Theoretical Neuroscience Course Part I 2005
The course has now finished, but you can find the lecture slides, homework assignments and references to articles and books on this site. General course information including a syllabus etc is here. Also
have a look at the Gatsby teaching
schedule for other courses taught by Gatsby people. This page will
mainly contain the weekly assignments and some additional reading. The
course is open to anybody from the University of London. If you'd like
to attend, please send us an email. |
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The teaching schedule is as follows.
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| Lectures | every Tuesday and Friday, 11 am - 1 pm, from 4-10 to 16-12
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| Review Sessions | every Friday, 9:30 am - 10:55 am
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| Venue | Gatsby Unit room 409, 4th floor
Alexandra House, 17 Queen Square
London WC1N 3AR |
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The teaching assistant is Misha Ahrens. If you have any
questions or things you'd specifically like to cover in the review sessions, please email him.
The main course book is
Theoretical Neuroscience by Dayan and Abbott. The appendix
of the book describes the maths needed for the course. If you need to brush up on mathematics, one recommended book is Riley,
Hobson and Bence: Mathematical Methods for Physicists. For a very simple intro to first order ODE's, see Hugh Wilson: spikes,
decisions and actions, chapters 1 and 2. A few very useful cribsheets are
basic maths you'll need for this course, and some matrix identities.
Some other useful resources on the web, including other theoretical neuroscience course sites are here. You might also be interested in the Gatsby neuroscience journal club.
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Below is a schedule of the review sessions (updated before every review session). The homework assignments can be downloaded from here. The section "reading" lists background reading material and is (usually) not meant as compulsory.
| Date | | Reading | Assignment |
| 12-10 | review session 1
biophysics
Hodgkin & Huxley etc |
Dayan and Abbott, chapter 5
Hodgkin & Huxley, '52 (the pioneering paper on channel modeling)
lecture slides |
homework 1 |
| 19-10 | review session 2
biophysics
cable equation, synapses |
Dayan and Abbott, chapter 6
for the keen: Koch (1999) ch. 2-5
Cox and Gabbiani's course site |
homework 2
hwk2data.mat |
| 26-10 | review session 3
systems neuroscience
receptive fields
spike statistics |
vision: Dayan and Abbott, chapter 2
Kandell, chapters 25-31
Zigmond, chapters 21, 22, 27, 28
spike statistics: Dayan and Abbott, chapter 1
R. Hahnloser's notes
Maneesh's lecture on neural coding
Maneesh's lecture on spike statistics |
homework 3 |
| 4-11 | review session 4
information theory
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Dayan and Abbott, chapter 4
Maneesh's notes on information theory (provisional)
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homework 4 |
| 11-11 | review session 5
neural encoding and decoding |
Jonathan's lecture on neural encoding
Dayan and Abbott, chapters 3-4
a review paper of LN models (Simoncelli et al)
and one on point processes in neuroscience (Brown et al) |
homework 5 |
| 18-11 | review session 6
population coding, Fisher information
reinforcement learning |
Dayan and Abbot, chapters 3-4, chapter 9
reinforcement learning lecture slides |
homework 6 |
| 25-11 | review session 7
plasticity and learning |
Dayan and Abbott, chapter 8
lecture slides
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homework 7 |
| 2-12 | review session 8
network dynamics |
Dayan and Abbott, chapter 7
Wilson and Cowan, 1972 and 1973 |
homework 8 |
| 16-12 | review session 9
network dynamics and dynamics of differential equations |
Dayan and Abbott, chapter 7
Boyce and DiPrima, Elementary differential Equations and Boundary Value Problems
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homework 9 |
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Page maintained by Misha Ahrens |