Introduction to Theoretical Neuroscience (Spring 2018)
Larry Abbott, Ken Miller, Stefano Fusi
Meetings – Tuesday, Thursday 2:00 - 3:30pm
Location – Jerome L Greene Science Center, 5th floor, conference room L5-084. (3227 Broadway, New York, NY 10027)
TAs – Ramin Khajeh, Jacob Portes, Sean Bittner
Text – Theoretical Neuroscience by P. Dayan and L.F. Abbott (MIT Press)
Website – https://ctn.zuckermaninstitute.columbia.edu/courses
Schedule
January
16 Course Overview, Matlab basics for neuroscience modeling (Ken, Stefano, Sean)
18 ODEs, Linear Algebra basics for neuroscience modeling (Ramin)
23 ODEs, Linear algebra with Matlab for neuroscience models (Jacob)
25 Electrical Properties of Neurons, Integrate-and-Fire Models (Larry)
30 Synapses, Short-Term Plasticity, Release Probability (Stefano)
February
1 Long-term plasticity (Stefano)
6 Hodgkin-Huxley (Larry)
8 Adaptation, Izhikevich Model, Phase-Planes, Stability Analysis (Larry)
13 Poisson spiking (Larry)
15 White Noise and Its Effect on I&F model (Larry)
20 Spike-Triggered Averages, Reverse Correlation, Visual Receptive Fields (Ken)
22 GLMs, Maximum Likelihood and Generative Models (Ken)
27 Population Encoding and Decoding (Ken)
March
1 Noise and Correlation Analyses (Ken)
6 [Cosyne Conference] - TA Review Session (Sean, Ramin, Jacob)
8 PCA, Dimensional Reduction (Larry)
13 SPRING BREAK
15 SPRING BREAK
20 Readouts, Perceptrons (Stefano)
22 Spiking and Rate Networks (transition from spiking to rate) (Stefano)
27 Network math (Ken)
29 Balanced Spiking Networks, E/I balance, stabilization and amplification (Ken)
April
3 Fixed Points, Lyapunov Fctn; Ring Model; Decision-making networks? (Ken)
5 Cortical Map Formation (Ken)
10 Perceptrons, 2-layer networks (Stefano)
12 Deep Networks, backprop, convolutional nets (Stefano)
17 Recurrent Networks (Hopfield, Capacity) (Stefano)
19 Chaotic Networks (Larry)
24 Recurrent Networks (learning) (Larry)
26 Reinforcement Learning (Stefano)