Cited by 93Neural dynamics and brain functionNeuroscience and Neuropharmacology ResearchMemory and Neural Mechanisms

Efficient “Communication through Coherence” Requires Oscillations Structured to Minimize Interference between Signals

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Akam, Thomas E., Kullmann, Dimitri M.·2012·PLoS Computational Biology

Abstract

The 'communication through coherence' (CTC) hypothesis proposes that selective communication among neural networks is achieved by coherence between firing rate oscillation in a sending region and gain modulation in a receiving region. Although this hypothesis has stimulated extensive work, it remains unclear whether the mechanism can in principle allow reliable and selective information transfer. Here we use a simple mathematical model to investigate how accurately coherent gain modulation can filter a population-coded target signal from task-irrelevant distracting inputs. We show that selective communication can indeed be achieved, although the structure of oscillatory activity in the target and distracting networks must satisfy certain previously unrecognized constraints. Firstly, the target input must be differentiated from distractors by the amplitude, phase or frequency of its oscillatory modulation. When distracting inputs oscillate incoherently in the same frequency band as the target, communication accuracy is severely degraded because of varying overlap between the firing rate oscillations of distracting inputs and the gain modulation in the receiving region. Secondly, the oscillatory modulation of the target input must be strong in order to achieve a high signal-to-noise ratio relative to stochastic spiking of individual neurons. Thus, whilst providing a quantitative demonstration of the power of coherent oscillatory gain modulation to flexibly control information flow, our results identify constraints imposed by the need to avoid interference between signals, and reveal a likely organizing principle for the structure of neural oscillations in the brain.

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  • Selective communication can be achieved through coherence between firing rate oscillation in the sending region and oscillatory gain modulation in the receiving region.

    “invoking the principle of ‘communication through coherence’—that selective communication can be achieved through coherence between firing rate oscillation in the sending region and oscillatory gain modulation in the receiving region [63,64].”
  • A CA1 network which has evolved a predisposition to oscillate at theta and gamma frequencies may enable more efficient processing of the phasic input it receives in vivo.

    “a CA1 network which has evolved a predisposition to oscillate at theta and gamma frequencies may enable more efficient processing of the phasic input it receives in vivo (Akam and Kullmann, 2012; Fries, 2015).”

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Authors
Akam, T. E., & Kullmann, D. M.
Affiliations
  • UCL Queen Square Institute of Neurology (GB)
  • Centre National de la Recherche Scientifique (FR)
Corresponding author
Akam, Thomas E.
Venue
PLoS Computational Biology
Published
2012-11-08
Volume
8
Issue
11
Pages
e1002760
ISSN
  • 1553-734X (ISSN-L)
  • 1553-7358
OpenAlex
W2033965963
Cited by
93
References
55
Citations by year
2026: 4 · 2025: 9 · 2024: 5 · 2023: 7 · 2022: 11 · 2021: 7 · 2020: 6 · 2019: 6 · 2018: 3 · 2017: 6 · 2016: 8 · 2015: 7 · 2014: 9 · 2013: 5
FWCI
3.44
Type
journal article
Language
en
Open access
Locations
  • PLoS Computational Biology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • UCL Discovery (University College London) (submittedVersion)
  • Figshare (submittedVersion, cc-by)
Funders
Wellcome Trust (095580)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
Keywords
neural oscillations, selective communication, population coding, distractor interference, signal-to-noise ratio, neural information transfer
MeSH terms
Animals, Brain, Cell Communication, Computer Simulation, Mammals, Models, Neurological, Nerve Net, Neurons, Computational Biology

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