September 2018
Volume 18, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2018
Feature-based plasticity revealed by decoded fMRI neural feedback (DecNef)
Author Affiliations
  • Zhiyan Wang
    Brown University, Department of Cognitive, Linguistic and Psychological Sciences
  • Masako Tamaki
    Brown University, Department of Cognitive, Linguistic and Psychological Sciences
  • Kazuhisa Shibata
    Nagoya University, Graduate School of Informatics, Department of Psychology
  • Michael Worden
    Brown University, Department of Neuroscience
  • Yuka Sasaki
    Brown University, Department of Cognitive, Linguistic and Psychological Sciences
  • Takeo Watanabe
    Brown University, Department of Cognitive, Linguistic and Psychological Sciences
Journal of Vision September 2018, Vol.18, 759. doi:10.1167/18.10.759
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Zhiyan Wang, Masako Tamaki, Kazuhisa Shibata, Michael Worden, Yuka Sasaki, Takeo Watanabe; Feature-based plasticity revealed by decoded fMRI neural feedback (DecNef). Journal of Vision 2018;18(10):759. doi: 10.1167/18.10.759.

      Download citation file:


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

      ×
  • Supplements
Abstract

We have proposed the two-stage model in which visual perceptual learning (VPL) consists of feature-based plasticity resulting from passive exposure to a primitive feature in early visual areas and task-based plasticity resulting from task improvements involving higher-stage areas (Watanabe & Sasaki, 2014, Ann Rev Psych). Here we show evidence for feature-based plasticity: VPL of primitive features results from purely passive "exposure" to a motion display consisting of both primitive and complex features. We conducted an experiment consisting of the pre-test, decoder construction stage, DecNef training and post-test. In the decoder construction stage, we used a Sekuler motion display where we perceive local primitive motion directions and the global motion direction that is the spatio-temporal average of the local motion directions. We constructed a decoder that discriminated fMRI signals evoked by two Sekuler displays with different global motion directions. One of the two displays was chosen as a target in a double-blind manner. During DecNef training, activity patterns corresponding to the target display were repeatedly induced in V1/V2 without participants' awareness of what was being induced (see supplementary info for detailed methods). If the repetitive activations only induce VPL of the local motion directions range, this will be in accord with the hypothesis that feature-based plasticity occurs based on primitive features in a purely passive manner. If these activations induce both VPL of the local motion directions range and VPL of the global motion direction, this will be at odds with the above hypothesis. The training was conducted for 1.5 hrs a day over 3 days. In pre- and post-tests, detection tests were conducted with 16 motion directions. We found that motion detectability was improved only within the local motion directions range with no particular improvement on the global motion direction. That is, we could selectively induce feature-based plasticity.

Meeting abstract presented at VSS 2018

×
×

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.

×