jose@glacier.ics.uci.edu (Jose Ambros-ingerson) (03/31/89)
Preprints of two recent publications are available from the Computational
Neuroscience Program at the University of California at Irvine:
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DERIVATION OF ENCODING CHARACTERISTICS OF LAYER II CEREBRAL CORTEX
Richard Granger, Jose Ambros-Ingerson, and Gary Lynch
Center for the Neurobiology of Learning and Memory
University of California
Irvine, CA. 92717
Computer simulations of layers I and II of piriform (olfactory) cortex
indicate that this biological network can generate a series of distinct
output responses to individual stimuli, such that different responses encode
different levels of information about a stimulus. In particular, after
learning a set of stimuli modeled after distinct groups of odors, the
simulated network's initial response to a cue indicates only its group or
category, whereas subsequent responses to the same stimulus successively
subdivide the group into increasingly specific encodings of the individual
cue. These sequences of responses amount to an automated organization of
perceptual memories according to both their similarites and differences,
facilitating transfer of learned information to novel stimuli without loss
of specific information about exceptions. Human recognition performance
robustly exhibits multiple levels: a given object can be identified as a
vehicle, as an automobile, or as a Mustang. The findings reported here
suggest that a function as apparently complex as hierarchical recognition
memory, which seems suggestive of higher `cognitive' processes, may be a
fundamental intrinsic property of the operation of this single cortical cell
layer in response to naturally-occurring inputs to the structure. We offer
the hypothesis that the network function of superficial cerebral cortical
layers may simultaneously acquire and hierarchically organize information
about the similarities and differences among perceived stimuli.
Experimental manipulation of the simulation has generated hypotheses of
direct links between the values of specific biological features and
particular attributes of behavior, generating testable physiological and
behavioral predictions.
(Appears in Journal of Cognitive Neuroscience, 1:61-84, 1989).
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MEMORIAL OPERATION OF MULTIPLE, INTERACTING SIMULATED BRAIN STRUCTURES
Richard Granger, Jose Ambros-Ingerson, Ursula Staubli and Gary Lynch
Center for the Neurobiology of Learning and Memory
University of California
Irvine, CA. 92717
Primary findings from simulations of the superficial layers of olfactory
cortex have been that repeated sampling of stimuli has two major effects:
first, multiple samples greatly increase the information capacity of a
network compared to that for a single sample, and second, the breaking of the
response into distinct samples imposes an organization on the memories thus
read out. It was found that repetitive sampling allows the network to form
and read out a sequence of different representations of a stimulus, denoting
information ranging from the membership of that stimulus in a group of
similar stimuli, to specific information unique to the stimulus itself.
This led us to the hypothesis that the combination of particular cellular
physiological features, anatomical designs, and repetitive sampling
performance, allows cortical networks to construct perceptual hierarchies
(Lynch and Granger, 1989)*. Those initial simulation experiments did not
address what is presumably an essential feature of repetitive sampling:
namely, the interaction between the cortex and its inputs. The present paper
reviews both our isolated cortical simulations and our first efforts to
explore the issue of interaction between cortex and peripheral structures.
New findings indicate that the mechanism of repeated sampling enables active
analysis of stimuli into their learned components.
*[Lynch, G. and Granger, R. (1989). Simulation and analysis of a cortical
network. The Psychology of Learning and Motivation, Vol.23 (in press).]
(To appear in: Neuroscience and Connectionist Models,
M.Gluck and D.Rumelhart, Eds., Hillsdale: Erlbaum Associates, 1989.)
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Send requests for reprints to:
Richard Granger
Computational Neuroscience Program
Bonney Center
University of California
Irvine, California 92717
(granger@ics.uci.edu)