August 2010
Volume 10, Issue 7
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2010
Increases in perceptual capacity as a function of perceptual learning: behavioral regularities and possible neural mechanisms
Author Affiliations
  • Michael Wenger
    Department of Psychology, The Pennsylvania State University
  • Rebecca Von Der Heide
    Department of Psychology, The Pennsylvania State University
  • Jennifer Bittner
    Department of Psychology, The Pennsylvania State University
  • Daniel Fitousi
    Department of Psychology, The Pennsylvania State University
Journal of Vision August 2010, Vol.10, 1116. doi:10.1167/10.7.1116
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      Michael Wenger, Rebecca Von Der Heide, Jennifer Bittner, Daniel Fitousi; Increases in perceptual capacity as a function of perceptual learning: behavioral regularities and possible neural mechanisms. Journal of Vision 2010;10(7):1116. doi: 10.1167/10.7.1116.

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Abstract

Standard indicators of the acquisition of visual perceptual expertise include systematic reductions in detection and identification thresholds, along with decreases in mean response times (RTs). One additional regularity documented in recent work has to do with changes in the ability to adapt to variations in perceptual workload, characterized as perceptual capacity, and measured at the level of the hazard function of the RT distribution. The present effort tests the potential of a computational modeling approach capable of accounting for these behavioral results, while simultaneously predicting patterns of scalp-level EEG. The approach is intended to allow for the representation of multiple competing hypotheses for the neural mechanisms responsible for these observable variables (i.e., placing the alternative hypotheses on a “level playing field”), and for the ability to systematically relate these hypotheses to formal models for perceptual behavior. The neural modeling approach uses populations of discrete-time integrate-and-fire neurons, connected as networks. The architecture is based on the known circuitry of early visual areas as well as known connectivity into and out of early visual areas. The architecture is shown to be capable of instantiating a set of prominent competing hypotheses for neural mechanisms (Gilbert, Sigman, & Crist, 2001): changes in cortical recruitment, sharpening of feature-specific tuning curves, changes in synaptic weightings, changes in within-region synchrony, and changes in across-region coherence, in both feed-forward and feed-back relations. In addition, it is shown that under reasonable simplifying assumptions, the models are also capable of making predictions for both observable response behavior and scalp-level EEG. We present data from an initial empirical test of these predictions, suggesting that changes in measures of synchrony across and within sensor regions best account for the prominent increases in perceptual capacity that accrue with the acquisition of perceptual expertise.

Wenger, M. Von Der Heide, R. Bittner, J. Fitousi, D. (2010). Increases in perceptual capacity as a function of perceptual learning: behavioral regularities and possible neural mechanisms [Abstract]. Journal of Vision, 10(7):1116, 1116a, http://www.journalofvision.org/content/10/7/1116, doi:10.1167/10.7.1116. [CrossRef]
Footnotes
 NIMH.
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