Enhancing the Temporal Complexity of Distributed Brain Networks with Patterned Cerebellar Stimulation

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Enhancing the Temporal Complexity of Distributed Brain Networks with Patterned Cerebellar Stimulation

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Title: Enhancing the Temporal Complexity of Distributed Brain Networks with Patterned Cerebellar Stimulation
Author: Farzan, Faranak; Pascual-Leone, Alvaro; Schmahmann, Jeremy D.; Halko, Mark

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Citation: Farzan, Faranak, Alvaro Pascual-Leone, Jeremy D. Schmahmann, and Mark Halko. 2016. “Enhancing the Temporal Complexity of Distributed Brain Networks with Patterned Cerebellar Stimulation.” Scientific Reports 6 (1): 23599. doi:10.1038/srep23599. http://dx.doi.org/10.1038/srep23599.
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Abstract: Growing evidence suggests that sensory, motor, cognitive and affective processes map onto specific, distributed neural networks. Cerebellar subregions are part of these networks, but how the cerebellum is involved in this wide range of brain functions remains poorly understood. It is postulated that the cerebellum contributes a basic role in brain functions, helping to shape the complexity of brain temporal dynamics. We therefore hypothesized that stimulating cerebellar nodes integrated in different networks should have the same impact on the temporal complexity of cortical signals. In healthy humans, we applied intermittent theta burst stimulation (iTBS) to the vermis lobule VII or right lateral cerebellar Crus I/II, subregions that prominently couple to the dorsal-attention/fronto-parietal and default-mode networks, respectively. Cerebellar iTBS increased the complexity of brain signals across multiple time scales in a network-specific manner identified through electroencephalography (EEG). We also demonstrated a region-specific shift in power of cortical oscillations towards higher frequencies consistent with the natural frequencies of targeted cortical areas. Our findings provide a novel mechanism and evidence by which the cerebellum contributes to multiple brain functions: specific cerebellar subregions control the temporal dynamics of the networks they are engaged in.
Published Version: doi:10.1038/srep23599
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4806366/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:26318603
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