On-line processing of uncertain information in visuomotor control

Jun Izawa, Reza Shadmehr

Research output: Contribution to journalArticle

Abstract

Our sensory observations represent a delayed, noisy estimate of the environment. Delay causes instability and noise causes uncertainty. To deal with these problems, theory suggests that the processing of sensory information by the brain should be probabilistic: to start a movement or to alter it midflight, our brain should make predictions about the near future of sensory states and then continuously integrate the delayed sensory measures with predictions to form an estimate of the current state. To test the predictions of this theory, we asked participants to reach to the center of a blurry target. With increased uncertainty about the target, reach reaction times increased. Occasionally, we changed the position of the target or its blurriness during the reach. We found that the motor response to a given second target was influenced by the uncertainty about the first target. The specific trajectories of motor responses were consistent with predictions of a "minimum variance" state estimator. That is, the motor output that the brain programmed to start a reaching movement or correct it midflight was a continuous combination of two streams of information: a stream that predicted the near future of the state of the environment and a stream that provided a delayed measurement of that state.

Original languageEnglish (US)
Pages (from-to)11360-11368
Number of pages9
JournalJournal of Neuroscience
Volume28
Issue number44
DOIs
StatePublished - Oct 29 2008

Fingerprint

Automatic Data Processing
Uncertainty
Brain
Noise

Keywords

  • Autopilot
  • Computational model
  • Integration
  • Motor control
  • Reaction time
  • Uncertainty

ASJC Scopus subject areas

  • Neuroscience(all)
  • Medicine(all)

Cite this

On-line processing of uncertain information in visuomotor control. / Izawa, Jun; Shadmehr, Reza.

In: Journal of Neuroscience, Vol. 28, No. 44, 29.10.2008, p. 11360-11368.

Research output: Contribution to journalArticle

@article{95cac67033b1440e854f97440b52d944,
title = "On-line processing of uncertain information in visuomotor control",
abstract = "Our sensory observations represent a delayed, noisy estimate of the environment. Delay causes instability and noise causes uncertainty. To deal with these problems, theory suggests that the processing of sensory information by the brain should be probabilistic: to start a movement or to alter it midflight, our brain should make predictions about the near future of sensory states and then continuously integrate the delayed sensory measures with predictions to form an estimate of the current state. To test the predictions of this theory, we asked participants to reach to the center of a blurry target. With increased uncertainty about the target, reach reaction times increased. Occasionally, we changed the position of the target or its blurriness during the reach. We found that the motor response to a given second target was influenced by the uncertainty about the first target. The specific trajectories of motor responses were consistent with predictions of a {"}minimum variance{"} state estimator. That is, the motor output that the brain programmed to start a reaching movement or correct it midflight was a continuous combination of two streams of information: a stream that predicted the near future of the state of the environment and a stream that provided a delayed measurement of that state.",
keywords = "Autopilot, Computational model, Integration, Motor control, Reaction time, Uncertainty",
author = "Jun Izawa and Reza Shadmehr",
year = "2008",
month = "10",
day = "29",
doi = "10.1523/JNEUROSCI.3063-08.2008",
language = "English (US)",
volume = "28",
pages = "11360--11368",
journal = "Journal of Neuroscience",
issn = "0270-6474",
publisher = "Society for Neuroscience",
number = "44",

}

TY - JOUR

T1 - On-line processing of uncertain information in visuomotor control

AU - Izawa, Jun

AU - Shadmehr, Reza

PY - 2008/10/29

Y1 - 2008/10/29

N2 - Our sensory observations represent a delayed, noisy estimate of the environment. Delay causes instability and noise causes uncertainty. To deal with these problems, theory suggests that the processing of sensory information by the brain should be probabilistic: to start a movement or to alter it midflight, our brain should make predictions about the near future of sensory states and then continuously integrate the delayed sensory measures with predictions to form an estimate of the current state. To test the predictions of this theory, we asked participants to reach to the center of a blurry target. With increased uncertainty about the target, reach reaction times increased. Occasionally, we changed the position of the target or its blurriness during the reach. We found that the motor response to a given second target was influenced by the uncertainty about the first target. The specific trajectories of motor responses were consistent with predictions of a "minimum variance" state estimator. That is, the motor output that the brain programmed to start a reaching movement or correct it midflight was a continuous combination of two streams of information: a stream that predicted the near future of the state of the environment and a stream that provided a delayed measurement of that state.

AB - Our sensory observations represent a delayed, noisy estimate of the environment. Delay causes instability and noise causes uncertainty. To deal with these problems, theory suggests that the processing of sensory information by the brain should be probabilistic: to start a movement or to alter it midflight, our brain should make predictions about the near future of sensory states and then continuously integrate the delayed sensory measures with predictions to form an estimate of the current state. To test the predictions of this theory, we asked participants to reach to the center of a blurry target. With increased uncertainty about the target, reach reaction times increased. Occasionally, we changed the position of the target or its blurriness during the reach. We found that the motor response to a given second target was influenced by the uncertainty about the first target. The specific trajectories of motor responses were consistent with predictions of a "minimum variance" state estimator. That is, the motor output that the brain programmed to start a reaching movement or correct it midflight was a continuous combination of two streams of information: a stream that predicted the near future of the state of the environment and a stream that provided a delayed measurement of that state.

KW - Autopilot

KW - Computational model

KW - Integration

KW - Motor control

KW - Reaction time

KW - Uncertainty

UR - http://www.scopus.com/inward/record.url?scp=56149122057&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=56149122057&partnerID=8YFLogxK

U2 - 10.1523/JNEUROSCI.3063-08.2008

DO - 10.1523/JNEUROSCI.3063-08.2008

M3 - Article

C2 - 18971478

AN - SCOPUS:56149122057

VL - 28

SP - 11360

EP - 11368

JO - Journal of Neuroscience

JF - Journal of Neuroscience

SN - 0270-6474

IS - 44

ER -