Learning to Attend: Modeling the Shaping of Selectivity in Infero-temporal Cortex in a Categorization Task |
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Authors: | Miruna Szabo Martin Stetter Gustavo Deco Stefano Fusi Paolo Del Giudice Maurizio Mattia |
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Institution: | Siemens AG, Corporate Technology, Information and Communications, Otto-Hahn-Ring 6, 81739, Munich, Germany. |
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Abstract: | Recent experiments on behaving monkeys have shown that learning a visual categorization task makes the neurons in infero-temporal
cortex (ITC) more selective to the task-relevant features of the stimuli (Sigala and Logothetis in Nature 415 318–320, 2002).
We hypothesize that such a selectivity modulation emerges from the interaction between ITC and other cortical area, presumably
the prefrontal cortex (PFC), where the previously learned stimulus categories are encoded. We propose a biologically inspired
model of excitatory and inhibitory spiking neurons with plastic synapses, modified according to a reward based Hebbian learning
rule, to explain the experimental results and test the validity of our hypothesis. We assume that the ITC neurons, receiving
feature selective inputs, form stronger connections with the category specific neurons to which they are consistently associated
in rewarded trials. After learning, the top-down influence of PFC neurons enhances the selectivity of the ITC neurons encoding
the behaviorally relevant features of the stimuli, as observed in the experiments. We conclude that the perceptual representation
in visual areas like ITC can be strongly affected by the interaction with other areas which are devoted to higher cognitive
functions.
Electronic Supplementary Material: Supplementary material is available in the online: version of this article at http://dx.doi.org/10.007/s00422-006-0054-z |
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