August 2010
Volume 10, Issue 7
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2010
Augmented Hebbian Learning Accounts for the Complex Pattern of Effects of Feedback in Perceptual Learning
Author Affiliations
  • Jiajuan Liu
    Laboratory of Brain Processes (LOBES), University of Southern California
  • Zhonglin Lu
    Laboratory of Brain Processes (LOBES), University of Southern California
  • Barbara Dosher
    Memory, Attention, and Perception Laboratory (MAPL), University of California, Irvine
Journal of Vision August 2010, Vol.10, 1115. doi:10.1167/10.7.1115
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to Subscribers Only
      Sign In or Create an Account ×
    • Get Citation

      Jiajuan Liu, Zhonglin Lu, Barbara Dosher; Augmented Hebbian Learning Accounts for the Complex Pattern of Effects of Feedback in Perceptual Learning. Journal of Vision 2010;10(7):1115. doi: 10.1167/10.7.1115.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

A complex pattern of empirical results on the role of feedback in perceptual learning has emerged: Whereas most perceptual learning studies employed trial-by-trial feedback, several studies documented significant perceptual learning with block, partial, or even no feedback, and no perceptual learning with false, random, manipulated block, and reversed feedback (Herzog & Fahle, 1997). Shibata et al (2009) showed that arbitrary block-feedback facilitated perceptual learning if it is more positive than the observer's actual performance. At high training accuracies, feedback is not necessary (Liu, Lu & Dosher, 2008), and significant learning was found in low training accuracy trials when they were mixed with high accuracy trials (Petrov, Dosher, & Lu, 2006; Liu, Lu & Dosher, 2009). We conducted a computational analysis of the complex pattern of empirical results on the role of feedback with the Augmented Hebbian Reweighting Model (AHRM; Petrov, Dosher & Lu, 2005), in which learning occurs exclusively through incremental Hebbian modification of the weights between representation units and the decision unit, by simulating existing feedback studies in the literature. The Hebbian learning algorithm incorporates external feedback, when present, simply as another input to the decision unit. Without feedback, the algorithm uses observer's internal response to update the weights. Block feedback was used to modify the weights of the bias unit in the model. The simulation results are both qualitatively and quantitatively consistent with the data reported in the literature. Augmented Hebbian Reweighting accounts for the complex pattern of results on the role of feedback in perceptual learning.

Liu, J. Lu, Z. Dosher, B. (2010). Augmented Hebbian Learning Accounts for the Complex Pattern of Effects of Feedback in Perceptual Learning [Abstract]. Journal of Vision, 10(7):1115, 1115a, http://www.journalofvision.org/content/10/7/1115, doi:10.1167/10.7.1115. [CrossRef]
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×