  Here we test our conceptual understanding of V1 function by asking two
experimental questions: 1) How do neurons respond to the spatiotemporal
structure contained in dynamic, natural scenes? and 2) What is the true range
of visual responsiveness and predictability of neural responses obtained in an
unbiased sample of neurons across all layers of cortex? We address these
questions by recording responses to natural movie stimuli with 32 channel
silicon probes. By simultaneously recording from cells in all layers, and
taking all recorded cells, we reduce recording bias that results from "hunting"
for neural responses evoked from drifting bars and gratings. A nonparametric
model reveals that many cells that are visually responsive do not appear to be
captured by standard receptive field models. Using nonlinear Radial Basis
Function kernels in a support vector machine, we can explain the responses of
some of these cells better than standard linear and phase-invariant complex
cell models. This suggests that V1 neurons exhibit more complex and diverse
responses than standard models can capture, ranging from simple and complex
cells strongly driven by their classical receptive fields, to cells with more
nonlinear receptive fields inferred from the nonparametric and RFB model, and
cells that are not visually responsive despite robust firing.
