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송현곤

Song, Hyun-Kon
eclat: electrochemistry lab of advanced technology
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dc.citation.endPage 5739 -
dc.citation.number 33 -
dc.citation.startPage 5734 -
dc.citation.title BIOMATERIALS -
dc.citation.volume 27 -
dc.contributor.author Venkataramani, Sowmya -
dc.contributor.author Xu, Heng -
dc.contributor.author Song, Yoon-Kyu -
dc.contributor.author Song, Hyun-Kon -
dc.contributor.author Palmore, G. Tayhas R. -
dc.contributor.author Fallon, Justin -
dc.contributor.author Nurmikko, Arto V. -
dc.date.accessioned 2023-12-22T09:40:45Z -
dc.date.available 2023-12-22T09:40:45Z -
dc.date.created 2014-09-26 -
dc.date.issued 2006-11 -
dc.description.abstract In vitro neuronal networks with geometrically defined features are desirable for studying long-term electrical activity within the neuron assembly and for interfacing with external microelectronic circuits. In standard cultures, the random spatial distribution and overlap of neurites makes this aim difficult; hence, many recent efforts have been made on creating patterned cellular circuits. Here, we present a novel method for creating a planar neural network that is compatible with optical devices. This method combines both topographical and chemical micropatterns onto which neurons can be cultured. Compared to other reported patterning techniques, our approach and choice of template appears to show both geometrical control over the formation of specific neurite connections at low plating density and compatibility with microelectronic circuits that stimulate and record neural activity. -
dc.identifier.bibliographicCitation BIOMATERIALS, v.27, no.33, pp.5734 - 5739 -
dc.identifier.doi 10.1016/j.biomaterials.2006.07.021 -
dc.identifier.issn 0142-9612 -
dc.identifier.scopusid 2-s2.0-33747761652 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/6508 -
dc.identifier.url http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=33747761652 -
dc.identifier.wosid 000241131500013 -
dc.language 영어 -
dc.publisher ELSEVIER SCI LTD -
dc.title Combined topographical and chemical micropatterns for templating neuronal networks -
dc.type Article -
dc.description.journalRegisteredClass scopus -

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