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Abstract:
Despite significant progress in understanding functional parcellation of the primate prefrontal cortex (PFC) it is currently unknown whether an intrinsic mechanism could dynamically coordinate activity between these functionally specialized sub-regions. Such a mechanism could be reflected in spatially organized rhythmic activity that is macroscopically observed as complex, rhythmic spatio-temporal patterns. Here, we used multielectrode arrays (Utah arrays) and recorded neural activity from a large area (16mm2) of the macaque lateral PFC during anesthesia in order to explore spatio-temporal patterns in the default state of the prefrontal cortical network. We recorded local field potentials (LFP's) (1-200Hz) and found that the spatial coherence of oscillatory activity exhibited a distinctive peak in the "beta" (15-30 Hz) frequency range during resting state but also during visual stimulation with dynamic movie stimuli. We then used the Hilbert transform to obtain the analytic signal and evaluated the two-dimensional instantaneous phase maps. We observed consistent phase gradients in the "beta" frequency range that formed complex, dynamic patterns, suggesting propagation of oscillatory activity across the cortical surface. A graph cut algorithm based on a measure of phase shift invariant similarity was used to cluster these spatio-temporal patterns. Our analysis revealed a dominant travelling wave pattern in the "beta" band, propagating along the ventral-dorsal plane and replaced by less frequent, less dominant patterns both in the absence of visual stimulation (spontaneous activity) and during stimulation with movie clips. By estimating mutual information, we found that the amplitude of this wave conveyed sensory information during the presentation of several movies. Our data show that travelling wave phenomena are suggestive of highly coordinated activity in the PFC, a cortical area known to be involved in higher order sensory processing. These traveling waves of oscillatory neural activity are modulated by sensory input and could provide a functional substrate for coordinating activity across different subregions of the PFC. Finally, our approach enables the unsupervised analysis of the complex spatio-temporal neural dynamics in ongoing oscillatory signals, providing an analytical framework to understand cooperative mechanisms in spatially distributed neural populations.
