Changes in the responses of Purkinje cells in the floccular complex of monkeys after motor learning in smooth pursuit eye movements
Changes in the responses of Purkinje cells in the floccular complex of monkeys after motor learning in smooth pursuit eye movements
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DOI：
10.1152/jn.2000.84.6.2945
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发表时间：
2000-12-01
影响因子：
2.5
通讯作者：
Lisberger, SG
中科院分区：
文献类型：
--
作者：
Kahlon, M;Lisberger, SG
我们通过对两只猴子追逐眼球运动的学习修改，跟踪了小脑小脑小叶复合体中的浦肯野细胞(PC)的简单和复杂的棘波放电。学习是由目标速度的两个步长引起的，即最初静止的目标以“学习”速度移动100ms，然后在同一方向上改变为更高或更低的速度。在随机交叉对照实验中，目标以学习的速度朝相反的方向移动。当学习方向是简单棘波反应的ON方向时，32个PC中有10个的学习与简单棘波放电的统计显著变化有关。在表现出显著学习表现的10台电脑中，有8台显示出预期方向的简单棘波输出的变化：当眼球加速通过学习而增加或减少时，发射增加或减少。在控制方向的追逐过程中，简单尖峰反应或眼球加速在统计学上没有显著变化。当学习方向在单峰反应的偏离方向时，15个PC中没有一个与学习显著相关。尽管只有一小部分个人计算机记录到了简单放电的变化，但对群体反应的分析表明，学习前后群体放电与眼球加速之间的关系是相同的。因此，学习与使修改的总体反应适合于驱动改变的行为的改变相关联。为了分析学习过程中的复合棘波放电，我们将目标运动开始后的第二、第三和第四个100ms的复合棘波放电与之前100ms内的视网膜图像运动相关联。数据与之前的证据基本一致，即图像运动以与简单尖峰相反的方向选择性驱动复杂的尖峰。比较控制后不同时间的复杂棘波反应和学习目标在学习方向上的运动，发现复杂棘波可以在眼球加速减少而不是增加的过程中引导学习。学习导致复杂的棘波对图像运动的敏感度增加或降低，与眼球加速的变化平行。复杂尖峰反应在所有PC中都是相似的，包括许多学习不会改变简单尖峰反应的PC。我们的数据并不反驳当前的小脑学习理论，但建议这些理论必须加以修改，以解释这里报道的绒毛状浦肯野细胞的简单和复杂的棘波放电。
We followed simple- and complex-spike firing of Purkinje cells (PCs) in the floccular complex of the cerebellum through learned modifications of the pursuit eye movements of two monkeys. Learning was induced by double steps of target speed in which initially stationary targets move at a "learning" speed for 100 ms and then change to either a higher or lower speed in the same direction. In randomly interleaved control trials, targets moved at the learning speed in the opposite direction. When the learning direction was the ON direction for simple- spike responses, learning was associated with statistically significant changes in simple- spike firing for 10 of 32 PCs. Of the 10 PCs that showed significant expressions of learning, 8 showed changes in simple-spike output in the expected direction: increased or decreased firing when eye acceleration increased or decreased through learning. There were no statistically significant changes in simple- spike responses or eye acceleration during pursuit in the control direction. When the learning direction was in the OFF direction for simple- spike responses, none of 15 PCs showed significant correlates of learning. Although changes in simple-spike firing were recorded in only a subset of PCs, analysis of the population response showed that the same relationship between population firing and eye acceleration obtained before and after learning. Thus learning is associated with changes that render the modified population response appropriate to drive the changed behavior. To analyze complex-spike firing during learning we correlated complex-spike firing in the second, third, and fourth 100 ms after the onset of target motion with the retinal image motion in the previous 100 ms. Data were largely consistent with previous evidence that image motion drives complex spikes with a direction selectivity opposite that for simple spikes. Comparison of complex-spike responses at different times after the onset of control and learning target motions in the learning direction implied that complex spikes could guide learning during decreases but not increases in eye acceleration. Learning caused increases or decreases in the sensitivity of complex spikes to image motion in parallel with changes in eye acceleration. Complex-spike responses were similar in all PCs, including many in which learning did not modify simple- spike responses. Our data do not disprove current theories of cerebellar learning but suggest that these theories would have to be modified to account for simple- and complex-spike firing of floccular Purkinje cells reported here.