Literature DB >> 22496294

Active sensing via movement shapes spatiotemporal patterns of sensory feedback.

Sarah A Stamper1, Eatai Roth, Noah J Cowan, Eric S Fortune.   

Abstract

Previous work has shown that animals alter their locomotor behavior to increase sensing volumes. However, an animal's own movement also determines the spatial and temporal dynamics of sensory feedback. Because each sensory modality has unique spatiotemporal properties, movement has differential and potentially independent effects on each sensory system. Here we show that weakly electric fish dramatically adjust their locomotor behavior in relation to changes of modality-specific information in a task in which increasing sensory volume is irrelevant. We varied sensory information during a refuge-tracking task by changing illumination (vision) and conductivity (electroreception). The gain between refuge movement stimuli and fish tracking responses was functionally identical across all sensory conditions. However, there was a significant increase in the tracking error in the dark (no visual cues). This was a result of spontaneous whole-body oscillations (0.1 to 1 Hz) produced by the fish. These movements were costly: in the dark, fish swam over three times further when tracking and produced more net positive mechanical work. The magnitudes of these oscillations increased as electrosensory salience was degraded via increases in conductivity. In addition, tail bending (1.5 to 2.35 Hz), which has been reported to enhance electrosensory perception, occurred only during trials in the dark. These data show that both categories of movements - whole-body oscillations and tail bends - actively shape the spatiotemporal dynamics of electrosensory feedback.

Mesh:

Year:  2012        PMID: 22496294     DOI: 10.1242/jeb.068007

Source DB:  PubMed          Journal:  J Exp Biol        ISSN: 0022-0949            Impact factor:   3.312


  16 in total

Review 1.  Adaptation of sensor morphology: an integrative view of perception from biologically inspired robotics perspective.

Authors:  Fumiya Iida; Surya G Nurzaman
Journal:  Interface Focus       Date:  2016-08-06       Impact factor: 3.906

2.  Active sensing associated with spatial learning reveals memory-based attention in an electric fish.

Authors:  James J Jun; André Longtin; Leonard Maler
Journal:  J Neurophysiol       Date:  2016-03-09       Impact factor: 2.714

3.  The Musculature That Drives Active Touch by Vibrissae and Nose in Mice.

Authors:  Sebastian Haidarliu; David Kleinfeld; Martin Deschênes; Ehud Ahissar
Journal:  Anat Rec (Hoboken)       Date:  2014-12-05       Impact factor: 2.064

4.  Motion parallax in electric sensing.

Authors:  Federico Pedraja; Volker Hofmann; Kathleen M Lucas; Colleen Young; Jacob Engelmann; John E Lewis
Journal:  Proc Natl Acad Sci U S A       Date:  2018-01-02       Impact factor: 11.205

5.  Dynamic modulation of visual and electrosensory gains for locomotor control.

Authors:  Erin E Sutton; Alican Demir; Sarah A Stamper; Eric S Fortune; Noah J Cowan
Journal:  J R Soc Interface       Date:  2016-05       Impact factor: 4.118

6.  Integration of visual and antennal mechanosensory feedback during head stabilization in hawkmoths.

Authors:  Payel Chatterjee; Agnish Dev Prusty; Umesh Mohan; Sanjay P Sane
Journal:  Elife       Date:  2022-06-27       Impact factor: 8.713

7.  Tuning movement for sensing in an uncertain world.

Authors:  Chen Chen; Todd D Murphey; Malcolm A MacIver
Journal:  Elife       Date:  2020-09-22       Impact factor: 8.140

8.  Electrosensory processing in Apteronotus albifrons: implications for general and specific neural coding strategies across wave-type weakly electric fish species.

Authors:  Diana Martinez; Michael G Metzen; Maurice J Chacron
Journal:  J Neurophysiol       Date:  2016-09-28       Impact factor: 2.714

9.  Active sensing system with in situ adjustable sensor morphology.

Authors:  Surya G Nurzaman; Utku Culha; Luzius Brodbeck; Liyu Wang; Fumiya Iida
Journal:  PLoS One       Date:  2013-12-26       Impact factor: 3.240

10.  Motor patterns during active electrosensory acquisition.

Authors:  Volker Hofmann; Bart R H Geurten; Juan I Sanguinetti-Scheck; Leonel Gómez-Sena; Jacob Engelmann
Journal:  Front Behav Neurosci       Date:  2014-05-28       Impact factor: 3.558

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