Literature DB >> 27170650

Dynamic modulation of visual and electrosensory gains for locomotor control.

Erin E Sutton1, Alican Demir2, Sarah A Stamper2, Eric S Fortune3, Noah J Cowan2.   

Abstract

Animal nervous systems resolve sensory conflict for the control of movement. For example, the glass knifefish, Eigenmannia virescens, relies on visual and electrosensory feedback as it swims to maintain position within a moving refuge. To study how signals from these two parallel sensory streams are used in refuge tracking, we constructed a novel augmented reality apparatus that enables the independent manipulation of visual and electrosensory cues to freely swimming fish (n = 5). We evaluated the linearity of multisensory integration, the change to the relative perceptual weights given to vision and electrosense in relation to sensory salience, and the effect of the magnitude of sensory conflict on sensorimotor gain. First, we found that tracking behaviour obeys superposition of the sensory inputs, suggesting linear sensorimotor integration. In addition, fish rely more on vision when electrosensory salience is reduced, suggesting that fish dynamically alter sensorimotor gains in a manner consistent with Bayesian integration. However, the magnitude of sensory conflict did not significantly affect sensorimotor gain. These studies lay the theoretical and experimental groundwork for future work investigating multisensory control of locomotion.
© 2016 The Author(s).

Entities:  

Keywords:  feedback control; locomotion; multisensory integration; sensory conflict; system identification; weakly electric fish

Mesh:

Year:  2016        PMID: 27170650      PMCID: PMC4892261          DOI: 10.1098/rsif.2016.0057

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  33 in total

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Authors:  Mark A Frye; Michael H Dickinson
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2.  Sensory uncertainty governs the extent of audio-visual interaction.

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Review 3.  Multisensory integration: current issues from the perspective of the single neuron.

Authors:  Barry E Stein; Terrence R Stanford
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4.  A Bayesian framework for active artificial perception.

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Review 5.  Feedback control as a framework for understanding tradeoffs in biology.

Authors:  Noah J Cowan; Mert M Ankarali; Jonathan P Dyhr; Manu S Madhav; Eatai Roth; Shahin Sefati; Simon Sponberg; Sarah A Stamper; Eric S Fortune; Thomas L Daniel
Journal:  Integr Comp Biol       Date:  2014-06-03       Impact factor: 3.326

6.  Aging and postural control: postural perturbations caused by changing the visual anchor.

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7.  Mutually opposing forces during locomotion can eliminate the tradeoff between maneuverability and stability.

Authors:  Shahin Sefati; Izaak D Neveln; Eatai Roth; Terence R T Mitchell; James B Snyder; Malcolm A Maciver; Eric S Fortune; Noah J Cowan
Journal:  Proc Natl Acad Sci U S A       Date:  2013-11-04       Impact factor: 11.205

8.  Context-dependent olfactory enhancement of optomotor flight control in Drosophila.

Authors:  Dawnis M Chow; Mark A Frye
Journal:  J Exp Biol       Date:  2008-08       Impact factor: 3.312

9.  Vision-based flight control in the hawkmoth Hyles lineata.

Authors:  Shane P Windsor; Richard J Bomphrey; Graham K Taylor
Journal:  J R Soc Interface       Date:  2013-12-11       Impact factor: 4.118

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Authors:  Jayne M Gardiner; Jelle Atema; Robert E Hueter; Philip J Motta
Journal:  PLoS One       Date:  2014-04-02       Impact factor: 3.240

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  5 in total

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4.  The Dome: A virtual reality apparatus for freely locomoting rodents.

Authors:  Manu S Madhav; Ravikrishnan P Jayakumar; Shahin G Lashkari; Francesco Savelli; Hugh T Blair; James J Knierim; Noah J Cowan
Journal:  J Neurosci Methods       Date:  2021-08-26       Impact factor: 2.987

5.  Electrosensory capture during multisensory discrimination of nearby objects in the weakly electric fish Gnathonemus petersii.

Authors:  Sarah Schumacher; Theresa Burt de Perera; Gerhard von der Emde
Journal:  Sci Rep       Date:  2017-03-03       Impact factor: 4.379

  5 in total

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