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灵长类动物前庭眼反射运动学习的神经基础。III. 学习位点的计算与行为分析。

Neural basis for motor learning in the vestibuloocular reflex of primates. III. Computational and behavioral analysis of the sites of learning.

作者信息

Lisberger S G

机构信息

Department of Physiology, W. M. Keck Foundation Center for Integrative Neuroscience, University of California, San Francisco 94143.

出版信息

J Neurophysiol. 1994 Aug;72(2):974-98. doi: 10.1152/jn.1994.72.2.974.

DOI:10.1152/jn.1994.72.2.974
PMID:7983549
Abstract
  1. We have used a combination of eye movement recordings and computer modeling to study long-term adaptive modification (motor learning) in the vestibuloocular reflex (VOR). The eye movement recordings place constraints on possible sites for motor learning. The computer model abides by these constraints, as well as constraints provided by data in previous papers, to formalize a new hypothesis about the sites of motor learning. The model was designed to reproduce as much of the existing neural and behavioral data as possible. 2. Motor learning was induced in monkeys by fitting them with spectacles that caused the gain of the VOR (eye speed divided by head speed) to increase to values > 1.6 or to decrease to values < 0.4. We elicited pursuit by providing ramp motion of a small target at 30 degrees/s along the horizontal axis. Changes in the gain of the VOR caused only small and inconsistent changes in the eye acceleration in the first 100 ms after the onset of pursuit and had no effect on the eye velocity during tracking of steady target motion. Electrical stimulation in the flocculus and ventral paraflocculus with single pulses or trains of pulses caused smooth eye movement toward the side of stimulation after latencies of 9-11 ms. Neither the latency, the peak eye velocity, nor the initial eye acceleration varied as a consistent function of the gain of the VOR. 3. The computer model contained nodes that represented position-vestibular-pause cells (PVP-cells) and flocculus target neurons (FTNs) in the vestibular nucleus, and horizontal gaze-velocity Purkinje cells (HGVP-cells) in the cerebellar flocculus and ventral paraflocculus. Node FTN represented only the "E-c FTNs," which show increased firing for eye motion away from the side of recording. The transfer functions in the model included dynamic elements (filters) as well as static elements (summing junctions, gain elements, and time delays). Except for the transfer functions that converted visual motion inputs into commands for smooth eye movement, the model was linear. 4. The performance of the model was determined both by computer simulation and, for the VOR in the dark, by analytic solution of linear equations. For simulation, we adjusted the parameters by hand to match the output of the model to the eye velocity of monkeys and to match the activity of the relevant nodes in the model to the firing of HGVP-cells, FTNs, and PVP-cells when the gain of the VOR was 0.4, 1.0, and 1.6.(ABSTRACT TRUNCATED AT 400 WORDS)
摘要
  1. 我们结合眼动记录和计算机建模来研究前庭眼反射(VOR)中的长期适应性改变(运动学习)。眼动记录对运动学习的可能位点施加了限制。计算机模型遵循这些限制以及先前论文中的数据所提供的限制,以形成关于运动学习位点的新假设。该模型旨在尽可能多地重现现有的神经和行为数据。2. 通过给猴子佩戴眼镜来诱导运动学习,这些眼镜会使VOR的增益(眼速除以头速)增加到大于1.6的值或降低到小于0.4的值。我们通过沿水平轴以30度/秒的速度提供小目标的斜坡运动来引发追踪。在追踪开始后的前100毫秒内,VOR增益的变化仅引起眼加速度的微小且不一致的变化,并且在稳定目标运动的追踪过程中对眼速度没有影响。在绒球和腹侧旁绒球进行单脉冲或脉冲串的电刺激,在9 - 11毫秒的潜伏期后会引起眼球向刺激侧的平滑运动。潜伏期、峰值眼速度和初始眼加速度均不会随着VOR增益的变化而呈现一致的函数关系。3. 计算机模型包含代表前庭核中的位置 - 前庭 - 暂停细胞(PVP细胞)和绒球目标神经元(FTN),以及小脑绒球和腹侧旁绒球中的水平凝视速度浦肯野细胞(HGVP细胞)的节点。节点FTN仅代表“E - c FTN”,即当眼球向远离记录侧运动时放电增加的那些细胞。模型中的传递函数包括动态元件(滤波器)以及静态元件(求和节点、增益元件和时间延迟)。除了将视觉运动输入转换为平滑眼球运动指令的传递函数外,模型是线性的。4. 模型的性能通过计算机模拟以及对于黑暗中的VOR通过线性方程的解析解来确定。对于模拟,我们手动调整参数,以使模型的输出与猴子的眼速度相匹配,并使模型中相关节点的活动与VOR增益为0.4、1.0和1.6时HGVP细胞、FTN和PVP细胞的放电相匹配。(摘要截于400字)

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