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      Local or Not Local: Investigating the Nature of Striatal Theta Oscillations in Behaving Rats

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          In the cortex and hippocampus, neuronal oscillations of different frequencies can be observed in local field potentials (LFPs). LFPs oscillations in the theta band (6–10 Hz) have also been observed in the dorsolateral striatum (DLS) of rodents, mostly during locomotion, and have been proposed to mediate behaviorally-relevant interactions between striatum and cortex (or between striatum and hippocampus). However, it is unclear if these theta oscillations are generated in the striatum. To address this issue, we recorded LFPs and spiking activity in the DLS of rats performing a running sequence on a motorized treadmill. We observed an increase in rhythmical activity of the LFP in the theta-band during run compared to rest periods. However, several observations suggest that these oscillations are mainly generated outside of the striatum. First, theta oscillations disappeared when LFPs were rereferenced against a striatal recording electrode and the imaginary coherence between LFPs recorded at different locations within the striatum was null. Second, 8% of the recorded neurons had their spiking activity phase-locked to the theta rhythm. Third, Granger causality analyses between LFPs simultaneously recorded in the cortex and the striatum revealed that the interdependence between these two signals in the theta range was mostly accounted for by a common external source. The most parsimonious interpretation of these results is that theta oscillations observed in striatal LFPs are largely contaminated by volume-conducted signals. We propose that striatal LFPs are not optimal proxies of network dynamics in the striatum and should be interpreted with caution.

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          Theta oscillations in the hippocampus.

          Theta oscillations represent the "on-line" state of the hippocampus. The extracellular currents underlying theta waves are generated mainly by the entorhinal input, CA3 (Schaffer) collaterals, and voltage-dependent Ca(2+) currents in pyramidal cell dendrites. The rhythm is believed to be critical for temporal coding/decoding of active neuronal ensembles and the modification of synaptic weights. Nevertheless, numerous critical issues regarding both the generation of theta oscillations and their functional significance remain challenges for future research.
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            Identifying true brain interaction from EEG data using the imaginary part of coherency.

            The main obstacle in interpreting EEG/MEG data in terms of brain connectivity is the fact that because of volume conduction, the activity of a single brain source can be observed in many channels. Here, we present an approach which is insensitive to false connectivity arising from volume conduction. We show that the (complex) coherency of non-interacting sources is necessarily real and, hence, the imaginary part of coherency provides an excellent candidate to study brain interactions. Although the usual magnitude and phase of coherency contain the same information as the real and imaginary parts, we argue that the Cartesian representation is far superior for studying brain interactions. The method is demonstrated for EEG measurements of voluntary finger movement. We found: (a) from 5 s before to movement onset a relatively weak interaction around 20 Hz between left and right motor areas where the contralateral side leads the ipsilateral side; and (b) approximately 2-4 s after movement, a stronger interaction also at 20 Hz in the opposite direction. It is possible to reliably detect brain interaction during movement from EEG data. The method allows unambiguous detection of brain interaction from rhythmic EEG/MEG data.
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              Measurement of Linear Dependence and Feedback between Multiple Time Series

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                Author and article information

                Journal
                eNeuro
                eNeuro
                eneuro
                eneuro
                eNeuro
                eNeuro
                Society for Neuroscience
                2373-2822
                1 September 2017
                13 September 2017
                Sep-Oct 2017
                : 4
                : 5
                : ENEURO.0128-17.2017
                Affiliations
                [1 ]Institut National de la Santé et de la Recherche Médicale, Unité 901 , Marseille 13009, France and
                [2 ]Aix-Marseille Université, Unité Mixte de Recherche S901 , Marseille 13009, France
                [3 ]Institut de Neurobiologie de la Méditerranée , Marseille 13009, France
                [4 ]Institut de Neurosciences de la Timone, Unité Mixte de Recherche 7289, Aix-Marseille Université, Centre National de la Recherche Scientifique , Marseille 13385, France
                Author notes

                The authors declare no competing financial interests.

                Author contributions: L.L., A.B., and D.R. designed research; L.L., P.R.-O., and M.T.J.P. performed research; L.L. analyzed data; L.L., A.B., and D.R. wrote the paper.

                This work was supported by the European Research Council (ERC-2013-CoG – 615699_NeuroKinematics; to D.R.), the Mexican Consejo Nacional de Ciencia y Tecnología (P.R.-O.), and a PhD fellowship from the French Ministère de l'Enseignement Superieur et de la Recherche (L.L.).

                [*]

                A.B. and D.R. shared last co-authorship.

                P. Rueda-Orozco’s present address: Instituto de Neurobiología, Universidad Nacional Autónoma de México, 76230 Querétaro, México.

                Correspondence should be addressed to either of the following: David Robbe, INMED/INSERM U901, Parc scientifique de Luminy, 163 route de Luminy, BP 13, 13273, Marseille cedex 09. E-mail: david.robbe@ 123456inserm.fr ; or Andrea Brovelli,  Institut de Neurosciences de la Timone, UMR 7289 CNRS, Aix Marseille University, Campus de Santé Timone, 27 Bd Jean Moulin, 13385 Marseille Cedex 05, France. E-mail: andrea.brovelli@ 123456univ-amu.fr .
                Author information
                http://orcid.org/0000-0002-9267-9641
                http://orcid.org/0000-0002-2801-803X
                http://orcid.org/0000-0002-5342-1330
                http://orcid.org/0000-0002-9450-0553
                Article
                eN-NWR-0128-17
                10.1523/ENEURO.0128-17.2017
                5616191
                28966971
                5b36bfbd-7e89-48d2-8d25-23156645ec41
                Copyright © 2017 Lalla et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.

                History
                : 12 April 2017
                : 12 August 2017
                : 15 August 2017
                Page count
                Figures: 7, Tables: 3, Equations: 0, References: 71, Pages: 14, Words: 9191
                Funding
                Funded by: ERC
                Award ID: ERC-2013-CoG - 615699
                Funded by: Ministère de l'enseignement supérieur et de la recherche
                Categories
                5
                5.1
                New Research
                Integrative Systems
                Custom metadata
                September/October 2017

                coherence,granger,lfp,rat,striatum,theta oscillation
                coherence, granger, lfp, rat, striatum, theta oscillation

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