Kjaer T W, Hertz J A, Richmond B J
Laboratory of Neuropsychology, National Institute of Mental Health, Bethesda, MD 20892, USA.
J Comput Neurosci. 1994 Jun;1(1-2):109-39. doi: 10.1007/BF00962721.
We have studied the encoding of spatial pattern information by complex cells in the primary visual cortex of awake monkeys. Three models for the conditional probabilities of different stimuli, given the neuronal response, were fit and compared using cross-validation. For our data, a feed-forward neural network proved to be the best of these models. The information carried by a cell about a stimulus set can be calculated from the estimated conditional probabilities. We performed a spatial spectroscopy of the encoding, examining how the transmitted information varies with both the average coarseness of the stimulus set and the coarseness differences within it. We find that each neuron encodes information about many features at multiple scales. Our data do not appear to allow a characterization of these variations in terms of the detection of simple single features such as oriented bars.
我们研究了清醒猴子初级视觉皮层中复杂细胞对空间模式信息的编码。针对给定神经元反应的不同刺激的条件概率，拟合了三种模型，并使用交叉验证进行比较。对于我们的数据，前馈神经网络被证明是这些模型中最佳的。细胞携带的关于刺激集的信息可以从估计的条件概率中计算出来。我们对编码进行了空间光谱分析，研究了传输的信息如何随刺激集的平均粗糙度及其内部的粗糙度差异而变化。我们发现每个神经元在多个尺度上编码关于许多特征的信息。我们的数据似乎不允许根据诸如定向条等简单单一特征的检测来描述这些变化。
