Vidne Michael, Ahmadian Yashar, Shlens Jonathon, Pillow Jonathan W, Kulkarni Jayant, Litke Alan M, Chichilnisky E J, Simoncelli Eero, Paninski Liam
Department of Applied Physics & Applied Mathematics, Center for Theoretical Neuroscience, Columbia University, New York, NY, USA.
J Comput Neurosci. 2012 Aug;33(1):97-121. doi: 10.1007/s10827-011-0376-2. Epub 2011 Dec 29.
Synchronized spontaneous firing among retinal ganglion cells (RGCs), on timescales faster than visual responses, has been reported in many studies. Two candidate mechanisms of synchronized firing include direct coupling and shared noisy inputs. In neighboring parasol cells of primate retina, which exhibit rapid synchronized firing that has been studied extensively, recent experimental work indicates that direct electrical or synaptic coupling is weak, but shared synaptic input in the absence of modulated stimuli is strong. However, previous modeling efforts have not accounted for this aspect of firing in the parasol cell population. Here we develop a new model that incorporates the effects of common noise, and apply it to analyze the light responses and synchronized firing of a large, densely-sampled network of over 250 simultaneously recorded parasol cells. We use a generalized linear model in which the spike rate in each cell is determined by the linear combination of the spatio-temporally filtered visual input, the temporally filtered prior spikes of that cell, and unobserved sources representing common noise. The model accurately captures the statistical structure of the spike trains and the encoding of the visual stimulus, without the direct coupling assumption present in previous modeling work. Finally, we examined the problem of decoding the visual stimulus from the spike train given the estimated parameters. The common-noise model produces Bayesian decoding performance as accurate as that of a model with direct coupling, but with significantly more robustness to spike timing perturbations.
许多研究报道，视网膜神经节细胞（RGCs）之间存在比视觉反应更快时间尺度上的同步自发放电。同步放电的两种候选机制包括直接耦合和共享噪声输入。在灵长类动物视网膜的相邻伞状细胞中，已对其快速同步放电进行了广泛研究，最近的实验工作表明，直接电耦合或突触耦合较弱，但在没有调制刺激的情况下共享突触输入较强。然而，先前的建模工作并未考虑伞状细胞群体放电的这一方面。在此，我们开发了一种纳入共同噪声影响的新模型，并将其应用于分析一个由超过250个同时记录的伞状细胞组成的大型、密集采样网络的光反应和同步放电。我们使用一种广义线性模型，其中每个细胞的放电率由时空滤波后的视觉输入、该细胞时间滤波后的先前放电以及代表共同噪声的未观察到的源的线性组合决定。该模型准确地捕捉了放电序列的统计结构和视觉刺激的编码，而无需先前建模工作中存在的直接耦合假设。最后，我们研究了在给定估计参数的情况下从放电序列解码视觉刺激的问题。共同噪声模型产生的贝叶斯解码性能与具有直接耦合的模型一样准确，但对放电时间扰动具有显著更高的鲁棒性。
