Stephens Greg J, Neuenschwander Sergio, George John S, Singer Wolf, Kenyon Garrett T
Physics Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.
Biol Cybern. 2006 Oct;95(4):327-48. doi: 10.1007/s00422-006-0093-5. Epub 2006 Aug 9.
We show that coherent oscillations among neighboring ganglion cells in a retinal model encode global topological properties, such as size, that cannot be deduced unambiguously from their local, time-averaged firing rates. Whereas ganglion cells may fire similar numbers of spikes in response to both small and large spots, only large spots evoke coherent high frequency oscillations, potentially allowing downstream neurons to infer global stimulus properties from their local afferents. To determine whether such information might be extracted over physiologically realistic spatial and temporal scales, we analyzed artificial spike trains whose oscillatory correlations were similar to those measured experimentally. Oscillatory power in the upper gamma band, extracted on single-trials from multi-unit spike trains, supported good to excellent size discrimination between small and large spots, with performance improving as the number of cells and/or duration of the analysis window was increased. By using Poisson distributed spikes to normalize the firing rate across stimulus conditions, we further found that coincidence detection, or synchrony, yielded substantially poorer performance on identical size discrimination tasks. To determine whether size encoding depended on contiguity independent of object shape, we examined the total oscillatory activity across the entire model retina in response to random binary images. As the ON-pixel probability crossed the percolation threshold, which marks the sudden emergence of large connected clusters, the total gamma-band activity exhibited a sharp transition, a phenomena that may be experimentally observable. Finally, a reanalysis of previously published oscillatory responses from cat ganglion cells revealed size encoding consistent with that predicted by the retinal model.
我们表明，视网膜模型中相邻神经节细胞之间的相干振荡编码了全局拓扑特性，例如大小，这些特性无法从其局部时间平均放电率中明确推导出来。虽然神经节细胞可能对小斑点和大斑点产生相似数量的尖峰放电，但只有大斑点会引发相干高频振荡，这可能使下游神经元能够从其局部传入神经中推断全局刺激特性。为了确定这种信息是否可以在生理现实的空间和时间尺度上提取，我们分析了人工尖峰序列，其振荡相关性与实验测量的相似。从多单元尖峰序列的单次试验中提取的上伽马波段的振荡功率支持对小斑点和大斑点进行良好到出色的大小辨别，随着细胞数量和/或分析窗口持续时间的增加，性能会提高。通过使用泊松分布的尖峰来归一化不同刺激条件下的放电率，我们进一步发现，在相同的大小辨别任务中，符合检测或同步产生的性能要差得多。为了确定大小编码是否依赖于与物体形状无关的邻接性，我们检查了整个模型视网膜对随机二值图像的总振荡活动。当开像素概率超过渗流阈值时，该阈值标志着大连接簇的突然出现，总伽马波段活动呈现出急剧转变，这一现象可能在实验中观察到。最后，对先前发表的猫神经节细胞振荡反应的重新分析揭示了与视网膜模型预测一致的大小编码。
