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考虑不确定性:小脑神经推理中的抑制作用。

Accounting for uncertainty: inhibition for neural inference in the cerebellum.

作者信息

Palacios Ensor Rafael, Houghton Conor, Chadderton Paul

机构信息

School of Physiology Pharmachology and Neuroscience, University of Bristol, Bristol BS8 1TH, UK.

School of Computer Science, University of Bristol, Bristol BS8 1UB, UK.

出版信息

Proc Biol Sci. 2021 Mar 31;288(1947):20210276. doi: 10.1098/rspb.2021.0276. Epub 2021 Mar 24.

Abstract

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.

摘要

感觉运动协调被认为依赖于基于小脑的内部模型进行状态估计,但其潜在的神经机制以及小脑各组成部分的具体贡献尚不清楚。任何推理过程的一个核心方面是不确定性的表征,或者相反,是表征后续估计的精度。在这里,我们讨论抑制作用对小脑皮质颗粒层神经表征精度编码的可能贡献。在这一层内,高尔基细胞影响兴奋性颗粒细胞,它们的作用对于塑造向下游浦肯野细胞的信息传递至关重要。在这篇综述中,我们将颗粒层中随之产生的兴奋-抑制平衡等同于精度加权推理过程的结果,并强调与这种计算一致的高尔基细胞抑制的生理特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a801/8059656/30542a6361e9/rspb20210276f01.jpg

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