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Multidimensional population activity in an electrically coupled inhibitory circuit in the cerebellar cortex.
Gurnani, Harsha; Silver, R Angus.
Afiliación
  • Gurnani H; Department of Neuroscience, Physiology, and Pharmacology, University College London, London WC1E 6BT, UK.
  • Silver RA; Department of Neuroscience, Physiology, and Pharmacology, University College London, London WC1E 6BT, UK. Electronic address: a.silver@ucl.ac.uk.
Neuron ; 109(10): 1739-1753.e8, 2021 05 19.
Article en En | MEDLINE | ID: mdl-33848473
ABSTRACT
Inhibitory neurons orchestrate the activity of excitatory neurons and play key roles in circuit function. Although individual interneurons have been studied extensively, little is known about their properties at the population level. Using random-access 3D two-photon microscopy, we imaged local populations of cerebellar Golgi cells (GoCs), which deliver inhibition to granule cells. We show that population activity is organized into multiple modes during spontaneous behaviors. A slow, network-wide common modulation of GoC activity correlates with the level of whisking and locomotion, while faster (<1 s) differential population activity, arising from spatially mixed heterogeneous GoC responses, encodes more precise information. A biologically detailed GoC circuit model reproduced the common population mode and the dimensionality observed experimentally, but these properties disappeared when electrical coupling was removed. Our results establish that local GoC circuits exhibit multidimensional activity patterns that could be used for inhibition-mediated adaptive gain control and spatiotemporal patterning of downstream granule cells.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Células de Golgi Cerebelosas / Inhibición Neural Idioma: En Revista: Neuron Asunto de la revista: NEUROLOGIA Año: 2021 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Células de Golgi Cerebelosas / Inhibición Neural Idioma: En Revista: Neuron Asunto de la revista: NEUROLOGIA Año: 2021 Tipo del documento: Article