths might be a prerequisite before attempting to get through the book you've suggested?  
> **username_4**: Most basic facts from linear algebra, calculus, probability, differential equations, numerical integration of differential equations and information theory, all of this with the focus on applied calculation (computational science, electrical engineering, statistical physics flavor). A couple of models are more than that, but you'll know it when you see it.  

---

