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dc.contributor.authorAaser, Peter
dc.contributor.authorKnudsen, Martinius
dc.contributor.authorHuse Ramstad, Ola
dc.contributor.authorvan de Wijdeven, Rosanne
dc.contributor.authorNichele, Stefano
dc.contributor.authorSandvig, Ioanna
dc.contributor.authorTufte, Gunnar
dc.contributor.authorBauer, Ulrich Stefan
dc.contributor.authorHalaas, Øyvind
dc.contributor.authorHendseth, Sverre
dc.contributor.authorSandvig, Axel
dc.contributor.authorValderhaug, Vibeke Devold
dc.date.accessioned2018-01-24T08:14:15Z
dc.date.available2018-01-24T08:14:15Z
dc.date.created2017-09-14T16:32:54Z
dc.date.issued2017
dc.identifier.isbn978-0-262-34633-7
dc.identifier.urihttp://hdl.handle.net/11250/2479230
dc.description.abstractThe human brain is a remarkable computing machine, i.e. vastly parallel, self-organizing, robust, and energy efficient. To gain a better understanding into how the brain works, a cyborg (cybernetic organism, a combination of machine and living tissue) is currently being made in an interdisciplinary effort, known as the Cyborg project. In this paper we describe how living cultures of neurons (biological neural networks) are successfully grown in-vitro over Micro-Electrode Arrays (MEAs), which allow them to be interfaced to a robotic body through electrical stimulation and neural recordings. Furthermore, we describe the bio- and nano-technological procedures utilized for the culture of such dissociated neural networks and the interface software and hardware framework used for creating a closed-loop hybrid neuro-system. A Reservoir Computing (RC) approach is used to harness the computational power of the neuronal culture.nb_NO
dc.language.isoengnb_NO
dc.publisherMIT Pressnb_NO
dc.relation.ispartofProceedings of the European Conference on Artificial Life 2017
dc.relation.urihttps://www.ntnu.edu/socrates
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleTowards Making a Cyborg: A Closed-Loop Reservoir-Neuro Systemnb_NO
dc.typeChapternb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.pagenumber430-437nb_NO
dc.identifier.doi10.7551/ecal_a_072
dc.identifier.cristin1493907
dc.relation.projectNorges forskningsråd: 270961nb_NO
dc.description.localcode© 2017 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) licensenb_NO
cristin.unitcode194,63,10,0
cristin.unitcode194,63,25,0
cristin.unitcode194,65,30,0
cristin.unitcode194,63,35,0
cristin.unitcode194,65,15,0
cristin.unitnameInstitutt for datateknologi og informatikk
cristin.unitnameInstitutt for teknisk kybernetikk
cristin.unitnameInstitutt for nevromedisin og bevegelsesvitenskap
cristin.unitnameInstitutt for elektroniske systemer
cristin.unitnameInstitutt for klinisk og molekylær medisin
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.fulltextoriginal
cristin.qualitycode2


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