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dc.contributor.authorWilson, Nathan
dc.contributor.authorWang, Forea L.
dc.contributor.authorChen, Naiyan
dc.contributor.authorYan, Sherry X.
dc.contributor.authorDaitch, Amy L.
dc.contributor.authorShi, Bo
dc.contributor.authorSharma, Samvaran
dc.contributor.authorSur, Mriganka
dc.date.accessioned2022-01-12T20:40:28Z
dc.date.available2022-01-12T18:53:55Z
dc.date.available2022-01-12T20:40:28Z
dc.date.issued2022-01-05
dc.identifier.issn1662-5110
dc.identifier.urihttps://hdl.handle.net/1721.1/138900.2
dc.description.abstractHere we demonstrate a facile method by which to deliver complex spatiotemporal stimulation to neural networks in fast patterns, to trigger interesting forms of circuit-level plasticity in cortical areas. We present a complete platform by which patterns of electricity can be arbitrarily defined and distributed across a brain circuit, either simultaneously, asynchronously, or in complex patterns that can be easily designed and orchestrated with precise timing. Interfacing with acute slices of mouse cortex, we show that our system can be used to activate neurons at many locations and drive synaptic transmission in distributed patterns, and that this elicits new forms of plasticity that may not be observable via traditional methods, including interesting measurements of associational and sequence plasticity. Finally, we introduce an automated “network assay” for imaging activation and plasticity across a circuit. Spatiotemporal stimulation opens the door for high-throughput explorations of plasticity at the circuit level, and may provide a basis for new types of adaptive neural prosthetics.en_US
dc.description.sponsorshipNIH (Grants EY007023, MH085802, MH126351, EY017500)en_US
dc.publisherFrontiers Media SAen_US
dc.relation.isversionof10.3389/fncir.2021.792228en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceFrontiersen_US
dc.titleA Platform for Spatiotemporal “Matrix” Stimulation in Brain Networks Reveals Novel Forms of Circuit Plasticityen_US
dc.typeArticleen_US
dc.identifier.citationWilson, Nathan R., Wang, Forea L., Chen, Naiyan, Yan, Sherry X., Daitch, Amy L. et al. 2022. "A Platform for Spatiotemporal “Matrix” Stimulation in Brain Networks Reveals Novel Forms of Circuit Plasticity." 15.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computational and Systems Biology Programen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.date.submission2022-01-12T18:45:24Z
mit.journal.volume15en_US
mit.licensePUBLISHER_CC
mit.metadata.statusPublication Information Neededen_US


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