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      Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG

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          Abstract

          Significance Subcortical structures play a critical role in brain functions such as sensory perception, memory, emotion, and consciousness. There are limited options for assessing neuronal dynamics within subcortical structures in humans. Magnetoencephalography and electroencephalography can measure electromagnetic fields generated by subcortical activity. But localizing the sources of these fields is very difficult, because the fields generated by subcortical structures are small and cannot be distinguished from distributed cortical activity. We show that cortical and subcortical fields can be distinguished if the cortical sources are sparse. We then describe an algorithm that uses sparsity in a hierarchical fashion to jointly localize cortical and subcortical sources. Our work offers alternative perspectives and tools for assessing subcortical brain dynamics in humans.

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          Most cited references66

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          Parallel organization of functionally segregated circuits linking basal ganglia and cortex.

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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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              CoSaMP: Iterative signal recovery from incomplete and inaccurate samples

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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proc Natl Acad Sci USA
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                November 28 2017
                November 28 2017
                November 28 2017
                November 14 2017
                : 114
                : 48
                : E10465-E10474
                Article
                10.1073/pnas.1705414114
                428a7917-a17d-4600-8dea-466226cb7c30
                © 2017

                Free to read

                http://www.pnas.org/site/misc/userlicense.xhtml

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