Paper Available

[Stephen Hanson]

Development of Schemata during Event Parsing:
Neisser's Perceptual Cycle as a Recurrent Connectionist Network


Catherine Hanson   &  Stephen Jose Hanson
Temple University     Siemens Research & Princeton University



Abstract:

Neural net simulations of human event parsing are described. A recurent net
was used to simulate data collect from humna subjects watching short
videotaped event sequences. In one simulation the net was trained on
one-half of a taped sequence with the other half of the sequence being used
to to test transfer performance. In another simulation the net was trained
on one complete event sequence and transfer to a different event sequence
was tested.  Neural Net simulations provided a unique means of observing
the interrelation of top-down and bottom-up processing in a a basic
cognitive task.  Examination of computational patterns of the net and
cluster analysis of the hidden units revealed two factors that may be
central to event perception: (1) similarity between a current input and an
activated schema and (2) expected duration of a given event.  Although the
importance of similarity between input and activated schemata during even
perception has been acknowledged previously (e.g. Neisser, 1976, Schank,
1982), the present research provides specific instantiation of how
similarity judgements can be made using both top-down and bottom-up
processing. Moreover, unlike other work on event perception, this approach
addresses potential mechanisms for how schemata develop.


Journal of Cognitive Neuroscience 8:2, pp. 119-134, 1996.


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