Psych 711 Syllabus

Section I: Basics

DOWNLOAD LECTURE SLIDES HERE

Jan. 17, 19: Overview and basic principles

Connectionist models. In Squire, L. (Ed.), Encyclopedia of Neuroscience, volume 3, pp. 75-82. Oxford: Academic Press.

McClelland (2009). The place of modeling in cognitive science. Topics in Cognitive Science, 1 (2009), 11-38.

Optional: Rogers, T. T. and McClelland (2014) PDP at 25: Further explorations in the microstructure of cognition.

Slides here

Jan. 24, 26: Constraint satisfaction

Rumelhart, D. E. (1989). The architecture of mind: A connectionist approach. In M. I. Posner (Ed.), Foundations of cognitive science (pp. 133-159). Cambridge, MA: MIT Press.

Rumelhart, D. E., Smolensky, P., McClelland, J. L., & Hinton, G. E. (1986). Schemata and sequential thought processes in PDP models. PDP2, Chapter 14.

Lab 1: The Jets-and-Sharks model

Slides here

Homework 1: Constraint satisfaction models. Part 1: The Jets-n-Sharks model. Part 2: The Room Schema

Homework download: schema.zip

Feedback here

Jets-n-Sharks / IAC-style activation function.

Jan. 31, Feb. 2: Simple learning: Hebb and delta rules

McClelland, J. L., and Rumelhart, D. E. (1988). The pattern associator. PDP Handbook, Chapter 4 (pp. 83-96).

McClelland, J. L. & Rumelhart, D. E. (1986). A distributed model of human learning and memory. PDP2, Chapter 17.

Lab: Learning in LENS

Hebb demo Excel file

Demo illustrating gradient descent in error for delta rule (perceptron) learning 

Slides here

Homework 2: Hebb and Delta rules

HW 2: Download assignment here

Download network files for HW2

Feb. 7 and 9: Distributed representations. Homework 1 due!

Hinton, G. E., McClelland, J. L., & Rumelhart, D. E. (1986). Distributed representations. PDP1, Chapter 3.

**No lab this week, begin developing project proposal**.

Feb. 14, 16 : Backpropagation

Rumelhart, D. E., Hinton, G. and Williams, R. (1986). Learning internal representations by backpropagating errors PDP1, Chapter 8.

McClelland, J. L. & Rumelhart, D. E. (1986). A distributed model of human learning and memory. PDP2, Chapter 17.

Lab: The XOR problem, building your own network

Download Excel demo illustrating linear separability constraint on delta rule

Slides here

Homework 3: Backpropagation

Download backpropagation assignment here

Download XOR network files

Section 2: Flavors

Feb. 21, 23: Building your own network

See FF network tutorial here

Lab: Building your own feed-forward network.

Feb. 28, March 2: Simple recurrent networks.

Elman, J. L. (1990). Finding structure in time. Cognitive Science, 14, 179-211

Lab: Building and testing simple recurrent networks

See SRN tutorial here

slides here

March 7, 9: Fully recurrent networks.

*** Project proposals due ***

Hinton, G. E. & Sejnowski, T. J. (1986). Learning and relearning in Boltzmann Machines. PDP1, Chapter 7.

Lab: Building and testing fully recurrent networks

slides here

March 14, 16: Self-organizing networks and “deep learning,” Homework 3 due.

Rumelhart, D. E. & Zipser, D. (1986). Feature discovery by competitive learning. PDP1, Chapter 5.

Kohonen, T. (1990). The self-organizing map. Proceedings of the IEEE, 78, 1465-1480.

Lab: Looking at model data 1 (unit activations)

slides here

———-SPRING BREAK———–

Section 3: Applications

March 28, 30: Perception.

McClelland et al. (2014), Interactive activation and mutual constraint satisfaction in perception and cognition. Cognitive Science, 38, 1139-1189.

Lab: Looking at model data 2 (similarity structure)

slides here

April 4, 6: Cognitive control

Botvinick, M. M. and Cohen, J. (2014). The computational and neural basis of cognitive control: Charted territory and new frontiers. Cognitive Science, 38, 1249-1285.

Lab: Project progress reports.

April 11, 13: Neural networks and Bayesian approaches

McClelland et al. (2010). Letting structure emerge. Trends in Cognitive Science.
Griffiths et al. (2010), Probabilistic models of cognition, Trends in Cognitive Science.

Lab: Project clinic–bring your model and I will consult!

April 18, 20: Memory

O’Reilly, R. C. et al. (2014). Complementary learning systems. Cognitive Science, 38, 1229-1248.

Lab: Project progress reports.

April 25, 27: Language

Seidenberg, M. S. and Plaut, D. C. (2014). Quasi-regularity and its discontents: The legacy of the past-tense debate. Cognitive Science, 38,

Lab: Project progress reports.

May 2, 4: Consciousness

Cleeremans, A. (2014). Connecting conscious and unconscious processing. Cognitive Science, 38, 1286-1315.

Lab: Progress reports