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Frequency-specifc coupling in fronto-parieto-occipital cortical circuits underlie active tactile discrimination
Processing of tactile sensory information in rodents is critically dependent on the communication between the primary somatosensory cortex (S1) and higher-order integrative cortical areas. Here, we have simultaneously characterized single-unit activity and local field potential (LFP) dynamics in the...
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Published in: | Scientific reports 2019-03, Vol.9 (1), p.1-14 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
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Summary: | Processing of tactile sensory information in rodents is critically dependent on the communication between the primary somatosensory cortex (S1) and higher-order integrative cortical areas. Here, we have simultaneously characterized single-unit activity and local field potential (LFP) dynamics in the S1, primary visual cortex (V1), anterior cingulate cortex (ACC), posterior parietal cortex (PPC), while freely moving rats performed an active tactile discrimination task. Simultaneous single unit recordings from all these cortical regions revealed statistically significant neuronal firing rate modulations during all task phases (anticipatory, discrimination, response, and reward). Meanwhile, phase analysis of pairwise LFP recordings revealed the occurrence of long-range synchronization across the sampled fronto-parieto-occipital cortical areas during tactile sampling. Causal analysis of the same pairwise recorded LFPs demonstrated the occurrence of complex dynamic interactions between cortical areas throughout the fronto-parietal-occipital loop. These interactions changed significantly between cortical regions as a function of frequencies (i.e. beta, theta and gamma) and according to the different phases of the behavioral task. Overall, these findings indicate that active tactile discrimination by rats is characterized by much more widespread and dynamic complex interactions within the fronto-parieto-occipital cortex than previously anticipated.
This work was supported by the National Institutes of Science and Technology Program Brain Machine Interface (INCT INCEMAQ 610009/2009-5) of the National Council for Scientific and Technological Development (CNPq/MCTI), Rio Grande do Norte Research Foundation (FAPERN), Coordination for the Improvement of Higher Education Personnel (CAPES), Brazilian Innovation Agency (FINEP 01.06.1092.00), Ministry of Education (MEC), Santos Dumont Institute (ISD) and Alberto Santos Dumont Association for the Advancement of Science (AASDAP). |
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ISSN: | 2045-2322 |
DOI: | 10.1038/s41598-019-41516-3 |