High-dimensional neural spike train analysis with generalized count linear dynamical systems

NeurIPS 2015 Yuanjun GaoLars BusingKrishna V. ShenoyJohn P. Cunningham

Latent factor models have been widely used to analyze simultaneous recordings of spike trains from large, heterogeneous neural populations. These models assume the signal of interest in the population is a low-dimensional latent intensity that evolves over time, which is observed in high dimension via noisy point-process observations... (read more)

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