Receive signals from the hidden units and generate some output based on what is received.

Output units (connectionism)

Receives signals from the input units and sends them to the output units.

Hidden units (connectionism)

Activated by stimuli and send signals to the hidden units.

Input units (connectionism)

Determines the extent to which a signal increases or decreases activity of the unit it was sent to.

connection weight

Artificial Neural Networks are built to resemble neurons in the human brain. The idea behind neural networks is to understand the pattern behind terms through examples rather than through task-specific rules.

Artificial Neural Networks

Example of activated connectionist network for living things and their properties

When the network generates wrong responses, an error signal is produced to help the learning process

Error signal

When a part of a connectionist network is damaged, the entire system does not fail, and performance is only affected incrementally. This is similar to the brain, since someone with damage may retain all cognitive functionality aside from the functions that damaged area is specialized to.

graceful degradation

A network following the connectionist approach to cognitive modeling. Contains different kinds of units with connections between them. The units and connections are supposed to resemble neurons and their networks within the brain.

University of Michigan - Ann Arbor

An approach to computer-based cognitive model in which concepts are represented by distributed activity across a network.

Connectionism (parallel distributed processing (PDP))

Goldstein, E. B. (2014). Cognitive psychology: Connecting mind, research and everyday experience. Nelson Education.


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