Joseph's class notes, in

[PDF].

Lecture 01: [PPT] : Overview; background on neural functioning

Lecture 02: [PPT] : Neurons; motor control

Lecture 03: [PPT] : Motor control; neural development

Lecture 04: [PPT] : Neural wiring; connectionist models: basics

Lecture 05: [PPT] : Artificial Neural Networks;
Psychological considerations

Lecture 06: [PPT] : Brain imaging

Lecture 07: [PPT] : Learning: biological and connectionist

Lectures 8-9: [PPT] : Connectionist models: backpropagation,
neural net extensions, and recruitment learning

Lecture 10: [PPT] : Color

Lecture 11-12: [PPT] : Categories & concepts; Image schemas

Lecture 12: [PDF] : Image schemas

Lecture 13: [PPT] : The Regier model

Lecture 14: [PPT] : Regier; force dynamics; brain motor areas; motor schemata; etc.

(Lecture 16: Motor control and x-schemas)

Lecture 17: [PPT] : The Bailey model and model merging: Part I

Lecture 18: [PPT] : The Bailey model and model merging: Part II

Lecture 19: [PPT] : The temporal structure of events: aspect and x-schemata

Lecture 20: [PPT] : FrameNet

Lecture 21: [PPT] : Metaphor

Lecture 22: [PPT] : Metaphor, Bayes nets, and the Narayanan model

Lecture 23: [PPT] : SHRUTI

Lecture 24: [PDF] : Grammar

(Lecture 25: Review Etc.)

Lecture 26: [PDF] : A Bayesian model of sentence processing

Lecture 27: [PPT] : Embodied construction grammar (ECG)

Lecture 28: [PPT] : Neuroeconomics

Lecture 29: [PPT] : Applications

Lecture 30: [PPT] : Review

Week 01: [PPT]

Week 02: [PPT]

Week 03: [PPT]

Week 04: [PPT]

Week 05: [PPT]

Week 06: [PPT]

Week 07: [PPT]

Week 08: [PPT]

Week 09: [PPT]

Week 10: [PPT]

Week 11: [PPT]

Week 12: [PPT]

Week 13: [PPT]

Week 14: [PPT]

Week 15: [PPT]

Backpropagation: [PDF]

A longer set of notes on backprop (including the momentum term)
and neural nets: [PDF]