Detailed Schedule


Lecture notes and other supplementary materials will be uploaded here after each lecture...

Term 1

Date Subject Lecturer Materials
3 Oct Sensation, Perception, and Inference. Maneesh Sahani perception-slides
6 Oct Point processes Maneesh Sahani pointproc-slides
10 Oct Information Maneesh Sahani info-slides
13 Oct (lecture cancelled)
16 Oct (no lecture scheduled)
20 Oct (lecture cancelled)
24 Oct Olfaction Troy Margrie (no slides)
27 Oct

30 Oct
Population Coding Peter Latham Peter's handwritten notes
See also recommended reading below
7 Nov Representation and Computation with Uncertainty Maneesh Sahani Handout from last year
Slides from last year
10 Nov Audition Nick Lesica Audition slides
14 Nov (Overview Lecture) Control Problems Adam Kampff No slides
28 Nov Hippocampus John O'Keefe Awaiting slides
30 Nov Cortical and Sub-cortical Movement/Posture Control Andy Murray Awaiting slides
05 Dec Innate Behaviour and Animal Learning Yoh Isogai Awaiting slides
Lecture references
08 Dec Learning/RL Peter Latham Legacy lecture slides from Peter D

Term 2

Date Subject Lecturer Materials
23 Jan - 02 Feb Biophysics lectures x4 Peter Latham Math you need to know
Linear analysis
Cable equation/dendrites
See also references below
06 Feb Recording Electrical Signals in Neurons Tom Otis Lecture outline/refs
Lecture slides
09 Feb Synaptic Transmission Troy Margrie Lecture concepts, keywords
The recommended book "Synapses" by Cowan et al. is in the library
13 Feb Synaptic Integration in Single Neurons Tiago Branco Lecture outline
Lecture slides
The ‘Neuron’ simulation environment
16 Feb Genes and Behaviour Yoh Isogai Cancer cell commentary
20 Feb Attractor networks Peter Latham Some notes at:
23 Feb Recurrent rate networks/feedforward networks Peter Latham See notes at:

Extra resources

Please feedback to the TAs which resources you found helpful, so this list can improve over time...

Population coding

Recommended papers:

Legacy lecture slides


Student notes

Online resources


Math notes from Peter L

(see lecture list above)

Important papers


  • Foundational Neuroscience questions and answers. These look like well-written answers to systems-ey questions - at least 50% of them seem relevant to our TN course, similar to questions in the systems section of the short-question exam. Let us know if you find them useful.