Class Notes (1,100,000)
CA (650,000)
McGill (40,000)
PSYC (4,000)

PSYC 532 Lecture Notes - Short-Term Memory, Spreading Activation, Connectionism

Course Code
PSYC 532
Rick Schultz

This preview shows page 1. to view the full 4 pages of the document.
Connectionism Lecture Notes
These are additional notes to the slides so it would be best to follow along with the slides for full
coverage of the topic….
Each Unit Has Simple Program:
Difference between biology and computer= excitatory and inhibition
Psychological Equivalents:
Pattern of activation across units (active or not)
Long term v.s Short term memory
Connection weights are being adjusted
Adjustment of connection weights= in order to reduce error
~Most general scheme…
Auto-Associator network:
Circles= units which are all doing the same job + fully connected to each other
Inputs-all are receiving this
Outputs-all sending this
Units + connection weights
Taking out some unit will make it do different things
Other Networks Have Restrictions:
Some constraints on values of connections e.g: Some groups of units have mutually inhibitory
connections (which are competing with each other)
~Good at learning patterns + generalization…
Output units= answer to problem
Hidden units= internal computation, no output or input
Input units= describe particular problem working on
o No lateral connections
o No communicating within a layer
o No backward connections
Distributed representations:
Each rectangle represents a neuron
Pattern represents a concept or an idea
Each different pattern represents a different idea
Each unit (96) is participating in different concepts
You're Reading a Preview

Unlock to view full version