title: Dissociated multi-unit activity and local field potentials: a theory inspired analysis of a motor decision task.
abstract: Local field potentials (LFP) and multi-unit activity (MUA) recorded in vivo are known to convey different information about the underlying neural activity. Here we extend and support the idea that single-electrode LFP-MUA task-related modulations can shed light on the involved large-scale, multi-modular neural dynamics. We first illustrate a theoretical scheme and associated simulation evidence, proposing that in a multi-modular neural architecture local and distributed dynamic properties can be extracted from the local spiking activity of one pool of neurons in the network. From this new perspective, the spectral features of the field potentials reflect the time structure of the ongoing fluctuations of the probed local neuronal pool on a wide frequency range. We then report results obtained recording from the dorsal premotor (PMd) cortex of monkeys performing a countermanding task, in which a reaching movement is performed, unless a visual stop signal is presented. We find that the LFP and MUA spectral components on a wide frequency band (3-2000 Hz) are very differently modulated in time for successful reaching, successful and wrong stop trials, suggesting an interplay of local and distributed components of the underlying neural activity in different periods of the trials and for different behavioural outcomes. Besides, the MUA spectral power is shown to possess a time-dependent structure, which we suggest could help in understanding the successive involvement of different local neuronal populations. Finally, we compare signals recorded from PMd and dorso-lateral prefrontal (PFCd) cortex in the same experiment, and speculate that the comparative time-dependent spectral analysis of LFP and MUA can help reveal patterns of functional connectivity in the brain.
authors.affiliation: Department of Technologies and Health, Istituto Superiore di Sanità, I-00161 Roma, Italy. mattia@iss.infn.it
authors.forename: Maurizio
authors.initials: M
authors.lastname: Mattia
authors.forename: Stefano
authors.initials: S
authors.lastname: Ferraina
authors.forename: Paolo
authors.initials: P
authors.lastname: Del Giudice
mesh_terms: D000818:Animals; D001921:Brain / Q000502:physiology*; D000882:Haplorhini; D008564:Membrane Potentials / Q000502:physiology; D008959:Models, Neurological; D009043:Motor Activity / Q000502:physiology; D016571:Neural Networks, Computer; D009434:Neural Pathways / Q000502:physiology*; D009474:Neurons / Q000502:physiology