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Self-referential phase reset based on inferior olive oscillator dynamics.

机译:基于次优橄榄振荡器动力学的自参考相位重置。

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The olivo-cerebellar network is a key neuronal circuit that provides high-level motor control in the vertebrate CNS. Functionally, its network dynamics is organized around the oscillatory membrane potential properties of inferior olive (IO) neurons and their electrotonic connectivity. Because IO action potentials are generated at the peaks of the quasisinusoidal membrane potential oscillations, their temporal firing properties are defined by the IO rhythmicity. Excitatory inputs to these neurons can produce oscillatory phase shifts without modifying the amplitude or frequency of the oscillations, allowing well defined time-shift modulation of action potential generation. Moreover, the resulting phase is defined only by the amplitude and duration of the reset stimulus and is independent of the original oscillatory phase when the stimulus was delivered. This reset property, henceforth referred to as selfreferential phase reset, results in the generation of organized clusters of electrically coupled cellsthat oscillate in phase and are controlled by inhibitory feedback loops through the cerebellar nuclei and the cerebellar cortex. These clusters provide a dynamical representation of arbitrary motor intention patterns that are further mapped to the motor execution system. Being supplied with sensory inputs, the olivo-cerebellar network is capable of rearranging the clusters during the process of movement execution. Accordingly, the phase of the IO oscillators can be rapidly reset to a desired phase independently of the history of phase evolution. The goal of this article is to show how this selfreferential phase reset may be implemented into a motor control system by using a biologically based mathematical model.
机译:小脑小脑网络是关键的神经元回路,可在脊椎动物CNS中提供高级运动控制。在功能上,其网络动力学围绕下橄榄(IO)神经元的振动膜电位特性及其电渗连通性进行组织。由于IO动作电位是在准弦状膜电位振荡的峰值处产生的,因此它们的瞬时触发特性由IO节奏来定义。这些神经元的兴奋性输入可以产生振荡相移,而无需改变振荡的幅度或频率,从而可以很好地定义动作电位生成的时移调制。而且,所产生的相位仅由复位刺激的幅度和持续时间定义,并且与传递刺激时的原始振荡相位无关。此重置属性(此后称为自参考相重置)导致生成电耦合细胞的有组织簇,这些簇发生相位振荡,并受通过小脑核和小脑皮质的抑制性反馈回路的控制。这些集群提供了任意运动意图模式的动态表示,这些运动意图模式进一步映射到了运动执行系统。通过提供感觉输入,小脑小脑网络能够在运动执行过程中重新排列集群。因此,可以独立于相位演变的历史将IO振荡器的相位快速重置为期望的相位。本文的目的是说明如何通过使用基于生物学的数学模型将这种自参考相位重置实现到电机控制系统中。

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