Literature DB >> 28592689

Control of the strength of visual-motor transmission as the mechanism of rapid adaptation of priors for Bayesian inference in smooth pursuit eye movements.

Timothy R Darlington1, Stefanie Tokiyama1, Stephen G Lisberger2.   

Abstract

Bayesian inference provides a cogent account of how the brain combines sensory information with "priors" based on past experience to guide many behaviors, including smooth pursuit eye movements. We now demonstrate very rapid adaptation of the pursuit system's priors for target direction and speed. We go on to leverage that adaptation to outline possible neural mechanisms that could cause pursuit to show features consistent with Bayesian inference. Adaptation of the prior causes changes in the eye speed and direction at the initiation of pursuit. The adaptation appears after a single trial and accumulates over repeated exposure to a given history of target speeds and directions. The influence of the priors depends on the reliability of visual motion signals: priors are more effective against the visual motion signals provided by low-contrast vs. high-contrast targets. Adaptation of the direction prior generalizes to eye speed and vice versa, suggesting that both priors could be controlled by a single neural mechanism. We conclude that the pursuit system can learn the statistics of visual motion rapidly and use those statistics to guide future behavior. Furthermore, a model that adjusts the gain of visual-motor transmission predicts the effects of recent experience on pursuit direction and speed, as well as the specifics of the generalization between the priors for speed and direction. We suggest that Bayesian inference in pursuit behavior is implemented by distinctly non-Bayesian internal mechanisms that use the smooth eye movement region of the frontal eye fields to control of the gain of visual-motor transmission.NEW & NOTEWORTHY Bayesian inference can account for the interaction between sensory data and past experience in many behaviors. Here, we show, using smooth pursuit eye movements, that the priors based on past experience can be adapted over a very short time frame. We also show that a single model based on direction-specific adaptation of the strength of visual-motor transmission can explain the implementation and adaptation of priors for both target direction and target speed.
Copyright © 2017 the American Physiological Society.

Entities:  

Keywords:  extrastriate area MT; frontal eye fields; gain control; monkeys; sensory-motor adaptation; smooth pursuit eye movements

Mesh:

Year:  2017        PMID: 28592689      PMCID: PMC5547260          DOI: 10.1152/jn.00282.2017

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  36 in total

1.  Regulation of the gain of visually guided smooth-pursuit eye movements by frontal cortex.

Authors:  M Tanaka; S G Lisberger
Journal:  Nature       Date:  2001-01-11       Impact factor: 49.962

2.  Bayesian integration in sensorimotor learning.

Authors:  Konrad P Körding; Daniel M Wolpert
Journal:  Nature       Date:  2004-01-15       Impact factor: 49.962

3.  Bayesian inference with probabilistic population codes.

Authors:  Wei Ji Ma; Jeffrey M Beck; Peter E Latham; Alexandre Pouget
Journal:  Nat Neurosci       Date:  2006-10-22       Impact factor: 24.884

4.  Directional organization of eye movement and visual signals in the floccular lobe of the monkey cerebellum.

Authors:  R J Krauzlis; S G Lisberger
Journal:  Exp Brain Res       Date:  1996-05       Impact factor: 1.972

5.  Ghosts in the machine: memory interference from the previous trial.

Authors:  Charalampos Papadimitriou; Afreen Ferdoash; Lawrence H Snyder
Journal:  J Neurophysiol       Date:  2014-11-05       Impact factor: 2.714

6.  The effect of expectations on slow oculomotor control. I. Periodic target steps.

Authors:  E Kowler; R M Steinman
Journal:  Vision Res       Date:  1979       Impact factor: 1.886

7.  Neural correlates of reliability-based cue weighting during multisensory integration.

Authors:  Christopher R Fetsch; Alexandre Pouget; Gregory C DeAngelis; Dora E Angelaki
Journal:  Nat Neurosci       Date:  2011-11-20       Impact factor: 24.884

8.  Initial tracking conditions modulate the gain of visuo-motor transmission for smooth pursuit eye movements in monkeys.

Authors:  J D Schwartz; S G Lisberger
Journal:  Vis Neurosci       Date:  1994 May-Jun       Impact factor: 3.241

9.  Do humans optimally integrate stereo and texture information for judgments of surface slant?

Authors:  David C Knill; Jeffrey A Saunders
Journal:  Vision Res       Date:  2003-11       Impact factor: 1.886

10.  The interaction of bayesian priors and sensory data and its neural circuit implementation in visually guided movement.

Authors:  Jin Yang; Joonyeol Lee; Stephen G Lisberger
Journal:  J Neurosci       Date:  2012-12-05       Impact factor: 6.167

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  9 in total

1.  Different mechanisms for modulation of the initiation and steady-state of smooth pursuit eye movements.

Authors:  Stuart Behling; Stephen G Lisberger
Journal:  J Neurophysiol       Date:  2020-02-19       Impact factor: 2.714

2.  Influence of prior and visual information on eye movements in amblyopic children.

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Journal:  J Comput Neurosci       Date:  2020-09-08       Impact factor: 1.621

3.  Disrupting Short-Term Memory Maintenance in Premotor Cortex Affects Serial Dependence in Visuomotor Integration.

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Journal:  J Neurosci       Date:  2021-10-04       Impact factor: 6.167

4.  Effect of Prior Direction Expectation on the Accuracy and Precision of Smooth Pursuit Eye Movements.

Authors:  Seolmin Kim; Jeongjun Park; Joonyeol Lee
Journal:  Front Syst Neurosci       Date:  2019-11-26

5.  Neural structure of a sensory decoder for motor control.

Authors:  Seth W Egger; Stephen G Lisberger
Journal:  Nat Commun       Date:  2022-04-05       Impact factor: 17.694

6.  Repeated applications of high potassium elicit long-term changes in a motor circuit from the crab, Cancer borealis.

Authors:  Mara C P Rue; Leandro M Alonso; Eve Marder
Journal:  iScience       Date:  2022-08-11

7.  Neural implementation of Bayesian inference in a sensorimotor behavior.

Authors:  Timothy R Darlington; Jeffrey M Beck; Stephen G Lisberger
Journal:  Nat Neurosci       Date:  2018-09-17       Impact factor: 24.884

8.  From Gaussian blobs to naturalistic videos: Comparison of oculomotor behavior across different stimulus complexities.

Authors:  Alexander Goettker; Ioannis Agtzidis; Doris I Braun; Michael Dorr; Karl R Gegenfurtner
Journal:  J Vis       Date:  2020-08-03       Impact factor: 2.240

9.  Retinal error signals and fluctuations in eye velocity influence oculomotor behavior in subsequent trials.

Authors:  Alexander Goettker
Journal:  J Vis       Date:  2021-05-03       Impact factor: 2.240

  9 in total

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