Published December 15, 2022 | Version v1
Dataset Open

The role of consciously timed movements in shaping and improving auditory timing

  • 1. University of California, Davis
  • 2. George Mason University

Description

Our subjective sense of time is intertwined with a plethora of perceptual, cognitive, and motor functions, and likewise, the brain is equipped to expertly filter, weight, and combine these signals for seamless interactions with a dynamic world. Until relatively recently, the literature on time perception has excluded the influence of motor activity, yet, it has been found that motor circuits in the brain are at the core of most timing functions. Several studies have now identified that concurrent movements exert robust effects on perceptual timing estimates, but critically, have not assessed how humans consciously judge the duration of their own movements. This creates a gap in our understanding of the mechanisms driving movement-related effects on sensory timing. We sought to address this gap by administering a sensorimotor timing task in which we explicitly compared the timing of isolated auditory tones and arm movements, or both simultaneously. We contextualized our findings within a Bayesian cue combination framework, in which separate sources of temporal information are weighted by their reliability and integrated into a unitary time estimate that is more precise than either unisensory estimate. Our results revealed differences in accuracy between auditory, movement, and combined trials, and crucially, that combined trials were the most accurately timed. Under the Bayesian framework, we found that participants' combined estimates were more precise than isolated estimates in a way that trended towards optimality, while being overall less optimal than the model's prediction. These findings elucidate previously unknown qualities of conscious motor timing and propose computational mechanisms that can describe how movements combine with perceptual signals to create unified, multimodal experiences of time.

Notes

The is file is in comma separated values (CSV) format, and can be imported into most data analysis software including R, Matlab, and JASP.

Funding provided by: National Institute of Mental Health
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000025
Award Number: F31MH128150

Funding provided by: National Science Foundation
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100008982
Award Number: 1849067

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