Neural Computation 2009-2010

Neural Computation (NC) is a 10 point MSc course of 18 lectures in the first semester.
Lectures are Tuesday and Friday: 12.10-13.00, Tuesday in AT 2.14 and Friday in 1GS, Gaddum. We start on time!
Instructor: Mark van Rossum

Short description

In this course we study the computations carried out by the nervous system. Unlike other courses and aritifical neural networks, we take a bottom-up approach. This means that we incorporate data from neurobiology, simulate certain aspects of it, and try to formulate theories about the brain.

Keywords: single neuron models, neural codes, plasticity models.

Copies of the lecture notes part1, part2 will be handed out in the lectures. Many of the cited references can be found using PubMed

Office hours: make an appointment or catch me after the lecture.

Prerequisites

No prior biology/neuroscience knowledge is required. I use a small subset of not very advanced math in the lectures. These older FMCS lecture notes can be used as a refresher. Alternatively, use Google to refresh forgotten maths if needed. If you are still stuck, use the practicals or office hours to resolve the problems.

In the tutorials we use MatLab and NEURON (a special purpose simulator). No prior experience with either is required, however MatLab skills are valuable for many courses.

More information on Matlab and how to make graphs and write reports.

Assessement

The course will be fully assessed by two reports of practical assignments which will appear here (deadlines will be announced). The two marks are averaged. Standard late policies will apply. Also see How to make graphs and write reports.

Assignment 1 Voltage clamps. Deadline 11/12 at noon. Handin to ITO.

Assignment 2 Rate based networks. Deadline 22/12 at noon.

Practicals

Practicals are Wednesdays in AT 5.08, from 16.00 to 18.00. No practicals in the first week. Tutors are Mike Hull and Annie Huo.

Timetable (approximate)

Week 1; week of Sep 21
Tuesday lecture: NO LECTURE
Friday lecture: 1. Introduction and Chapter 1: Anatomy
No practical.

Week 2; week of Sep 28
Tuesday lecture: 2. Chapter 2: Passive properties.
Friday lecture: NO LECTURE
Practical: 1. The NEURON simulator: Passive properties

Week 3; week of Oct 5
Tuesday lecture: 3. Chapter 3: Hodgkin-Huxley
Friday lecture: 4. Chapter 3: Hodgkin-Huxley
No practical

Week 4; week of Oct 12
Tuesday lecture: 5. Chapter 4: Synapses
Friday lecture: NO LECTURE
Practical: 2. The NEURON simulator: Hodgkin-Huxley model

Week 5; week of Oct 19
Tuesday lecture: NO LECTURE
Friday lecture: 6. Chapter 4: Synapses
Practical: 3. NEURON: Interactions of synapses on dendrites

Week 6; week of Oct 26
Tuesday lecture: 7. Chapter 5: Integrate and Fire
Friday lecture:8. Chapter 6: Firing statistics
Practical: 4. Matlab: AMPA receptor simulation. Script (will appear later): ampa.m

Week 7; week of Nov 2
Tuesday lecture: 9. Chapter 7: Retina and V1
Friday lecture: 10. Chapter 7: Retina and V1

Week 8; week of Nov 9
Tuesday lecture: 11. Chapter 8: Population codes
Friday lecture: 12. Chapter 8: Coding
Practical: 5. Matlab: Mutual information of a Poisson spiker Script (will appear later): bits.m

Week 9; week of Nov 16
Tuesday lecture: 13. Chapter 9: Higher visual processing
Friday lecture: 14. Chapter 10: Networks
Practical: 6. Matlab: Ben-Yishai network Script: ben2.m

Week 10; week of Nov 23
Tuesday lecture: 15. Chapter 11+12: Decisions
Friday lecture: 16. Chapter 13: Hebbian Learning
No practical.

Week 11; week of Nov 30
Tuesday lecture: 17. Chapter 14: Spike timing dependent plasticity
Friday lecture:
Practical: 7. Matlab: Hebbian learning with constraints Script (will appear later): hebb.m

Additional information:

Additional Matlab: An Integrate and fire neuron Script: mvr_if_matlab.m

Movies of LGN and V1 recordings (play with mplayer under linux):

hubel_Wiesel_lgn_off_cell.asf
hubel_wiesel_binocular_cell.asf
hubel_wiesel_complex.asf
hubel_wiesel_directional_cell.asf
hubel_wiesel_lgn_on_cell.asf
hubel_wiesel_simple_cell.asf

Recurrent 6-node network with chaotic behavior bifur6.m

Home : Teaching : Courses : Nc