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Higher order correlations in non-stationary visually evoked gamma oscillations
##manager.scheduler.building##: Edificio Santa Maria
##manager.scheduler.room##: Auditorio San Agustin
Date: 2019-07-10 12:00 PM – 03:45 PM
Last modified: 2019-06-14
Abstract
Collective activity of neurons could play an important role in the large-scale integration of brain and there is still no integral formulation of the laws that govern its dynamics. As collective activity responds to evoked stimuli, we study the spatiotemporal properties of visually-evoked neuronal responses using high density surface electrocorticography (ECoG) recordings sampling neuronal activity along an entire hemisphere of the mouse brain. We combine surface and laminar recordings in different cortical areas within and outside the visual system. We found that in time domain, responses evoked by identical visual stimuli vary dramatically between trials and across individuals. Yet, frequency-domain analysis showed a consistent visually evoked synchronous gamma band oscillation (30-50Hz), which is present in all mice and coherent across trials in the early phase (<250 msec) of the visual evoked potential. This coherent gamma oscillation organizes into standing, traveling and rotational waves observed over large swaths of the cortical surface. Under isoflurane anesthesia, gamma waves extend into the posterior parietal association and the somatosensory cortices. In contrast, under propofol anesthesia, the gamma waves decay quickly and fail to reliably extend outside of the visual cortex. Our findings suggest that a consistent aspect of neuronal response to a visual stimulus is a spatiotemporal gamma oscillation that can extend over large areas of the cortex. We have applied an information geometry approach to determine how large scale gamma oscillations emerge from local interactions between neighboring locations in the cortex. Our findings suggest that while both anesthetics render subjects unconscious, the mechanisms by which they create this behavioral state arise through different network interactions thought the cortex.