Cell responsiveness in macaque superior temporal polysensory area measured by temporal discriminants.
Cell responsiveness in macaque superior temporal polysensory area measured by temporal discriminants.
复制标题
通过时间判别式测量猕猴上颞多感觉区的细胞反应性。
DOI：
10.1162/089976603322297296
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
Siegel,RM
中科院分区：
文献类型：
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作者：
Turner,JA;Anderson,KC;Siegel,RM
对来自两只猕猴的颞上多感觉区（STPa）的341个细胞的放电数据进行了三种不同的分析，以确定视觉光流模式反应的时间放电模式。这些数据是在猴子观看四种类型的光流并对显示器的变化做出反应时收集的。平均放电率（MFR）分析考虑刺激开始后500 ms内放电率的平均变化;判别（DIS）分析和主成分（PCA + DIS）分析考虑了刺激呈现后超过1000 ms的时间分组的放电率的变化，使用30至500 ms的bin大小。DIS分析使用逐步下降的判别分析来找到其中细胞的放电率可以区分刺激的时间窗口; PCA + DIS分析提取了细胞放电率的主成分，而不考虑刺激类型，然后对PCA分数应用逐步下降的判别分析，以确定是否有任何主成分可以区分刺激。这两个时间分析发现细胞敏感的光流的MFR分析错过了。一小部分细胞在时间分析中表现出多重选择性。因此，时间分析给出了由STPa神经元的放电特性编码的信息的更完整的表示。最后，这种方法结合了经典的统计技术的时间方法，以选择调谐神经元从人口中的一个公正的方式。
The firing-rate data from 341 cells from two macaques' superion temporal polysensory area (STPa) were subjected to three different analyses to determine the temporal firing-rate patterns in response to visual optic flow patterns. The data were collected while the monkey viewed four types of optic flow and responded to the change in the display. The mean firing rate (MFR) analysis considered the mean change in firing rate for 500 ms after stimulus onset; the discriminant (DIS) analysis and the principal components (PCA+DIS) analysis considered the change in time-binned firing rate over 1000 ms after stimulus presentation, using bin sizes of 30 to 500 ms. The DIS analysis used a step-down discriminant analysis to find temporal windows in which the cell's firing rate could discriminate among the stimuli; the PCA+DIS analysis extracted the principal components of the cell's firing rates without regard for the stimulus type and then applied a step-down discriminant analysis to the PCA scores to determine whether any of the principal components could discriminate among the stimuli. The two temporal analyses found cells sensitive to the optic flows that the MFR analysis missed. A small proportion of cells showed multiple selectivities under the temporal analyses. Thus, the temporal analyses give a more complete representation of the information encoded by the firing properties of STPa neurons. Finally, this approach incorporates temporal approaches with classical statistical techniques in order to select tuned neurons from a population in an unbiased manner.