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Neural Plasticity
Volume 2017 (2017), Article ID 3478742, 12 pages
https://doi.org/10.1155/2017/3478742
Research Article

The Impact of Feedback on the Different Time Courses of Multisensory Temporal Recalibration

1Medical Scientist Training Program, Vanderbilt University Medical School, Vanderbilt University, Nashville, TN 37235, USA
2Vanderbilt Brain Institute, Vanderbilt University Medical School, Vanderbilt University, Nashville, TN 37235, USA
3Neuroscience Graduate Program, Vanderbilt Brain Institute, Vanderbilt University Medical School, Vanderbilt University, Nashville, TN 37235, USA
4Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN 37235, USA
5Department of Psychology, Vanderbilt University, Nashville, TN 37235, USA
6Department of Psychiatry, Vanderbilt University Medical Center, Nashville, TN 37235, USA

Correspondence should be addressed to Matthew A. De Niear; ude.tlibrednav@raein.ed.a.wehttam

Received 26 October 2016; Revised 14 January 2017; Accepted 26 January 2017; Published 21 February 2017

Academic Editor: Zili Liu

Copyright © 2017 Matthew A. De Niear et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The capacity to rapidly adjust perceptual representations confers a fundamental advantage when confronted with a constantly changing world. Unexplored is how feedback regarding sensory judgments (top-down factors) interacts with sensory statistics (bottom-up factors) to drive long- and short-term recalibration of multisensory perceptual representations. Here, we examined the time course of both cumulative and rapid temporal perceptual recalibration for individuals completing an audiovisual simultaneity judgment task in which they were provided with varying degrees of feedback. We find that in the presence of feedback (as opposed to simple sensory exposure) temporal recalibration is more robust. Additionally, differential time courses are seen for cumulative and rapid recalibration dependent upon the nature of the feedback provided. Whereas cumulative recalibration effects relied more heavily on feedback that informs (i.e., negative feedback) rather than confirms (i.e., positive feedback) the judgment, rapid recalibration shows the opposite tendency. Furthermore, differential effects on rapid and cumulative recalibration were seen when the reliability of feedback was altered. Collectively, our findings illustrate that feedback signals promote and sustain audiovisual recalibration over the course of cumulative learning and enhance rapid trial-to-trial learning. Furthermore, given the differential effects seen for cumulative and rapid recalibration, these processes may function via distinct mechanisms.