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NEU/PSY 502
502A
Syllabus
Lectures
Paper Presentation Rubric
Class 1: Introduction and History
Class 2: Perception and Constraint Satisfaction
Class 3: Associative Learning and Topography
Class 4: Sequences and Predictions
Class 5: Dynamics of Integration and Decision Making
Class 6: Cerebellum and Error-driven Learning
Class 7: Reinforcement Learning
Class 8: Dopamine and Basal Ganglia
Class 9: Basics of Motor System + Motor Cortex
Class 10: Explore/exploit and noradrenergic neuromodulation
Class 11: Distributed Representation
Class 12: Episodic Memory and Hippocampal Function
Class 13: Bayesian Inference and Neural Networks (Griffiths)
Class 14: Episodic Memory and Sleep
Class 15: Attention, Control and Prefrontal Function
Class 16: Working memory
Class 17: Representation and Capacity Limits
Class 18: Optimization and Control
Class 19: Dynamics and Geometry of Control
Class 20: Oscillations and Coherence
Class 21: ISC & BCI
Class 22: Social Cognition
Class 23: Cognitive Neuropsychology and the Origins of Computational Psychiatry
Class 24: Development
502B
Syllabus
502B Computation
Introduction
1 Primer
1.1 Scalars, Vectors, and Matrices
1.2 Logistic Function
1.3 Perceptron and XOR
2 Dynamics in Perception
2.1 Hebbian Learning
2.2 Hopfield Networks
2.3 Dynamic Systems and Bistable Perception
3 Decision Making
3.1 Drift Diffusion Models
4 Reinforcement Learning
4.1 Reinforcement Learning
5 Statistical Learning and Backpropagation
5.1 Rumelhart Semantic Network
6 Episodic Memory
6.1 Episodic Memory
6.2 Episodic Generalization Optimization - EGO
7 Selective Attention, Automaticity, and Control
7.1 Stroop Model
8 Conflict Monitoring, Effort, and Control
8.1 Conflict Monitoring
9 Integration, Attention, Context, and Control
9.1 ISC-CI Model
502B Empirical
Introduction
Repository
Open issue
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Syllabus
Syllabus
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