Effects of sensorimotor adaptation on confidence

Humans are able to adapt to large and sudden perturbations of sensory feedback. For example, after plunging one’s hand into the water to retrieve a shell there is an immediate mismatch between visual feedback and proprioceptively sensed location. Sensor-motor adaptation takes time, as anyone who has encountered an unexpected computer mouse sensitivity can attest. What sensory and motor-execution cues are used to determine confidence, and do the dynamics of confidence parallel those of ongoing sensorimotor adaptation? Participants made a slicing reach through a visual target with an unseen hand followed by a continuous judgment of confidence in the success of their reach. After the confidence response, visual feedback of hand position was shown at the same distance along the reach as the target. For the confidence judgment, participants adjusted the size of an arc centered on the target. Larger arcs reflected lower confidence. Points were awarded if the visual feedback was within the arc, and fewer points returned for larger arcs. This incentivized attentive reporting and minimizing feedback-target distance to maximize the score. A fixed, rotational perturbation (alternating clockwise/counterclockwise across blocks) was applied to the feedback on trials 20-70 within each 100-trial block. We used least-squares cross validation to compare four Bayesian-inference models of sensorimotor confidence adaptation based on prospective cues (e.g., knowledge of motor noise and past performance), retrospective cues (e.g., proprioceptive measurements), or both sources of information to maximize expected gain (i.e., an ideal observer) with additional parameters for learning and bias. All of the participants use proprioception when calculating sensorimotor confidence during motor adaptation. Most participants depended primarily on a recalibrated proprioceptive signal for confidence. Over repeated blocks of exposure to the perturbation, participants’ confidence recovered exponentially to pre-adaptation levels, but at a different rate than motor learning.

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Publication Details

Journal
Journal of Vision
Published
2024-09-15
DOI
https://doi.org/10.1167/jov.24.10.1121
Citations
1
Primary Topic
Motor Control and Adaptation
Type
article
Field-Weighted Citation Impact
0.34
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article

Effects of sensorimotor adaptation on confidence

Marissa E. Fassold, Michael S. Landy
1 citations
Journal of Vision
Motor Control and Adaptation
0.34
article

Effects of sensorimotor adaptation on confidence

Marissa E. Fassold, Michael S. Landy
article en
1 citations

Abstract

Humans are able to adapt to large and sudden perturbations of sensory feedback. For example, after plunging one’s hand into the water to retrieve a shell there is an immediate mismatch between visual feedback and proprioceptively sensed location. Sensor-motor adaptation takes time, as anyone who has encountered an unexpected computer mouse sensitivity can attest. What sensory and motor-execution cues are used to determine confidence, and do the dynamics of confidence parallel those of ongoing sensorimotor adaptation? Participants made a slicing reach through a visual target with an unseen hand followed by a continuous judgment of confidence in the success of their reach. After the confidence response, visual feedback of hand position was shown at the same distance along the reach as the target. For the confidence judgment, participants adjusted the size of an arc centered on the target. Larger arcs reflected lower confidence. Points were awarded if the visual feedback was within the arc, and fewer points returned for larger arcs. This incentivized attentive reporting and minimizing feedback-target distance to maximize the score. A fixed, rotational perturbation (alternating clockwise/counterclockwise across blocks) was applied to the feedback on trials 20-70 within each 100-trial block. We used least-squares cross validation to compare four Bayesian-inference models of sensorimotor confidence adaptation based on prospective cues (e.g., knowledge of motor noise and past performance), retrospective cues (e.g., proprioceptive measurements), or both sources of information to maximize expected gain (i.e., an ideal observer) with additional parameters for learning and bias. All of the participants use proprioception when calculating sensorimotor confidence during motor adaptation. Most participants depended primarily on a recalibrated proprioceptive signal for confidence. Over repeated blocks of exposure to the perturbation, participants’ confidence recovered exponentially to pre-adaptation levels, but at a different rate than motor learning.

Journal of VisionVol. 24(10)
New York University (US)
Openalex Percentile: Top 40%
Motor Control and Adaptation
0.34
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