Neuroinformatics  FAQ:

A rather personal view of neuroinformatics.
by Mark van Rossum

Q: What is neuro-informatics?

Being a rather new field, the answer depends on who you ask.
The Edinburgh DTC has defined three core areas:
- Neural computation: Computing paradigms inspired on the brain, and figuring out the computations in the brain.
 I classify myself in this area.
- Neural engineering: Building neuroscience inspired hardware and making neuron-silicon interfaces.
- Software systems: Developing software to share data, simulator tools, and visualisation tools.

Q: I want to switch from physics/maths to neuroinfomatics. What do I need?

First, you might feel more secure  knowing that many people before you have made this switch.

Clear scientific thinking is the most important skill. Next, I think, are quantitative skills.
Typical tools I use for my work are: statistical physics, non-linear dynamics and simulations.

Programming is an important secondary skill. However, it is important to point out that excellent programming
by itself does not make good science. Progamming languages that are used a lot in this field are: Python, C, C++, and Matlab.

Q: I already have a PhD. Should I first obtain a PhD in neuroinformatics before I can work in this field, or can I go for a postdoc position straight away?

Not necessarly. A large part of the skills you learned during your PhD (writing papers, scientific thinking, independent work) will be also useful when you switch fields. However, there is a danger that you will not get exposed to enough neuroscience. You should consider this when looking for postdoc positions. You  need to be extra pro-active to study neuroscience and to integrate into your new field.

Q: Do I have to do experiments?

No. Some researchers working in neuroinformatics never see a lab.
Others are captivated by studying the nervous system directly and turn into full-time experimentalists.

Q: What attracts you in Neural Computation?

The nature of my personal fascination with neuroscience is not very different than my fascination with physics.  Physics tries to figure out the rules governing the physical world and tries to describe the world in mathematical terms. This seems a crazy idea, but the weird thing is, of course, that it works. The realization that all that we see is made out of atoms, that everything obeys the same laws, is awsome.

In neuroscience one tries to understand how the brain works, and therefore what the basis is for our thinking.  And, crazy as this idea might seem,  in some cases we start to understand it. We know roughly how the sensory systems and the motor systems work, especially for the lower animals. The realization that all our thinking is done by those things called neurons is equally astounding as relativity theory.

What makes neural computation particularly fun is that many questions remain still open and can be researched.
The field also moves very fast, so that a newcomer in the field has an advantage.

Q: What else should I do to decide on an area of interest?

Talk to people in the field.

Conferences are a very good source of information, not only for experts. Students in our programme are encouraged to visit conferences and summer schools.

Read a few books. A first year student can easily asks question to which nobody knows the answer. What is even
better, the student can try to learn the necessary techniques and explore the issue for themselves after a couple of months.

Q: How is Edinburgh as a city?

Edinburgh is beautiful medieval city with a lot of character.
Partly due to the large university it is very lively as well.
You might be surprised that it is actually not very cold in the winter.
Also the rainfall is not severe, less than Rome!
(The caveats are that it does not get hot in the summer, and that the rain is horizontal...)

Living expenses: Expect to pay some 400 BP/month for a one bedroom appartment for two.
Many students share flats reducing expenses.

Q: I would like to read more on neuroscience. What are good books?

There are many popular science books about the brain. Although not always 100% accurate, they can be an interesting read and help you to familiarize with the subject.

When you study at the DTC, we will send you an introductory neuroscience book:
- "Neuroscience: Exploring the Brain" by Mark F. Bear, Barry W.
  Connors, Michael A.  Paradiso. ISBN: 0781739446

The next books are more extensive, but might be a bit overwhelming.

- "Principles of Neural Science" by Eric R. Kandel (Editor), James
  H. Schwartz (Editor), Thomas M. Jessell. McGraw-Hill/Appleton &
  Lange; ISBN: 0838577016; 4th edition (January 5, 2000)

- "Fundamental Neuroscience" by Michael J. Zigmond (Editor), Floyd
  E. Bloom (Editor), Story C. Landis (Editor), Larry R. Squire
  (Editor). Academic Press; ISBN: 0127808701; 1st edition (January 15,
- "Neurobiology" by Gordon M. Shepherd, Oxford University Press; ISBN:
  0195088433; 3rd edition (June 1997)

- "From Neuron to Brain" by John G. Nicholls, Bruce G. Wallace, Paul
  A. Fuchs, A. Robert. Martin Sinauer Assoc; ISBN: 0878934391; 4th
  edition (January 15, 2001)

Computational modelling of neural systems:

- " Fundamentals of computational neuroscience"
Trappenberg, T. P. (2002). Oxford. Good, easiliy readable introduction.

- "The Computational Brain" by Patricia S. Churchland, Terrence
  J. Sejnowski. MIT Press; ISBN:
0262531208; Reprint edition (February 3, 1994)
- "Theoretical Neuroscience : Computational and Mathematical Modeling
  of Neural Systems" by Peter Dayan, L. F. Abbott. MIT Press; ISBN:
  0262041995; 1st edition (December 1, 2001) [Physics/math inclined]

- "Computational Explorations in Cognitive Neuroscience :
  Understanding the Mind by Simulating the Brain" by Randall
  C. O'Reilly, Yuko Munakata. MIT Press; ISBN:
  0262650541; 1st edition (September 4, 2000)

- "Methods in Neuronal Modeling - 2nd Edition : From Ions to Networks"
  by Christof Koch (Editor), Idan Segev (Editor). MIT Press; ISBN:
  0262112310; 2nd edition (June 4, 1998)

- "Biophysics of Computation: Information Processing in Single
  Neurons" by Christof Koch, Oxford University Press; ISBN:
  0195104919; (November 1998)

- "Introduction to the theory of neural computation"
Hertz, J., Krogh, A., and Palmer, R. G. (1991). Perseus, Reading, MA.
Technical, but very thorough book

Journal articles can be found via