NSCI 401: Introduction to Modelling in Neuroscience

Syllabus (2017-2018)

Classroom: BioSci, Room 1120
Day, time: Tuesdays, 8:30am - 11:30am

Office hours: Jonathan Coutinho (TA) - please make an appointment!
Botterell Hall, Rm 257
Office hours with Jonathan are for questions on team-based learning projects and paper presentations. For lecture-related questions, please contact me.

Course organization (Sept 12)
Paper selection, course outline

Lecture (Sept 12):
The computational anatomy of the brain
Brain structures and their functional role
Information flow
Cortical organization

Health and wellness...

Lecture (Sept 12):
Single neuron models
Introduction to the working principles of neurons
Membrane potentials
Ion channels
An excursion into electricity
Modelling single neuron behaviour
Synaptic inputs
Integrate and fire models
Hodgkin-Huxley neuron model
Other models

Sept 20: drop-out limit

Seminar (Sept 26):
Izhikevich (2003) - Kaija K, Izabelle S
Rolls, et al. (2008) - Greg B, Ciara M, Alex P

Reading assignment (Sept 19)
Jonas & Kording's chip paper

Write a 1-page (12pt, single line spacing) essay with your scientifically justified opinion on one specific selected point that the paper makes. Submit a PDF version to me by Sept 25 midnight!

Lecture (Sept 26):
Spike coding
What is a code?
Spike train properties
Spike rates
Tuning curves
Spike count variability
Poisson statistics
Spike coding
Cosine tuning
Population coding
A few words about decoding

Seminar (Oct 10):
Petersen, et al. (2002) - Chelsea D, Hanieh G, Marianne J
Stevenson et al. (2012) - Tayyaba B, Stefan N, Emma R

Team-based learning project (Sept 26 - Oct 9):

Reading portfolio
Deneve & Pouget (2004)
Körding & Wolpert (2006)
Probabilities primer (optional)

Project - groups

Deadline for submission: Oct 9, 11:59pm

"Tell me, and I will forget.

                                    Show me, and I may remember.
                                    Involve me, and I will understand."
(Chinese proverb)

Lecture (Oct 10):
Sensory processing
World-brain interface
Sensory organs
Sensory pre-processing
Sensory processing
Sensory receptive fields
Gain modulation
Self-organizing maps

Seminar (Oct 17):
Bradley & Goyal (2008) - Alana D, Christine L, Dasha R
Aumentado-Armstrong et al. (2015) - Junyang Y, Betty C, Elisha K

Lecture (Oct 17):
Eye movements

Introduction to eye movements
Neural substrates
Control problems
Modelling eye movements
Linear systems theory
Modelling the eye (Laplace formalism)
Gaze holding (the neural integrator)
Motor command generation
Coordinating different eye (and head) movements
Problems and solutions

Seminar (Oct 24):
Ghasia, et al. (2008) - Bradley B, Berkeley S, Wendy Y
Orban de Xivry et al. (2013) - Sohaib H, Rachel W, Henri V

Lecture (Oct 24):
Decision making
What are decisions?
Involved brain structures
Basal ganglia
Models of decision making
Race models
Diffusion models
Optimal decision criteria
Conflict resolution - winner-take-all

Seminar (Oct 31):
Resulaj, et al. (2009) - Chelsea J, Will K, Wara L
Perugini et al. (2016) - Benett B, Iman K, Nancy Y

Lecture (Oct 31):
Modelling attention
What is attention?
Overt vs. covert attention
Visual attention
Neural mechanisms
Modelling visual attention (Itti & Koch)
Feature maps
Saliency maps
Top-down modulation: expectation & task demands
Selective tuning model & hierarchies (Tsotsos)

Seminar (Nov 7):
Miconi & VanRullen (2016) - Samantha L, Megan M, Elisabeth T

Lecture (Nov 7):
Adaptation and learning
What is learning?
Motor learning
Systems level approach
Synaptic plasticity
Hebbian learning
Physiology and biophysics
Learning in neural networks
Supervised vs. unsupervised learning
Conditioning and reinforcement learning

Seminar (Nov 21):
Izhikevich (2007) - Toros C, Chris Z
Kool et al. (2016) - Kevin H, Caitlyn K

Team-based learning project (Nov 7-20):

Reading portfolio
Scott (2012)
Diedrichsen, et al. (2010)
Shadmehr & Krakauer (2008)

Project - groups

Deadline for submission: Nov 20, 11:59pm

"Any fool can know.
The point is to understand."

(Albert Einstein)

Lecture (Nov 21):
Definition & processes
Long-term vs. short-term memory
Short-term memory
Neuronal behaviour
Potential mechanisms
Link to attention
Memory theories (long-term)
Associative and auto-associative memory
Distributed memory
Sparse coding and capacity

Seminar (Nov 28):

Wilson & Linster (2008) - Matthew B, Charissa L
Couey, et al. (2013) - Mike F, Sarah F

Lecture (Nov 28):

Bayesian TBL Project debriefing slides
Optimal Control Theory TBL Project debriefing slides

Preliminary marks (60% of final mark)

Exam questions
(Fall 2017)

Time and location: Dec 15, 7PM, Jeffery Hall
(3h exam)
Fall 2010 exam questions (FYI)
Fall 2011 exam questions (FYI)
Fall 2012 exam questions (FYI)
Fall 2013 exam questions (FYI)
Fall 2014 exam questions (FYI)
Fall 2016 exam questions (FYI)

Peer Support Centre

Further readings:
Peter Dayan & Larry F. Abbott. Theoretical Neuroscience. MIT-Press, 2001
Thomas P. Trappenberg. Fundamentals of Neuroscience (2nd Ed.). Oxford University Press, 2010

Please read this about academic integrity!