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1000 Titel
  • Computational Pipeline for NIRS-EEG Joint Imaging of tDCS-Evoked Cerebral
1000 Autor/in
  1. Guhathakurta, Debarpan |
  2. Dutta, Anirban |
1000 Erscheinungsjahr 2016
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2016-06-20
1000 Erschienen in
1000 Quellenangabe
  • 10: 261
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2016
1000 Lizenz
1000 Verlagsversion
  • http://dx.doi.org/10.3389/fnins.2016.00261 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4913108/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Transcranial direct current stimulation (tDCS) modulates cortical neural activity and hemodynamics. Electrophysiological methods (electroencephalography-EEG) measure neural activity while optical methods (near-infrared spectroscopy-NIRS) measure hemodynamics coupled through neurovascular coupling (NVC). Assessment of NVC requires development of NIRS-EEG joint-imaging sensor montages that are sensitive to the tDCS affected brain areas. In this methods paper, we present a software pipeline incorporating freely available software tools that can be used to target vascular territories with tDCS and develop a NIRS-EEG probe for joint imaging of tDCS-evoked responses. We apply this software pipeline to target primarily the outer convexity of the brain territory (superficial divisions) of the middle cerebral artery (MCA). We then present a computational method based on Empirical Mode Decomposition of NIRS and EEG time series into a set of intrinsic mode functions (IMFs), and then perform a cross-correlation analysis on those IMFs from NIRS and EEG signals to model NVC at the lesional and contralesional hemispheres of an ischemic stroke patient. For the contralesional hemisphere, a strong positive correlation between IMFs of regional cerebral hemoglobin oxygen saturation and the log-transformed mean-power time-series of IMFs for EEG with a lag of about −15 s was found after a cumulative 550 s stimulation of anodal tDCS. It is postulated that system identification, for example using a continuous-time autoregressive model, of this coupling relation under tDCS perturbation may provide spatiotemporal discriminatory features for the identification of ischemia. Furthermore, portable NIRS-EEG joint imaging can be incorporated into brain computer interfaces to monitor tDCS-facilitated neurointervention as well as cortical reorganization.
1000 Sacherschließung
lokal computational modeling
lokal ischemic stroke
lokal near-infrared spectroscopy
lokal transcranial direct current stimulation
lokal electroencephalography
lokal neurovascular coupling
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/creator/R3VoYXRoYWt1cnRhLCBEZWJhcnBhbg==|https://frl.publisso.de/adhoc/creator/RHV0dGEsIEFuaXJiYW4=
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  1. Institut National de Recherche en Informatique et en Automatique (INRIA) |
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1000 Dateien
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    1000 Förderer Institut National de Recherche en Informatique et en Automatique (INRIA) |
    1000 Förderprogramm -
    1000 Fördernummer -
1000 Objektart article
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1000 Erstellt am 2017-08-10T14:52:56.778+0200
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1000 Bearbeitet von 288
1000 Zuletzt bearbeitet 2021-01-15T09:04:20.067+0100
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1000 Vgl. frl:6403798
1000 Oai Id
  1. oai:frl.publisso.de:frl:6403798 |
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