NEURAL-NETWORK MODEL OF THE CEREBELLUM - TEMPORAL DISCRIMINATION AND THE TIMING OF MOTOR-RESPONSES
NEURAL-NETWORK MODEL OF THE CEREBELLUM - TEMPORAL DISCRIMINATION AND THE TIMING OF MOTOR-RESPONSES
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DOI：
10.1162/neco.1994.6.1.38
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发表时间：
1994-01-01
影响因子：
2.9
通讯作者：
MAUK, MD
中科院分区：
文献类型：
--
作者：
BUONOMANO, DV;MAUK, MD
大量的证据表明，小脑在运动的产生中起着重要的作用。运动输出的一个重要方面是它与外部刺激或运动的其他组成部分相关的时间。以前的研究表明，小脑在运动的时间上起着重要作用。在这里，我们描述了一个基于小脑突触组织的神经网络模型，它可以产生几十毫秒到几秒范围内的定时响应。与以前的模型相比，时间编码出现在小脑电路的动力学，既不依赖于传导延迟，具有不同时间常数的元素阵列，也不依赖于以不同频率振荡的元素群体。相反，时间是从瞬时颗粒细胞群体向量中提取的。由于颗粒-高尔基体-颗粒细胞的负反馈，活性颗粒细胞的亚群是时变的。我们表明，模拟颗粒细胞活动的人口矢量表现出动态的，非周期性的轨迹响应于周期性的输入。以这种方式对时间进行编码，可以通过改变在目标时间窗口内活跃的颗粒细胞的颗粒->浦肯野细胞连接的强度，选择性地改变刺激开始后特定时间间隔内网络的输出。在该时间间隔的强化记忆随后表示为浦肯野细胞活性的变化，其相对于刺激开始适当定时。因此，本模型表明，基于小脑电路的网络可以通过将时间编码为颗粒细胞活动的群体向量来学习适当的定时响应。
Substantial evidence has established that the cerebellum plays an important role in the generation of movements. An important aspect of motor output is its timing in relation to external stimuli or to other components of a movement. Previous studies suggest that the cerebellum plays a role in the timing of movements. Here we describe a neural network model based on the synaptic organization of the cerebellum that can generate timed responses in the range of tens of milliseconds to seconds. In contrast to previous models, temporal coding emerges from the dynamics of the cerebellar circuitry and depends neither on conduction delays, arrays of elements with different time constants, nor populations of elements oscillating at different frequencies. Instead, time is extracted from the instantaneous granule cell population vector. The subset of active granule cells is time-varying due to the granule-Golgi-granule cell negative feedback. We demonstrate that the population vector of simulated granule cell activity exhibits dynamic, nonperiodic trajectories in response to a periodic input. With time encoded in this manner, the output of the network at a particular interval following the onset of a stimulus can be altered selectively by changing the strength of granule --> Purkinje cell connections for those granule cells that are active during the target time window. The memory of the reinforcement at that interval is subsequently expressed as a change in Purkinje cell activity that is appropriately timed with respect to stimulus onset. Thus, the present model demonstrates that a network based on cerebellar circuitry can learn appropriately timed responses by encoding time as the population vector of granule cell activity.