4.7 Review

Accounting for uncertainty: inhibition for neural inference in the cerebellum

Journal

Publisher

ROYAL SOC
DOI: 10.1098/rspb.2021.0276

Keywords

neural computation; neural networks; state estimation; granule cell layer; sensorimotor

Funding

  1. Wellcome Trust Neural Dynamics PhD studentship
  2. Wellcome Trust Investigator Award

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The review discusses the possible contribution of inhibition to the encoding of precision of neural representations in the granular layer of the cerebellar cortex, emphasizing the critical role of Golgi cells in shaping information transmission downstream to Purkinje cells.
Sensorimotor coordination is thought to rely on cerebellar-based internal models for state estimation, but the underlying neural mechanisms and specific contribution of the cerebellar components is unknown. A central aspect of any inferential process is the representation of uncertainty or conversely precision characterizing the ensuing estimates. Here, we discuss the possible contribution of inhibition to the encoding of precision of neural representations in the granular layer of the cerebellar cortex. Within this layer, Golgi cells influence excitatory granule cells, and their action is critical in shaping information transmission downstream to Purkinje cells. In this review, we equate the ensuing excitation-inhibition balance in the granular layer with the outcome of a precision-weighted inferential process, and highlight the physiological characteristics of Golgi cell inhibition that are consistent with such computations.

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