Georgopoulos A P, Massey J T
Behav Brain Res. 1985 Nov-Dec;18(2):159-66. doi: 10.1016/0166-4328(85)90071-3.
We examined the directionality of static and dynamic motor effects on cell discharge recorded during arm movements in motor cortex and area 5. Movements of 8 directions were performed by rhesus monkeys in a two-dimensional space ('movement task'). Static effects were determined using a static hold task in the same workspace ('static task'); they were adequately described as planar activity surfaces in 78/124 (63%) and 63/105 (60%) of motor cortical and area 5 cells, respectively, that showed statistically significant changes in steady-state activity associated with holding in different positions. The frequency of discharge expected during the movement time on the basis of the static effect alone was calculated for every trial using the static plane equation and the movement path. The difference between this value and the discharge rate observed in the movement task during the same period of time was taken as an estimate of the contribution of non-static, i.e. dynamic factors. Thus static and dynamic tuning curves were generated. These curves were compared with respect to depth of tuning and spatial congruence. The former was estimated by taking the difference between the maximum and minimum of the curve, and the latter by measuring the correlation between the static and dynamic curves. We found the following. First, the dynamic tuning curves were more deeply tuned than the corresponding static ones, by 1.51 and 1.59 times in motor cortex and area 5, respectively. This result was statistically significant in both areas (paired t-test, P less than 0.001).(ABSTRACT TRUNCATED AT 250 WORDS)
我们研究了在运动皮层和5区记录的手臂运动过程中,静态和动态运动效应在细胞放电方面的方向性。恒河猴在二维空间中执行8个方向的运动(“运动任务”)。通过在相同工作空间中的静态保持任务(“静态任务”)来确定静态效应;在运动皮层和5区分别有78/124(63%)和63/105(60%)的细胞,其稳态活动与不同位置的保持相关且有统计学显著变化,这些细胞的静态效应被充分描述为平面活动表面。对于每个试验,使用静态平面方程和运动路径计算仅基于静态效应在运动时间内预期的放电频率。该值与在同一时间段的运动任务中观察到的放电率之间的差异被视为非静态即动态因素贡献的估计值。由此生成了静态和动态调谐曲线。比较了这些曲线在调谐深度和空间一致性方面的情况。前者通过取曲线最大值和最小值之间的差值来估计,后者通过测量静态和动态曲线之间的相关性来估计。我们发现以下情况。首先,动态调谐曲线比相应的静态调谐曲线调谐得更深,在运动皮层和5区分别深1.51倍和1.59倍。这一结果在两个区域均具有统计学显著性(配对t检验,P小于0.001)。(摘要截短至250字)