Characterizing patches of primary visual cortex with minimal bias

The brain is highly complex, and studying it requires simplifying experiments, analyses, and theories. New techniques can capture more of the brain's complexity while reducing biases in our understanding of how it works. This thesis describes experiments in primary visual cortex of anesthetized cat, using high-density silicon multisite electrodes to simultaneously record from as many neurons as possible across all cortical layers, thereby characterizing local cortical populations with minimal bias. Recordings were maintained for many hours at a time, and included both spontaneous and stimulus-evoked periods, with a wide variety of naturalistic and artificial visual stimuli. A new "divide-and-conquer" spike sorting method translated correlated multisite voltages into action potentials of spatially localized, isolated neurons. This method tracked neurons over periods of many hours despite drift, and distinguished neurons with firing rates < 0.05 Hz. Neuron physiology was reasonably normal and mostly agreed with accepted principles of visual cortex, but there were exceptions. Surprisingly, firing rates across the population followed a lognormal distribution, and 82% of neurons had mean firing rates < 1 Hz. Also surprisingly, orientation tuning strength across the population was inversely correlated with log firing rate. Finally, there was evidence for neural shift work: over long durations, as some neurons became silent, others became active. To break down analyses by cell type, neurons were classified by their temporal spike shape and receptive field. Responses to repeated natural scene movie clips consisted of unique patterns of remarkably sparse, temporally precise (20 ms wide), reliable events. Mean pairwise correlations between neurons, as measured between trial-averaged responses to natural scene movies, were weakly positive. Correlations between simple and complex cells were lower — and between complex cells were higher — than expected, challenging the hierarchical model of complex cells. Cortical state was classified according to the local field potential, revealing greater natural scene movie response precision, sparseness, and reliability during the synchronized than desynchronized cortical state, contrary to reports in rodents. The open-ended, inclusive, high-dimensional experiments and analyses described here make few assumptions, potentially leading to more insightful theories of brain function than hypothesis-driven research alone.Medicine, Faculty ofGraduat