Literature DB >> 34035395

Synergistic population coding of natural communication stimuli by hindbrain electrosensory neurons.

Ziqi Wang1, Maurice J Chacron2.   

Abstract

Understanding how neural populations encode natural stimuli with complex spatiotemporal structure to give rise to perception remains a central problem in neuroscience. Here we investigated population coding of natural communication stimuli by hindbrain neurons within the electrosensory system of weakly electric fish Apteronotus leptorhynchus. Overall, we found that simultaneously recorded neural activities were correlated: signal but not noise correlations were variable depending on the stimulus waveform as well as the distance between neurons. Combining the neural activities using an equal-weight sum gave rise to discrimination performance between different stimulus waveforms that was limited by redundancy introduced by noise correlations. However, using an evolutionary algorithm to assign different weights to individual neurons before combining their activities (i.e., a weighted sum) gave rise to increased discrimination performance by revealing synergistic interactions between neural activities. Our results thus demonstrate that correlations between the neural activities of hindbrain electrosensory neurons can enhance information about the structure of natural communication stimuli that allow for reliable discrimination between different waveforms by downstream brain areas.

Entities:  

Year:  2021        PMID: 34035395     DOI: 10.1038/s41598-021-90413-1

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  74 in total

1.  Decorrelated neuronal firing in cortical microcircuits.

Authors:  Alexander S Ecker; Philipp Berens; Georgios A Keliris; Matthias Bethge; Nikos K Logothetis; Andreas S Tolias
Journal:  Science       Date:  2010-01-29       Impact factor: 47.728

Review 2.  Neural correlations, population coding and computation.

Authors:  Bruno B Averbeck; Peter E Latham; Alexandre Pouget
Journal:  Nat Rev Neurosci       Date:  2006-05       Impact factor: 34.870

3.  Effects of noise correlations on information encoding and decoding.

Authors:  Bruno B Averbeck; Daeyeol Lee
Journal:  J Neurophysiol       Date:  2006-03-22       Impact factor: 2.714

4.  The effect of correlated variability on the accuracy of a population code.

Authors:  L F Abbott; P Dayan
Journal:  Neural Comput       Date:  1999-01-01       Impact factor: 2.026

Review 5.  Measuring and interpreting neuronal correlations.

Authors:  Marlene R Cohen; Adam Kohn
Journal:  Nat Neurosci       Date:  2011-06-27       Impact factor: 24.884

Review 6.  Correlations and Neuronal Population Information.

Authors:  Adam Kohn; Ruben Coen-Cagli; Ingmar Kanitscheider; Alexandre Pouget
Journal:  Annu Rev Neurosci       Date:  2016-04-21       Impact factor: 12.449

7.  Relating the Structure of Noise Correlations in Macaque Primary Visual Cortex to Decoder Performance.

Authors:  Or P Mendels; Maoz Shamir
Journal:  Front Comput Neurosci       Date:  2018-03-05       Impact factor: 2.380

8.  The Nature of Shared Cortical Variability.

Authors:  I-Chun Lin; Michael Okun; Matteo Carandini; Kenneth D Harris
Journal:  Neuron       Date:  2015-07-23       Impact factor: 17.173

9.  Structures of Neural Correlation and How They Favor Coding.

Authors:  Felix Franke; Michele Fiscella; Maksim Sevelev; Botond Roska; Andreas Hierlemann; Rava Azeredo da Silveira
Journal:  Neuron       Date:  2016-01-20       Impact factor: 17.173

10.  Direction-Selective Circuits Shape Noise to Ensure a Precise Population Code.

Authors:  Eric Shea-Brown; Fred Rieke; Joel Zylberberg; Jon Cafaro; Maxwell H Turner
Journal:  Neuron       Date:  2016-01-20       Impact factor: 17.173

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