Learning and Selective Attention
Peter Dayan Sham Kakade P Read Montague
Nature Neuroscience, 3 , 1218-1223.
Abstract
Selective attention involves the differential processing of different
stimuli, and has widespread psychological and neural consequences.
Although computational modeling should offer a powerful way of
linking the observable phenomena at different levels, a bulk of work
has focused on the relatively narrow issue of constraints on
processing resources. By contrast, we consider statistical
and informational aspects of selective attention,
divorced from resource constraints. These aspects are cleanly
evident in animal conditioning experiments involving uncertain
predictions and unreliable stimuli. Neuromodulatory systems and
limbic structures are known to underpin attentional effects in such
tasks.
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