Literature DB >> 17925244

Neural strategies for optimal processing of sensory signals.

Leonard Maler1.   

Abstract

The electrosensory system is used for both spatial navigation tasks and communication. An electric organ generates a sinusoidal electric field and cutaneous electroreceptors respond to this field. Objects such as prey or rocks cause a local low-frequency modulation of the electric field; this cue is used by electric fish for navigation and prey capture. The interference of the electric fields of conspecifics produces beats, often with high frequencies, that are also sensed by the electroreceptors; furthermore, these electric fish can transiently modulate their electric discharge as a communication signal. Thus these fish must therefore detect a variety of low-intensity signals that differ greatly in their spatial extent, frequency, and duration. Behavioral studies suggest that they are highly adapted to these tasks. Experimental and theoretical analyses of the neural circuitry for the electrosense has demonstrated many commonalities with the more common senses, e.g., topographic mapping and receptive fields with On or Off centers and surround inhibition. The integration of computational and experimental analyses has demonstrated novel mechanisms that appear to optimize weak signal detection in the electrosense including: noise shaping by correlations within single spike trains, induction of oscillations by delayed feedback inhibition, the requirement for maps with differing receptive field sizes tuned for different stimulus parameters, and the role of non-plastic feedback for adaptive cancellation of redundant signals. It is likely that these mechanisms will also be operative in other sensory systems.

Mesh:

Year:  2007        PMID: 17925244     DOI: 10.1016/S0079-6123(06)65009-7

Source DB:  PubMed          Journal:  Prog Brain Res        ISSN: 0079-6123            Impact factor:   2.453


  8 in total

1.  Inhibition of SK and M channel-mediated currents by 5-HT enables parallel processing by bursts and isolated spikes.

Authors:  Tara Deemyad; Leonard Maler; Maurice J Chacron
Journal:  J Neurophysiol       Date:  2011-01-05       Impact factor: 2.714

2.  Chemosensory burst coding by mouse vomeronasal sensory neurons.

Authors:  Hannah A Arnson; Timothy E Holy
Journal:  J Neurophysiol       Date:  2011-04-27       Impact factor: 2.714

3.  Effect of inhibitory feedback on correlated firing of spiking neural network.

Authors:  Jinli Xie; Zhijie Wang
Journal:  Cogn Neurodyn       Date:  2013-01-09       Impact factor: 5.082

4.  Variable synaptic strengths controls the firing rate distribution in feedforward neural networks.

Authors:  Cheng Ly; Gary Marsat
Journal:  J Comput Neurosci       Date:  2017-11-10       Impact factor: 1.621

5.  Regulation of response properties and operating range of the AFD thermosensory neurons by cGMP signaling.

Authors:  Sara M Wasserman; Matthew Beverly; Harold W Bell; Piali Sengupta
Journal:  Curr Biol       Date:  2011-03-08       Impact factor: 10.834

6.  Differences in Sodium Channel Densities in the Apical Dendrites of Pyramidal Cells of the Electrosensory Lateral Line Lobe.

Authors:  Sree I Motipally; Kathryne M Allen; Daniel K Williamson; Gary Marsat
Journal:  Front Neural Circuits       Date:  2019-06-04       Impact factor: 3.492

7.  Learning contrast-invariant cancellation of redundant signals in neural systems.

Authors:  Jorge F Mejias; Gary Marsat; Kieran Bol; Leonard Maler; André Longtin
Journal:  PLoS Comput Biol       Date:  2013-09-12       Impact factor: 4.475

8.  Optimal dynamic coding by mixed-dimensionality neurons in the head-direction system of bats.

Authors:  Arseny Finkelstein; Nachum Ulanovsky; Misha Tsodyks; Johnatan Aljadeff
Journal:  Nat Commun       Date:  2018-09-04       Impact factor: 14.919

  8 in total

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