NSCI 401: Introduction to Modelling in Neuroscience

Classroom: Mackintosh-Corry Hall, Room D214
Day, time: Mondays, 11:30am - 2:30pm

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.

All student presentations can be found here!

Course organization (Sept 10)
Paper selection, course outline

Jonny's slides on expectations and deliverables

Health and wellness...
Some health and wellness pointers

Short opinion paper assignment:
Jonas & Kording (2017)
(due Sept 16, 11:59pm; sent to TA - 12jdc1@queensu.ca)

Lecture (Sept 17):
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

Seminar (Sept 24):
Izhikevich (2003) - Conor D, Michael R
Rolls, et al. (2008) - Nikki F, Boris K, Andrew L

Sept 19: drop-out limit

Lecture (Sept 24):
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 1):
Petersen, et al. (2002) - Paul I, Jamil M, Demille O
Stevenson et al. (2012) - Emily L, Grace P, Natasha P

Lecture (Oct 1):
Sensory processing
World-brain interface
Sensory organs
Sensory pre-processing
Sensory processing
Sensory receptive fields
Gain modulation
Self-organizing maps

Seminar (Oct 15):
Bradley & Goyal (2008) - Aleks B, Sara G, Claudia T
Aumentado-Armstrong et al. (2015) - Marcelo D, Kate M, Maria S

Team-based learning project (Oct 2 - 14):

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

Project - groups

Deadline for submission: Oct 14, 11:59pm

"Tell me, and I will forget.

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

Lecture (Oct 15):
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 22):
Ghasia, et al. (2008) - Karen B, Alec L, Amin E
Orban de Xivry et al. (2013) - Adam A, Bailey B, Jonathan W

Lecture (Oct 22):
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 (Nov 5):
Resulaj, et al. (2009) - Matthew P, Antonia S, Justin S
Perugini et al. (2016) - Alexa B, Phoenix H, Nicole T

Team-based learning project (Oct 23 - Nov 5):

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

Project - groups

Deadline for submission: Nov 5, 11:59pm

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

(Albert Einstein)

Lecture (Nov 5):
Adaptation and learning
What is learning?
Motor learning
Systems level approach
Reinforcement learning (RL)
Synaptic plasticity
Hebbian learning
Physiology and biophysics
Learning in neural networks
Supervised vs. unsupervised learning
Conditioning and reinforcement learning

Seminar (Nov 12):
Izhikevich (2007) - Kristen L, Alex R, Joseph T
Kool et al. (2016) - David C, Obinna O, Nazgol K

Lecture (Nov 12):
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 19):
Miconi & VanRullen (2016) - n/a
Akbas & Eckstein (2017) - Andy G, Erin M, Rachel S

Lecture (Nov 19):
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 26):

Wilson & Linster (2008) - Victoria K, Jonathan L, Justin N
Couey, et al. (2013) - Michael A, Bernice H, Jessica K
Schneegans & Bays (2017) - Sophie C, Sarah H, Victoria C

Lecture (Nov 26):

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

Preliminary marks (70% of final mark)

Exam questions 
(Fall 2018)

Time and location: Dec 7, 2018 @ 2pm
(3h exam) - Bews Gym
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)
Fall 2017 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!