Literature DB >> 22225379

Sensory coding in oscillatory electroreceptors of paddlefish.

Alexander B Neiman1, David F Russell.   

Abstract

Coherence and information theoretic analyses were applied to quantitate the response properties and the encoding of time-varying stimuli in paddlefish electroreceptors (ERs), studied in vivo. External electrical stimuli were Gaussian noise waveforms of varied frequency band and strength, including naturalistic waveforms derived from zooplankton prey. Our coherence analyses elucidated the role of internal oscillations and transduction processes in shaping the 0.5-20 Hz best frequency tuning of these electroreceptors, to match the electrical signals emitted by zooplankton prey. Stimulus-response coherence fell off above approximately 20 Hz, apparently due to intrinsic limits of transduction, but was detectable up to 40-50 Hz. Aligned with this upper fall off was a narrow band of intense internal noise at ∼25 Hz, due to prominent membrane potential oscillations in cells of sensory epithelia, which caused a narrow deadband of external insensitivity. Using coherence analysis, we showed that more than 76% of naturalistic stimuli of weak strength, ∼1 μV∕cm, was linearly encoded into an afferent spike train, which transmitted information at a rate of ∼30 bits∕s. Stimulus transfer to afferent spike timing became essentially nonlinear as the stimulus strength was increased to induce bursting firing. Strong stimuli, as from nearby zooplankton prey, acted to synchronize the bursting responses of afferents, including across populations of electroreceptors, providing a plausible mechanism for reliable information transfer to higher-order neurons through noisy synapses.

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Year:  2011        PMID: 22225379      PMCID: PMC3258284          DOI: 10.1063/1.3669494

Source DB:  PubMed          Journal:  Chaos        ISSN: 1054-1500            Impact factor:   3.642


  54 in total

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  6 in total

1.  Synchronous spikes are necessary but not sufficient for a synchrony code in populations of spiking neurons.

Authors:  Jan Grewe; Alexandra Kruscha; Benjamin Lindner; Jan Benda
Journal:  Proc Natl Acad Sci U S A       Date:  2017-02-15       Impact factor: 11.205

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Journal:  Sci Rep       Date:  2018-05-29       Impact factor: 4.379

3.  Information filtering by coincidence detection of synchronous population output: analytical approaches to the coherence function of a two-stage neural system.

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4.  Peripheral sensory coding through oscillatory synchrony in weakly electric fish.

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5.  Characteristic effects of stochastic oscillatory forcing on neural firing: analytical theory and comparison to paddlefish electroreceptor data.

Authors:  Christoph Bauermeister; Tilo Schwalger; David F Russell; Alexander B Neiman; Benjamin Lindner
Journal:  PLoS Comput Biol       Date:  2013-08-15       Impact factor: 4.475

6.  Self-Consistent Scheme for Spike-Train Power Spectra in Heterogeneous Sparse Networks.

Authors:  Rodrigo F O Pena; Sebastian Vellmer; Davide Bernardi; Antonio C Roque; Benjamin Lindner
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  6 in total

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