Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/2911
DC FieldValueLanguage
dc.contributor.authorIrvine, A.W.-
dc.contributor.authorTsechpenakis, Gabriel-
dc.contributor.authorChatzis, Sotirios P.-
dc.contributor.otherΧατζής, Σωτήριος Π.-
dc.date.accessioned2013-02-20T12:39:09Zen
dc.date.accessioned2013-05-17T05:34:06Z-
dc.date.accessioned2015-12-02T12:26:29Z-
dc.date.available2013-02-20T12:39:09Zen
dc.date.available2013-05-17T05:34:06Z-
dc.date.available2015-12-02T12:26:29Z-
dc.date.issued2010-06-
dc.identifier.citationIEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010, pp. 65-68en_US
dc.identifier.isbn978-1-4244-4125-9 (print)-
dc.identifier.issn978-1-4244-4126-6 (online)-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/2911-
dc.description.abstractWe make a major step towards answering the question posed in the title, using as model the mouse foetus in its 17-19 embryonic days. We use (a) 2-photon microscopy to image the brainstem cell activity ([Ca2+]) in the pre-Boetzinger complex, and (b) electrical recordings from the phrenic nerve, which indicate the diaphragm contraction during inspiration. We classify the brainstem regions (individual cells or groups of cells) into 'active' and 'inactive', based on whether they contribute or not to the individual electrical signal peaks. As features, we use the Continuous Wavelet Transform-based Semblance responses, for comparing non-periodic and/or periodic-like signals. We use our novel Generative Mixture Model (GMM) possibilistic clustering to obtain the desired classes robustly. This way, we model the inspiration control as a physiological process, which is a crucial step towards understanding how the living brain controls breathingen_US
dc.language.isoenen_US
dc.rights© 2010 IEEEen_US
dc.subjectDiagnostic imagingen_US
dc.subjectMultiphoton processesen_US
dc.subjectPhotonsen_US
dc.subjectNeuronsen_US
dc.subjectRespirationen_US
dc.subjectCellsen_US
dc.titleWhich brainstem cells generate the respiration cycles?en_US
dc.typeBook Chapteren_US
dc.collaborationUniversity of Miamien_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.countryUnited Statesen_US
dc.subject.fieldEngineering and Technologyen_US
dc.relation.conferenceIEEE International Symposium on Biomedical Imagingen_US
dc.identifier.doi10.1109/ISBI.2010.5490412en_US
dc.dept.handle123456789/54en
cut.common.academicyear2009-2010en_US
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_3248-
item.openairetypebookPart-
item.languageiso639-1en-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-4956-4013-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Κεφάλαια βιβλίων/Book chapters
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