Kawato M, Gomi H
ATR Human Information Processing Research Laboratories, Kyoto, Japan.
Trends Neurosci. 1992 Nov;15(11):445-53. doi: 10.1016/0166-2236(92)90008-v.
Although one particular model of the cerebellum, as proposed by Marr and Albus, provides a formal framework for understanding how heterosynaptic plasticity of Purkinje cells might be used for motor learning, the physiological details remain largely an engima. Developments in computational neuroscience and artificial neural networks applied to real control problems are essential to understand fully how workspace errors associated with movement performances can be converted into motor-command errors, and how these errors can then be used as one kind of synaptic input by motor-learning algorithms that are based on biologically plausible rules involving heterosynaptic plasticity. These developments, as well as recent advances in the study of cellular mechanisms of synaptic plasticity, form the basis for the detailed computational models of cerebellar motor learning that have been proposed. These models provide hints toward resolving a long-standing controversy in the oculomotor literature regarding the sites of adaptive changes in the vestibuloocular reflex (VOR) and the optokinetic eye movement response (OKR), and suggest new experiments to elucidate general mechanisms of sensory motor learning.
尽管马尔和阿尔布斯提出的一种特定的小脑模型为理解浦肯野细胞的异突触可塑性如何用于运动学习提供了一个正式框架,但生理细节在很大程度上仍是一个谜。将计算神经科学和应用于实际控制问题的人工神经网络发展到能够完全理解与运动表现相关的工作空间误差如何转化为运动指令误差,以及这些误差如何随后被基于涉及异突触可塑性的生物学上合理规则的运动学习算法用作一种突触输入,这一点至关重要。这些发展以及突触可塑性细胞机制研究的最新进展,构成了已提出的小脑运动学习详细计算模型的基础。这些模型为解决眼动文献中关于前庭眼反射(VOR)和视动眼运动反应(OKR)适应性变化部位的长期争议提供了线索,并提出了新的实验来阐明感觉运动学习的一般机制。