Literature DB >> 22457454

Inferring the role of inhibition in auditory processing of complex natural stimuli.

Nadja Schinkel-Bielefeld1, Stephen V David, Shihab A Shamma, Daniel A Butts.   

Abstract

Intracellular studies have revealed the importance of cotuned excitatory and inhibitory inputs to neurons in auditory cortex, but typical spectrotemporal receptive field models of neuronal processing cannot account for this overlapping tuning. Here, we apply a new nonlinear modeling framework to extracellular data recorded from primary auditory cortex (A1) that enables us to explore how the interplay of excitation and inhibition contributes to the processing of complex natural sounds. The resulting description produces more accurate predictions of observed spike trains than the linear spectrotemporal model, and the properties of excitation and inhibition inferred by the model are furthermore consistent with previous intracellular observations. It can also describe several nonlinear properties of A1 that are not captured by linear models, including intensity tuning and selectivity to sound onsets and offsets. These results thus offer a broader picture of the computational role of excitation and inhibition in A1 and support the hypothesis that their interactions play an important role in the processing of natural auditory stimuli.

Mesh:

Year:  2012        PMID: 22457454      PMCID: PMC3378413          DOI: 10.1152/jn.01173.2011

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


  48 in total

1.  Predicting every spike: a model for the responses of visual neurons.

Authors:  J Keat; P Reinagel; R C Reid; M Meister
Journal:  Neuron       Date:  2001-06       Impact factor: 17.173

2.  Estimating spatio-temporal receptive fields of auditory and visual neurons from their responses to natural stimuli.

Authors:  F E Theunissen; S V David; N C Singh; A Hsu; W E Vinje; J L Gallant
Journal:  Network       Date:  2001-08       Impact factor: 1.273

3.  A simple white noise analysis of neuronal light responses.

Authors:  E J Chichilnisky
Journal:  Network       Date:  2001-05       Impact factor: 1.273

4.  Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex.

Authors:  Michael Wehr; Anthony M Zador
Journal:  Nature       Date:  2003-11-27       Impact factor: 49.962

5.  Linearity of cortical receptive fields measured with natural sounds.

Authors:  Christian K Machens; Michael S Wehr; Anthony M Zador
Journal:  J Neurosci       Date:  2004-02-04       Impact factor: 6.167

6.  Topography and synaptic shaping of direction selectivity in primary auditory cortex.

Authors:  Li I Zhang; Andrew Y Y Tan; Christoph E Schreiner; Michael M Merzenich
Journal:  Nature       Date:  2003-07-10       Impact factor: 49.962

7.  Excitatory and inhibitory intensity tuning in auditory cortex: evidence for multiple inhibitory mechanisms.

Authors:  M L Sutter; W C Loftus
Journal:  J Neurophysiol       Date:  2003-06-11       Impact factor: 2.714

8.  Analyzing neural responses to natural signals: maximally informative dimensions.

Authors:  Tatyana Sharpee; Nicole C Rust; William Bialek
Journal:  Neural Comput       Date:  2004-02       Impact factor: 2.026

9.  Excitatory and inhibitory response areas of auditory neurons in the cochlear nucleus.

Authors:  D D Greenwood; N Maruyama
Journal:  J Neurophysiol       Date:  1965-09       Impact factor: 2.714

10.  Organization of inhibitory frequency receptive fields in cat primary auditory cortex.

Authors:  M L Sutter; C E Schreiner; M McLean; K N O'connor; W C Loftus
Journal:  J Neurophysiol       Date:  1999-11       Impact factor: 2.714

View more
  17 in total

1.  Integration over multiple timescales in primary auditory cortex.

Authors:  Stephen V David; Shihab A Shamma
Journal:  J Neurosci       Date:  2013-12-04       Impact factor: 6.167

Review 2.  Neural encoding of sensory and behavioral complexity in the auditory cortex.

Authors:  Kishore Kuchibhotla; Brice Bathellier
Journal:  Curr Opin Neurobiol       Date:  2018-04-27       Impact factor: 6.627

3.  Online stimulus optimization rapidly reveals multidimensional selectivity in auditory cortical neurons.

Authors:  Anna R Chambers; Kenneth E Hancock; Kamal Sen; Daniel B Polley
Journal:  J Neurosci       Date:  2014-07-02       Impact factor: 6.167

Review 4.  Incorporating behavioral and sensory context into spectro-temporal models of auditory encoding.

Authors:  Stephen V David
Journal:  Hear Res       Date:  2017-12-31       Impact factor: 3.208

5.  Incorporating Midbrain Adaptation to Mean Sound Level Improves Models of Auditory Cortical Processing.

Authors:  Ben D B Willmore; Oliver Schoppe; Andrew J King; Jan W H Schnupp; Nicol S Harper
Journal:  J Neurosci       Date:  2016-01-13       Impact factor: 6.167

6.  Temporal asymmetries in auditory coding and perception reflect multi-layered nonlinearities.

Authors:  Thomas Deneux; Alexandre Kempf; Aurélie Daret; Emmanuel Ponsot; Brice Bathellier
Journal:  Nat Commun       Date:  2016-09-01       Impact factor: 14.919

7.  Inferring nonlinear neuronal computation based on physiologically plausible inputs.

Authors:  James M McFarland; Yuwei Cui; Daniel A Butts
Journal:  PLoS Comput Biol       Date:  2013-07-18       Impact factor: 4.475

Review 8.  Adaptive stimulus optimization for sensory systems neuroscience.

Authors:  Christopher DiMattina; Kechen Zhang
Journal:  Front Neural Circuits       Date:  2013-06-06       Impact factor: 3.492

9.  Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina.

Authors:  Jian K Liu; Tim Gollisch
Journal:  PLoS Comput Biol       Date:  2015-07-31       Impact factor: 4.475

10.  Input-Specific Gain Modulation by Local Sensory Context Shapes Cortical and Thalamic Responses to Complex Sounds.

Authors:  Ross S Williamson; Misha B Ahrens; Jennifer F Linden; Maneesh Sahani
Journal:  Neuron       Date:  2016-06-23       Impact factor: 17.173

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.