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Coupling between spiking activity and beta band spatio-temporal patterns in the macaque PFC

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Safavi,  S
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Panagiotaropoulos,  T
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Kapoor,  V
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Logothetis,  NK
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Besserve,  M
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Safavi, S., Panagiotaropoulos, T., Kapoor, V., Logothetis, N., & Besserve, M. (2013). Coupling between spiking activity and beta band spatio-temporal patterns in the macaque PFC. Poster presented at 43rd Annual Meeting of the Society for Neuroscience (Neuroscience 2013), San Diego, CA, USA.


Cite as: http://hdl.handle.net/21.11116/0000-0001-4E23-1
Abstract
Previous analysis of Local Field Potentials (LFPs) recorded from the inferior convexity of the macaque prefrontal cortex (PFC) revealed a dominant travelling wave pattern in the beta band (15-30 Hz) propagating along the ventral-dorsal plane. We hypothesized that propagating rhythmic activity reflects the intrinsic dynamics of the underlying neural populations which might be instrumental to information processing and sensory integration. Here, we investigated the relationship between multi-unit spiking activities (MUA) and LFPs in the same area of the PFC. We first computed spike-field coherence for each channel of the array. Many recording sites (typical example in Fig 1A) exhibited a distinctive peak in the beta frequency range both for resting state (spontaneous activity) and during visual stimulation with dynamic movie stimuli. We extracted the instantaneous phases in the beta band using Hilbert transform. We then computed the phase locking of spikes in each channel to a common LFP reference channel. The results exemplified on Fig 1 B, showed that many recording sites exhibited locking of spikes to the same phase of remote beta band LFP. This result was observed for many LFP reference channels, suggesting action potentials in all channels are synchronized to a common phenomenon. We used complex Singular Value Decomposition (SVD) of the spike-phase locking matrix to capture the dominant underlying spatio-temporal pattern of beta oscillations associated to spiking activity across the array. The dominant pattern estimated from the first eigen-mode of SVD exhibits a phase gradient along the ventral-dorsal plane (Fig 1 C), suggesting that MUA across the array are synchronized to the global travelling wave pattern previously observed along this direction in the LFP signal. This new result suggests MUA is synchronized to large scale ongoing travelling wave patterns in the beta band both during stimulation and spontaneous activity. Further information theoretic analysis will address how this mechanism serves distributed sensory encoding and processing in this area.