Statistical analysis of neural data: Classification-based approaches: spike-triggered averaging, spike-triggered covariance, and the linear-nonlinear cascade model
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Efficient and direct estimation of a neural subunit model for sensory coding
Many visual and auditory neurons have response properties that are well explained by pooling the rectified responses of a set of spatially shifted linear filters. These filters cannot be estimated using spike-triggered averaging (STA). Subspace methods such as spike-triggered covariance (STC) can recover multiple filters, but require substantial amounts of data, and recover an orthogonal basis ...
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تاریخ انتشار 2007