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Feedback inhibition controls spike transfer in hybrid thalamic circuits

Author

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  • Gwendal Le Masson

    (Institut François Magendie, Université Victor Segalen Bordeaux 2)

  • Sylvie Renaud-Le Masson

    (Laboratoire IXL, CNRS UMR 5818, ENSEIRB, Université de Bordeaux 1)

  • Damien Debay

    (Unité de Neurosciences Intégratives et Computationnelles, CNRS UPR 2191, Institut de Neurobiologie Alfred Fessard)

  • Thierry Bal

    (Unité de Neurosciences Intégratives et Computationnelles, CNRS UPR 2191, Institut de Neurobiologie Alfred Fessard)

Abstract

Sensory information reaches the cerebral cortex through the thalamus, which differentially relays this input depending on the state of arousal1,2,3,4,5. Such ‘gating’ involves inhibition of the thalamocortical relay neurons by the reticular nucleus of the thalamus6,7,8, but the underlying mechanisms are poorly understood. We reconstructed the thalamocortical circuit as an artificial and biological hybrid network in vitro. With visual input simulated as retinal cell activity, we show here that when the gain in the thalamic inhibitory feedback loop is greater than a critical value, the circuit tends towards oscillations—and thus imposes a temporal decorrelation of retinal cell input and thalamic relay output. This results in the functional disconnection of the cortex from the sensory drive, a feature typical of sleep states. Conversely, low gain in the feedback inhibition and the action of noradrenaline, a known modulator of arousal4,9,10, converge to increase input–output correlation in relay neurons. Combining gain control of feedback inhibition and modulation of membrane excitability thus enables thalamic circuits to finely tune the gating of spike transmission from sensory organs to the cortex.

Suggested Citation

  • Gwendal Le Masson & Sylvie Renaud-Le Masson & Damien Debay & Thierry Bal, 2002. "Feedback inhibition controls spike transfer in hybrid thalamic circuits," Nature, Nature, vol. 417(6891), pages 854-858, June.
  • Handle: RePEc:nat:nature:v:417:y:2002:i:6891:d:10.1038_nature00825
    DOI: 10.1038/nature00825
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    Cited by:

    1. Ling Li & Shasha Li & Wenhai Wang & Jielian Zhang & Yiming Sun & Qunrui Deng & Tao Zheng & Jianting Lu & Wei Gao & Mengmeng Yang & Hanyu Wang & Yuan Pan & Xueting Liu & Yani Yang & Jingbo Li & Nengjie, 2024. "Adaptative machine vision with microsecond-level accurate perception beyond human retina," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    2. Niklas Brake & Flavie Duc & Alexander Rokos & Francis Arseneau & Shiva Shahiri & Anmar Khadra & Gilles Plourde, 2024. "A neurophysiological basis for aperiodic EEG and the background spectral trend," Nature Communications, Nature, vol. 15(1), pages 1-15, December.

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