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dc.contributor.authorZverev, Mihail
dc.contributor.authorFanjul Vélez, Félix 
dc.contributor.authorSalas García, Irene 
dc.contributor.authorOrtega Quijano, Noé 
dc.contributor.authorArce Diego, José Luis 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2017-08-01T14:08:05Z
dc.date.available2017-08-01T14:08:05Z
dc.date.issued2016
dc.identifier.issn0277-786X
dc.identifier.issn1996-756X
dc.identifier.otherMAT2012-38664-C02-01es_ES
dc.identifier.urihttp://hdl.handle.net/10902/11484
dc.description.abstractThe number of people in risk of developing a neurodegenerative disease increases as the life expectancy grows due to medical advances. Multiple techniques have been developed to improve patient’s condition, from pharmacological to invasive electrodes approaches, but no definite cure has yet been discovered. In this work Optical Neural Stimulation (ONS) has been studied. ONS stimulates noninvasively the outer regions of the brain, mainly the neocortex. The relationship between the stimulation parameters and the therapeutic response is not totally clear. In order to find optimal ONS parameters to treat a particular neurodegenerative disease, mathematical modeling is necessary. Neural networks models have been employed to study the neural spiking activity change induced by ONS. Healthy and pathological neocortical networks have been considered to study the required stimulation to restore the normal activity. The network consisted of a group of interconnected neurons, which were assigned 2D spatial coordinates. The optical stimulation spatial profile was assumed to be Gaussian. The stimulation effects were modeled as synaptic current increases in the affected neurons, proportional to the stimulation fluence. Pathological networks were defined as the healthy ones with some neurons being inactivated, which presented no synaptic conductance. Neurons’ electrical activity was also studied in the frequency domain, focusing specially on the changes of the spectral bands corresponding to brain waves. The complete model could be used to determine the optimal ONS parameters in order to achieve the specific neural spiking patterns or the required local neural activity increase to treat particular neurodegenerative pathologies.es_ES
dc.description.sponsorshipThis work has been partially supported by the project MAT2012-38664-C02-01 of the Spanish Ministery of Economy and Competitiveness and by San Cándido Foundation.es_ES
dc.format.extent5 p.es_ES
dc.language.isoenges_ES
dc.publisherSPIE Society of Photo-Optical Instrumentation Engineerses_ES
dc.rightsCopyright 2016 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.es_ES
dc.sourceProceedings of SPIE, 2016, 9690, 96901Qes_ES
dc.sourceClinical and Translational Neurophotonics; Neural Imaging and Sensing; and Optogenetics and Optical Manipulation, San Francisco, 2016es_ES
dc.subject.otherOptical neural stimulationes_ES
dc.subject.otherNeural networkes_ES
dc.subject.otherNeurodegenerative diseaseses_ES
dc.subject.otherNeural spikinges_ES
dc.titleAnalysis of optical neural stimulation effects on neural networks affected by neurodegenerative diseaseses_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.relation.publisherVersionhttps://doi.org/10.1117/12.2208683es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1117/12.2208683
dc.type.versionpublishedVersiones_ES


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