Literature DB >> 15806098

Electroreceptor neuron dynamics shape information transmission.

Maurice J Chacron1, Leonard Maler, Joseph Bastian.   

Abstract

The gymnotiform weakly electric fish Apteronotus leptorhynchus can capture prey using electrosensory cues that are dominated by low temporal frequencies. However, conventional tuning curves predict poor electroreceptor afferent responses to low-frequency stimuli. We compared conventional tuning curves with information tuning curves and found that the latter predicted substantially improved responses to these behaviorally relevant stimuli. Analysis of receptor afferent baseline activity showed that negative correlations reduced low-frequency noise levels, thereby increasing information transmission. Multiunit recordings from receptor afferents showed that this increased information transmission could persist at the population level. Finally, we verified that this increased low-frequency information is preserved in the spike trains of central neurons that receive receptor afferent input. Our results demonstrate that conventional tuning curves can be misleading when certain noise reduction strategies are used by the nervous system.

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Year:  2005        PMID: 15806098      PMCID: PMC5283878          DOI: 10.1038/nn1433

Source DB:  PubMed          Journal:  Nat Neurosci        ISSN: 1097-6256            Impact factor:   24.884


  33 in total

Review 1.  Information theory and neural coding.

Authors:  A Borst; F E Theunissen
Journal:  Nat Neurosci       Date:  1999-11       Impact factor: 24.884

2.  Negative interspike interval correlations increase the neuronal capacity for encoding time-dependent stimuli.

Authors:  M J Chacron; A Longtin; L Maler
Journal:  J Neurosci       Date:  2001-07-15       Impact factor: 6.167

3.  Spike-frequency adaptation of a generalized leaky integrate-and-fire model neuron.

Authors:  Y H Liu; X J Wang
Journal:  J Comput Neurosci       Date:  2001 Jan-Feb       Impact factor: 1.621

4.  Receptive field organization determines pyramidal cell stimulus-encoding capability and spatial stimulus selectivity.

Authors:  Joseph Bastian; Maurice J Chacron; Leonard Maler
Journal:  J Neurosci       Date:  2002-06-01       Impact factor: 6.167

5.  Attentional modulation of motion integration of individual neurons in the middle temporal visual area.

Authors:  Erik P Cook; John H R Maunsell
Journal:  J Neurosci       Date:  2004-09-08       Impact factor: 6.167

6.  High-frequency vibratory sensitive neurons in monkey primary somatosensory cortex: entrained and nonentrained responses to vibration during the performance of vibratory-cued hand movements.

Authors:  M A Lebedev; R J Nelson
Journal:  Exp Brain Res       Date:  1996-10       Impact factor: 1.972

7.  Multiple electrosensory maps in the medulla of weakly electric gymnotiform fish. I. Physiological differences.

Authors:  C A Shumway
Journal:  J Neurosci       Date:  1989-12       Impact factor: 6.167

8.  Receptive fields and functional architecture of monkey striate cortex.

Authors:  D H Hubel; T N Wiesel
Journal:  J Physiol       Date:  1968-03       Impact factor: 5.182

9.  A circuit for detection of interaural time differences in the brain stem of the barn owl.

Authors:  C E Carr; M Konishi
Journal:  J Neurosci       Date:  1990-10       Impact factor: 6.167

Review 10.  Is there chaos in the brain? II. Experimental evidence and related models.

Authors:  Henri Korn; Philippe Faure
Journal:  C R Biol       Date:  2003-09       Impact factor: 1.583

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  54 in total

1.  Sensory coding in oscillatory electroreceptors of paddlefish.

Authors:  Alexander B Neiman; David F Russell
Journal:  Chaos       Date:  2011-12       Impact factor: 3.642

2.  Parallel coding of first- and second-order stimulus attributes by midbrain electrosensory neurons.

Authors:  Patrick McGillivray; Katrin Vonderschen; Eric S Fortune; Maurice J Chacron
Journal:  J Neurosci       Date:  2012-04-18       Impact factor: 6.167

3.  Sparse and dense coding of natural stimuli by distinct midbrain neuron subpopulations in weakly electric fish.

Authors:  Katrin Vonderschen; Maurice J Chacron
Journal:  J Neurophysiol       Date:  2011-09-21       Impact factor: 2.714

4.  Sub- and suprathreshold adaptation currents have opposite effects on frequency tuning.

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Journal:  J Physiol       Date:  2012-06-25       Impact factor: 5.182

5.  Neural heterogeneities influence envelope and temporal coding at the sensory periphery.

Authors:  M Savard; R Krahe; M J Chacron
Journal:  Neuroscience       Date:  2010-10-28       Impact factor: 3.590

6.  Neural heterogeneities and stimulus properties affect burst coding in vivo.

Authors:  O Avila-Akerberg; R Krahe; M J Chacron
Journal:  Neuroscience       Date:  2010-03-15       Impact factor: 3.590

7.  Balanced ionotropic receptor dynamics support signal estimation via voltage-dependent membrane noise.

Authors:  Curtis M Marcoux; Stephen E Clarke; William H Nesse; Andre Longtin; Leonard Maler
Journal:  J Neurophysiol       Date:  2015-11-11       Impact factor: 2.714

Review 8.  Contrast coding in the electrosensory system: parallels with visual computation.

Authors:  Stephen E Clarke; André Longtin; Leonard Maler
Journal:  Nat Rev Neurosci       Date:  2015-11-12       Impact factor: 34.870

9.  Feedback and feedforward control of frequency tuning to naturalistic stimuli.

Authors:  Maurice J Chacron; Leonard Maler; Joseph Bastian
Journal:  J Neurosci       Date:  2005-06-08       Impact factor: 6.167

10.  Neural variability, detection thresholds, and information transmission in the vestibular system.

Authors:  Soroush G Sadeghi; Maurice J Chacron; Michael C Taylor; Kathleen E Cullen
Journal:  J Neurosci       Date:  2007-01-24       Impact factor: 6.167

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