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| 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 contact Mary Hardie. |
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| Lecturers | | Topic
(see course info for more details) |
| Peter Latham | Biophysics, single neurones, networks |
| Maneesh Sahani
and Liam Paninski | Neural coding, Information theory |
| Peter Dayan | Learning |
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| Teaching Assistant | Quentin Huys |
| Any questions or things you'd
specifially like to cover in the revision sessions, just send Quentin an
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| Time and place | Gatsby Unit room 409, 4th floor, 17 Queen Square |
| Lectures | Tuesdays and Fridays 11am to 1pm |
| Revision sessions | Fridays 2 - 3pm |
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| 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 maths 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, chapter 1 and
2. A few very useful cribsheets: basic maths you'll need
for this course, some matrix identities, and more matrix algebra.
Some other useful resources on the web, including other theoretical
neuroscience course sites are here. You might also be interested in
the Gatsby neuro journal club. |
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| Date | | Reading | Assignment |
| 8.10. | Lecture 1
Ions, membranes, Hodgkin and Huxley |
Dayan and Abbott chapter 5
For the keen:
Johnston and Wu, chapter 2, 5 and 6
Hodgin and Huxley (1952) | 1, pdf |
| 15.10. | Lectures 2/3
Cable equation and synapses |
Dayan and Abbott chapter 6
For the keen: Koch (1999): chapters 2-5
Cox and Gabbiani's course site | 2, pdf |
| 22.10. | Lectures 4/5
Synapses and phase planes |
Dayan and Abbott chapter 5/6
For the keen:
Wilson: Spikes, Decisions, Actions
Gerstner and Kistler: Spiking Neuron Models | 3, pdf |
| 29.10. | Lectures 6/7
Systems neuroscience,
spike statistics |
Dayan and Abbott chapter 2 on vision
Carpenter RHS: chapters on vision and hearing
More in depth: Kandel: chapters 25-31
Zigmond: chapters 21,22,27,28
Spike stats: Richard Hahnloser's notes
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4, pdf |
| 5.11. | Lectures 8/9
Encoding models / spike analysis |
lecture 8 slides: discrete encoding
lecture 9 slides: continuous encoding
Dayan and Abbott chapter 3/4
A review paper on LN methods
and one on point
processes in neuroscience: Brown et al. 2002
| 5, pdf |
| 12.11. | Lectures 10/11
Decoding models / Info theory |
lecture 10 slides: decoding
lecture 11 slides: estimation of information-theoretic quantities
Dayan and Abbott chapter 3/4
notes on sufficient statistics | 6, pdf |
| 19.11. | Lectures 12/13
Information theory / Population coding |
Dayan and Abbott chapter 3/4 | 7, pdf |
| 26.11. | Lectures 14/15
Learning / Hebb rules |
Dayan and Abbott chapter 8
lecture 14/15 slides
| 8,
pdf |
| 3.12. | Lectures 16/17/18
Dynamics of large networks |
Wilson and Cowan 1972, 1973
Wilson: Spikes, Decisions, Actions
Dayan and Abbott chapter 7 | 9, pdf |
| 10.12. | Lecture 19
Reinforcement learning |
Dayan and Abbott chapter 9
lecture 18/19 slides
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| Page maintained by Quentin Huys |
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