September 2021
Volume 21, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2021
Serial dependence and representational momentum in single-trial perceptual decisions
Author Affiliations & Notes
  • David Pascucci
    Ecole polytechnique fédérale de lausanne (EPFL)
  • Gijs Plomp
    University of Fribourg
  • Footnotes
    Acknowledgements  This research was supported by funding from the Swiss National Science Foundation (grant no. PP00P1_157420 to GP; grant no. PZ00P1_179988 to DP). The funders had no role in study design, data collection, and analysis.
Journal of Vision September 2021, Vol.21, 2198. doi:https://doi.org/10.1167/jov.21.9.2198
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      David Pascucci, Gijs Plomp; Serial dependence and representational momentum in single-trial perceptual decisions. Journal of Vision 2021;21(9):2198. https://doi.org/10.1167/jov.21.9.2198.

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

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Abstract

The human brain has evolved to predict and anticipate environmental events from their temporal dynamics. Predictions can bias perception toward the recent past, particularly when the environment contains no foreseeable changes, but can also push perception toward future states of sensory input, like when anticipating the trajectory of moving objects. Here, we show that perceptual decisions are simultaneously influenced by both past and future states of sensory signals. Using an orientation adjustment task, we demonstrate that single-trial errors are displaced toward previous features of behaviorally relevant stimuli and, at the same time, toward future states of dynamic sensory signals. These opposing tendencies, consistent with decisional serial dependence and representational momentum, involve different types of processing: serial dependence occurs beyond objecthood whereas representational momentum requires the representation of a single object with coherent dynamics in time and space. The coexistence of these two phenomena supports the independent binding of stimuli and decisions over time.

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