Larry Abbott, Stefano Fusi, Ashok Litwin-Kumar, Ken Miller
Meetings: Tuesdays, Lectures 12.30 - 2.00pm, Recitations 2.00 - 3.30pm
Thursdays, Math Supplements 12.30 - 2.00pm, Lectures 2.00 - 3.30pm
Location: Jerome L Greene Science Center, 5th floor, conference room L5-084
TAs: Ella Batty, Ramin Khajeh, Salomon Muller, Danil Tyulmankov, Marjorie Xie
Text: Theoretical Neuroscience by P. Dayan and L.F. Abbott (MIT Press)
January
22 Math Intro: Differential Equations (Ashok)
24 Electrical Properties of Neurons, Integrate-and-Fire (Larry) - Assign 1 download
Calculus Review (Dan)
29 Adaptation, Izhikevich Model, Phase-Planes, Stability Analysis (Larry)
Recitation (Ramin)
30 Assign 1 Due
31 The Hodgkin-Huxley Model (Larry)
Taylor Series, Linearization (Dan)
February
5 Synapses, Short-Term Plasticity, Release Probability (Stefano) - Assign 2 download
Recitation (Ramin)
7 Probability / Poisson spiking, Central Limit Theorem/Gaussian (Larry)
Combinatorics (Dan)
12 Probability / Encoding I (Ken, lecture notes) - Assign 3 download
Recitation (Ramin)
13 Assign 2 Due
14 Linear Algebra I (Ken)
Linear Algebra 0 (Dan)
19 Linear Algebra II (Ken) Assign 4
Recitation (Marjorie)
20 Assign 3 Due
21 Dimensional Reduction I (Ken)
Linear systems (Dan)
26 Dimensional Reduction II (Ashok) - Assign 5 download
Recitation (Marjorie)
27 Assign 4 Due
28 COSYNE
March
5 COSYNE
Recitation (Marjorie)
7 Receptive Fields, GLMs, and Maximum Likelihood (Ashok)
Convolution (Dan)
12 Spike and Rate Networks I (Larry)
Recitation (Marjorie)
13 Assign 5 Due
14 Spike and Rate Networks II (Stefano) - Assign 6 download
Fourier transforms (Dan)
19 Spring Break
21 Spring Break
26 E/I Networks I (Ken)
Recitation (Salomon)
28 E/I Networks II (Ken) - Assign 7 download
Multivariable calculus (Dan)
April
2 Decision-Making Networks (Stefano)
Recitation (Salomon)
3 Assign 6 Due
4 Recurrent Networks - Hopfield and Random (Larry) - Assign 8 download
Multivariable calculus continued (Dan)
9 Optimization I (Ashok)
Recitation (Salomon)
10 Assign 7 due
11 Optimization II (Ashok) - Assign 9 download
Lagrange multipliers (Dan)
16 Perceptron and Decoding (Stefano)
Recitation (Ella)
17 Assign 8 Due
18 Learning in Recurrent Networks (Larry)
Probability (Dan)
23 Multilayer Perceptrons (Ashok) - Assign 10 download
Recitation (Ella)
24 Assign 9 Due
25 Deep Learning I (Stefano)
Probability continued (Dan)
30 Deep Learning II (Stefano)
Recitation (Ella)
May
1 Assign 10 Due
2 Reinforcement Learning (Stefano) - Assign 11
Information Theory (Dan)
7 Recitation (Ella)
8 Assign 11 Due
Meetings: Wednesdays, 10.15 - 11.45am
Location – Jerome L Greene Science Center, 6th floor room L6-087
Encoding and Decoding
Jan 23 Intro (Fabio Stefanini)
Jan 30 Linear & Logistic Regression (Ramon Nogueira, Josh Glaser)
Feb 6 GLM & Nonlinear Regression (Ramon Nogueira, Josh Glaser)
Feb 13 Static Models for Dimensionality Reduction (Matt Whiteway)
Feb 20 Dynamic Models for Dimensionality Reduction (Shreya Saxena)
Feb 27 Cosyne
Mar 6 Cosyne
Mar 13 Hackathon Encoding & Decoding
Mechanistic Models of Neural Circuits
Mar 20 Intro. From Spiking Models to Population Rate Part I (Laureline Logiaco)
Mar 27 From Spiking Models to Population Rate Part II (Laureline Logiaco)
Apr 3 Inhibition Stabilized Networks & Supralinear Stabilized Networks (Mario Dipoppa)
Apr 10 Neural Variability in Rate Models, Appropriateness Spiking vs. Rate Models (Mario Dipoppa)
Apr 17 Equilibrium Theory for Hopfield Model (Alessandro Ingrosso)
Apr 24 Dynamic Mean Field Theory of Chaotic Rate Networks (Alessandro Ingrosso)
Learning in Recurrent Networks
May 1 Intro. Learning in Recurrent Networks, Backprop Through Time (Rainer Engelken)
May 8 Least-Squares, RLS, FORCE, Kalman Filters (James Murray)
May 15 Dynamic Mean Field Theory for Low-Rank Static Solutions (Rainer Engelken)
May 22 Control Theory for Low-Rank Static Solutions (James Murray)
May 29 Bonus