Learned predictiveness speeds visual processing
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Updated: May 24, 2026

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
Published on: January 23, 2017
Jennifer L O'Brien1, Jane E Raymond
1University of South Florida, USA.
Abstract:
When humans learn that the presence of a cue predicts the likelihood of an outcome, they can exploit this learned predictiveness, such that formation of subsequent associations between that cue and new outcomes is facilitated. Could such enhanced selection for association arise early enough to facilitate low-level visual processing? In a test of this possibility, adult volunteers first engaged in a value-learning task involving faces that were differentially predictive of monetary wins or losses. Later, in a simple recognition task, these faces were briefly presented for a variable duration and then masked. The critical presentation duration needed to produce criterion-level recognition was measured to index the visual processing speed for each learned face. Critical duration was significantly shorter for stimuli with high learned predictiveness than for stimuli with low learned predictiveness, regardless of whether they were associated with wins or losses. These results show that neural mechanisms involved in predicting future outcomes are able to modulate visual processing efficiency, probably via cortical feedback processes.
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