Literature DB >> 8890311

Logarithmic time course of sensory adaptation in electrosensory afferent nerve fibers in a weakly electric fish.

Z Xu1, J R Payne, M E Nelson.   

Abstract

1. We recorded single unit activity from individual primary electrosensory afferent axons in the posterior branch of the anterior lateral line nerve of gymnotid weakly electric fish, Apteronotus leptorhynchus. We analyzed the responses of P-type (probability-coding) afferent fibers to externally applied amplitude step changes in the quasi-sinusoidal transdermal potential established by the fish's own electric organ discharge (EOD). 2. In response to AM step increases in transdermal potential, the firing rate of P-type afferents exhibited an abrupt increase followed by an initially rapid and subsequently more gradual decay back toward the baseline level. Afferent responses continued to adapt slowly throughout the duration of prolonged step stimuli lasting > 100 s. The time course of sensory adaptation was similar for all units tested. 3. We introduce a new functional form for describing the time course of sensory adaptation in which the change in firing rate delta r decays logarithmically with time: delta r(t) = A/[B In (t) + 1]. This logarithmic form accurately describes the adaptation time course of P-type afferents over five decades in time, from milliseconds to hundreds of seconds, with only two free parameters. Using a nonlinear least-squares fitting technique, we obtained a mean value of the parameter B, which characterizes the adaptation time course, of 0.149 +/- 0.028 (mean +/- SD, n = 49). 4. We compare logarithmic fits with traditional multiexponential and power law forms and demonstrate that the logarithmic form yields a better characterization of P-type afferent responses. This analysis helps explain the variability in previously reported adaptation time constants, which have ranged from 0.2 to 3.4 s, in gymnotid P-type afferents. 5. We tested the linearity of P-type afferent responses using positive and negative AM steps of varying amplitudes. Aside from nonlinearities associated with rectification (firing rates cannot be negative) and saturation (firing rates cannot exceed the EOD frequency), we found that P-type afferent responses scaled linearly with stimulus amplitude. 6. Based on the observed linearity, we predict the frequency domain response characteristics of P-type afferents and find that the predicted gain and phase are in good agreement with experimental measurements using sinusoidal AM stimuli over a range of AM frequencies from 1 to 100 Hz. Thus the logarithmic parameterization of the step appears to accurately capture the response dynamics of P-type afferents over a wide range of behaviorally relevant AM frequencies. 7. We conclude that the temporal filtering properties of pyramidal cells in the medullary electrosensory nucleus, the electrosensory lateral line lobe (ELL), need to be reevaluated in light of the logarithmic adaptation time course in the periphery, and we discuss implications for the role of P-type afferents in driving a feedback gain control mechanism that regulated ELL pyramidal cell responsiveness.

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Year:  1996        PMID: 8890311     DOI: 10.1152/jn.1996.76.3.2020

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  26 in total

1.  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

2.  Nonrenewal statistics of electrosensory afferent spike trains: implications for the detection of weak sensory signals.

Authors:  R Ratnam; M E Nelson
Journal:  J Neurosci       Date:  2000-09-01       Impact factor: 6.167

3.  Type I burst excitability.

Authors:  Carlo R Laing; Brent Doiron; André Longtin; Liza Noonan; Ray W Turner; Leonard Maler
Journal:  J Comput Neurosci       Date:  2003 May-Jun       Impact factor: 1.621

4.  Continuous detection of weak sensory signals in afferent spike trains: the role of anti-correlated interspike intervals in detection performance.

Authors:  J B M Goense; R Ratnam
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2003-08-14       Impact factor: 1.836

5.  Comparison of coding capabilities of Type I and Type II neurons.

Authors:  Martin St-Hilaire; André Longtin
Journal:  J Comput Neurosci       Date:  2004 May-Jun       Impact factor: 1.621

6.  To burst or not to burst?

Authors:  Maurice J Chacron; André Longtin; Leonard Maler
Journal:  J Comput Neurosci       Date:  2004 Sep-Oct       Impact factor: 1.621

7.  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

8.  Neural adaptation facilitates oscillatory responses to static inputs in a recurrent network of ON and OFF cells.

Authors:  Jeremie Lefebvre; Andre Longtin; Victor G LeBlanc
Journal:  J Comput Neurosci       Date:  2010-12-18       Impact factor: 1.621

Review 9.  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

10.  Spike-frequency adaptation generates intensity invariance in a primary auditory interneuron.

Authors:  Jan Benda; R Matthias Hennig
Journal:  J Comput Neurosci       Date:  2007-05-30       Impact factor: 1.621

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