Nicholas Swindale

Throughout most of the 20th century the brain has been studied as a reflexive system with ever improving recording methods being applied within a variety of sensory and behavioural paradigms.Yet the brains of most animals (and all mammals) are spontaneously active with incoming sensory stimuli modulating rather than driving neural activity.The aim of this thesis is to characterize spontaneous neural activity across multiple temporal and spatial scales relying on biophysical simulations, experiments and analysis of recordings from the visual cortex of cats and dorsal cortex and thalamus of mouse.Biophysically detailed simulations yielded novel datasets for testing spike sorting algorithms which are critical for isolating single neuron activity. Sorting algorithms tested provided low error rates with operator skill being as important as sorting suite. Simulated datasets have similar characteristics to in vivo acquired data and ongoing larger-scope efforts are proposed for developing the next generation of spike sorting algorithms and extracellular probes.Single neuron spontaneous activity was correlated to dorsal cortex neural activity in mice. Spike-triggered-maps revealed that spontaneously firing cortical neurons were co-activated with homotopic and mono-synaptically connected cortical areas, whereas thalamic neurons co-activatedwith more diversely connected areas. Both bursting and tonic firing modes yielded similar maps and the time courses of spike-triggered-maps revealed distinct patterns suggesting such dynamics may constitute intrinsic single neuron properties. The mapping technique extends previous work tofurther link spontaneous neural activity across temporal and spatial scales and suggests additional avenues of investigation.Synchronized state cat visual and mouse sensory cortex electrophysiological recordings revealed that spontaneously occurring activity UP-state transitions fall into stereotyped classes of events that can be grouped. Single visual cortex neurons active during UP-state transitions fire in a partially preserved order extending previous findings on high firing rate neurons in rat somatosensory and auditory cortex. The firing order for many neurons changes over periods longer than 30-minutes suggesting a complex non-stationary temporal neural code may underlie spontaneous and stimulusevoked neural activity.This thesis shows that ongoing spontaneous brain activity contains substantial structure that can be used to further our understanding of brain function.

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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.

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The brain is composed of many anatomically distinct areas that control different functions. Acommon feature of these areas is that information is represented in a spatially organized manner. Inthe visual system, retinal representation is spatially mapped onto visual areas such that neighboringneurons respond to adjacent retinal locations, forming a retinotopic map. When axons from tworetinas project to the same target structure, both produce similar retinotopic projections on thelarge scale but these segregate into eye-specific domains locally. How these spatial representationsare formed is not well understood. Experimental studies have shown that many mechanisms areinvolved.Several modeling studies have addressed how such organization arises, with most representingdifferent varying subsets of the mechanisms known to be present and showing how the particularrepresentation of mechanisms can produce the emergent properties of organization. This resultsin models producing similar outputs yet coming to different conclusions that often cannot be reconciled.By omitting behaviors that are present and likely to be involved in organization, suchas spiking neurons and the dynamics of axon and synapse growth and retraction, the models arepoorly constrained. This limits their explanatory and predictive scope regarding how organizationdevelops, and further limits their ability to examine how the different mechanisms interact.To more accurately analyze both how such organization develops and the interactions betweenunderlying mechanisms, a model of the developing retinocollicular pathway was produced thatrepresented a wide range of cellular and subcellular phenomena, including spike-timing dependentplasticity (STDP), chemoaffinity, spontaneous retinal activity, trophic factors, and growth andretraction of synapses and axons. The model demonstrated retinotopic refinement and eye-specificsegregation across a wide range of parameters and variations in implementation. Results indicatedthat the mechanisms necessary for organization were chemoaffinity, retinal waves, trophic factorsand homeostatic controls. Analysis of the relative roles of activity and chemoaffinity suggested thatthese mechanisms play distinct and complementary roles. Among the predictions of the model arethat smaller synapses produce more refined projections and, surprisingly, that STDP does not playa significant role in organization.

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