Plasticity of cerebellar Purkinje cells in behavioral training of body balance control.

Ray X Lee,Chiming Huang,Chen-Tung Yen,Meng-Li Tsai,Jian-Jia Huang

doi:10.3389/fnsys.2015.00113

Abstract

Neural responses to sensory inputs caused by self-generated movements (reafference) and external passive stimulation (exafference) differ in various brain regions. The ability to differentiate such sensory information can lead to movement execution with better accuracy. However, how sensory responses are adjusted in regard to this distinguishability during motor learning is still poorly understood. The cerebellum has been hypothesized to analyze the functional significance of sensory information during motor learning, and is thought to be a key region of reafference computation in the vestibular system. In this study, we investigated Purkinje cell (PC) spike trains as cerebellar cortical output when rats learned to balance on a suspended dowel. Rats progressively reduced the amplitude of body swing and made fewer foot slips during a 5-min balancing task. Both PC simple (SSs; 17 of 26) and complex spikes (CSs; 7 of 12) were found to code initially on the angle of the heads with respect to a fixed reference. Using periods with comparable degrees of movement, we found that such SS coding of information in most PCs (10 of 17) decreased rapidly during balance learning. In response to unexpected perturbations and under anesthesia, SS coding capability of these PCs recovered. By plotting SS and CS firing frequencies over 15-s time windows in double-logarithmic plots, a negative correlation between SS and CS was found in awake, but not anesthetized, rats. PCs with prominent SS coding attenuation during motor learning showed weaker SS-CS correlation. Hence, we demonstrate that neural plasticity for filtering out sensory reafference from active motion occurs in the cerebellar cortex in rats during balance learning. SS-CS interaction may contribute to this rapid plasticity as a form of receptive field plasticity in the cerebellar cortex between two receptive maps of sensory inputs from the external world and of efference copies from the will center for volitional movements.

Highlights

Physical activities involve both active and passive movements
Motor Learning Measured by Head-body Pitch Angle We started with a protocol for motor learning with the objective to challenge the rats in a task that was not part of their routine motor repertoire
We investigated neural plasticity of cerebellar information processing in rats by examining Purkinje cell (PC) spike trains as the rats performed a motor learning task

Summary

Introduction

Physical activities involve both active and passive movements. Maintenance of balance is such a process, requiring integration of sensory information resulting from gravity-induced passive movement and self-generated active movement. Proper behavior requires animals to distinguish and respond differently to the same type of sensory inputs when they have different origins (i.e., PC plasticity in balance control active or passive movement) (Angelaki and Cullen, 2008; Cullen, 2011; Rochefort et al, 2013), such as reducing abnormal behavior like “ghost orienting” without a particular purpose or a specific stimulus (Anderson et al, 2012) This differential neural processing is thought to involve computational processing of sensory signals from peripheral receptors and motor command signals from motor centers to sensory receiving areas. Considering the neural plasticity during reafference learning, differential adjustment of neuronal responses to the same peripheral sensory inputs due to different causes (i.e., active or passive motion), here called “intention-dependent plasticity” (IDP), is still not well understood

Methods

Results

Conclusion