Courses

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

Download Schedule 

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)