Neural and Behavioral Modeling 2018 Fall

Neural and Behavioral Modeling @ NTU, given by Prof. Tsung-Ren Huang.

Syllabus

Week	Subject
01	National Holiday
02	Course Introduction: Models & modeling
03	Behavioral Modeling (1/2): System dynamics
04	Behavioral Modeling (2/2): Agent-based modeling
05	Computational Cognitive Science (1/2): Basics
06	National Holiday
07	Computational Cognitive Science (2/2): Advanced
08	Computational Cognitive Neuroscience (1/8): Modeling principles & canonical neural computation
09	Computational Cognitive Neuroscience (2/8): Overview of learning & memory
10	Computational Cognitive Neuroscience (3/8): Local/shallow learning & memory
11	Computational Cognitive Neuroscience (4/8): Global/deep learning & memory
12	Computational Cognitive Neuroscience (5/8): Deep convolutional neural networks
13	Computational Cognitive Neuroscience (6/8): Deep reinforcement learning
14	Computational Cognitive Neuroscience (7/8): Deep recurrent neural networks
15	Computational Cognitive Neuroscience (8/8): Advanced issues & models
16	Computational Neuroscience (1/2): 1 spiking neuron
17	Computational Neuroscience (2/2): N spiking neurons

Weekly Assignments

Assignments are in the hw folder. (R06227101_#.ipynb)

#	Description
01	no assignment
02	1. Party Simulation 2. Shunting Equation
03	1. Nonlinear love triangle 2. Tragedy of the Commons
04	Replicate one Agent-Based Model (group genesis in homogeneous population)
05	1. Drifit Diffusion Model 2. Port EZdata.m from Matlab to Python
08	Replicate Sequence Memory Model
09	no assignment
10	2-layered Linear Network(numpy & pytorch version)
11	Tuning the performance of a neural net
12	1. Neural Network performance assessment 2. Universal Approximation Theorem
14	Activation/Signal Function in RNN
15	1. Visualizing the latent space of an autoencoder 2. Integer Factorization
16	Integrate-and-Fire Neuron with a Refractory Period
17	(optional)