Computational Modeling of Pair-Association Memory in Inferior Temporal
Cortex
Masahiko Morita and Atsuo Suemitsu
Abstract:
Distinctive neuronal activities related to visual stimulus-stimulus
association have been found in the inferior temporal (IT) cortex of
monkeys. They provide an important clue to elucidating the memory
mechanisms of the brain, but do not accord with existing neural
network models. In the present paper, we clarify the computational
principle required for reproducing the empirical data and construct a
biologically feasible model that learns and performs a delayed
pair-association task. This model is composed of two neural networks,
association network N1 and trainer network N2, and pair-association
memories are formed by their interactions. Specifically, N2 receives
the output of N1 in addition to an external input, and sends a
learning signal back to N1; this signal works as a guide for shifts in
output pattern or state transitions of N1, and memory traces are
engraved along its path, so that a trajectory attractor connecting
from the cue-coding to the target-coding state is formed in
N1. Computer simulation shows that the model not only distinguishes
the target in the task, but also explains the activity of the IT
neurons very well. It is reasonable to presume that N1 and N2
correspond to area TE and the rhinal cortex, respectively; based on
this theory, we explain some physiological findings on learning and
memory, and also make several predictions.
Keywords:
inferotemporal cortex, pair-recall neuron, perirhinal cortex,
computational theory, trajectory attractor, feedforward-inhibition
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