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Pregled bibliografske jedinice broj: 1237438

Network analysis identifies consensus physiological measures of neurovascular coupling in humans


Squair, Jordan W.; Lee, Amanda H. X.; Sarafis, Zoe K.; Chan, Franco; Barak, Otto F.; Dujić, Željko; Day, Trevor; Phillips, Aaron A.
Network analysis identifies consensus physiological measures of neurovascular coupling in humans // Journal of cerebral blood flow and metabolism, 40 (2020), 3; 656-666 doi:10.1177/0271678X19831825 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1237438 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Network analysis identifies consensus physiological measures of neurovascular coupling in humans

Autori
Squair, Jordan W. ; Lee, Amanda H. X. ; Sarafis, Zoe K. ; Chan, Franco ; Barak, Otto F. ; Dujić, Željko ; Day, Trevor ; Phillips, Aaron A.

Izvornik
Journal of cerebral blood flow and metabolism (0271-678X) 40 (2020), 3; 656-666

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Neurovascular coupling ; functional hyperemia ; network analysis ; parameter identification ; spinal cord injury

Sažetak
Intimate communication between neural and vascular structures is required to match neuronal metabolism to blood flow, a process termed neurovascular coupling. The number of laboratories assessing neurovascular coupling in humans is increasing due to clinical interest in disease states, and basic science interest in a non- anesthetized, non-craniotomized, unrestrained, in vivo model. However, there is a lack of knowledge regarding how best to characterize the neurovascular response. To address this knowledge gap, we have amassed a highly powered human neurovascular coupling dataset, and deployed a network-based approach to reveal the most powerful and consistent metrics for quantifying neurovascular coupling. Using dimensionality reduction, community-based clustering, and majority-voting of traditional metrics (e.g. peak response, time to peak) and non-traditional metrics (e.g. varying time windows, pulsatility), we have identified which of the existing metrics predominantly characterize the neurovascular coupling response, are stable within and across participants, and explain the vast majority of the variance within our dataset of over 300 trials. We then harnessed our empirical approach to generate powerful novel metrics of neurovascular coupling, termed iAmplitude, iRate, and iPulsatility, which increase sensitivity when capturing population differences. These metrics may be useful to optimally understand neurovascular coupling in health and disease.

Izvorni jezik
Engleski

Znanstvena područja
Kliničke medicinske znanosti



POVEZANOST RADA


Ustanove:
Medicinski fakultet, Split

Profili:

Avatar Url Željko Dujić (autor)

Poveznice na cjeloviti tekst rada:

doi journals.sagepub.com

Citiraj ovu publikaciju:

Squair, Jordan W.; Lee, Amanda H. X.; Sarafis, Zoe K.; Chan, Franco; Barak, Otto F.; Dujić, Željko; Day, Trevor; Phillips, Aaron A.
Network analysis identifies consensus physiological measures of neurovascular coupling in humans // Journal of cerebral blood flow and metabolism, 40 (2020), 3; 656-666 doi:10.1177/0271678X19831825 (međunarodna recenzija, članak, znanstveni)
Squair, J., Lee, A., Sarafis, Z., Chan, F., Barak, O., Dujić, Ž., Day, T. & Phillips, A. (2020) Network analysis identifies consensus physiological measures of neurovascular coupling in humans. Journal of cerebral blood flow and metabolism, 40 (3), 656-666 doi:10.1177/0271678X19831825.
@article{article, author = {Squair, Jordan W. and Lee, Amanda H. X. and Sarafis, Zoe K. and Chan, Franco and Barak, Otto F. and Duji\'{c}, \v{Z}eljko and Day, Trevor and Phillips, Aaron A.}, year = {2020}, pages = {656-666}, DOI = {10.1177/0271678X19831825}, keywords = {Neurovascular coupling, functional hyperemia, network analysis, parameter identification, spinal cord injury}, journal = {Journal of cerebral blood flow and metabolism}, doi = {10.1177/0271678X19831825}, volume = {40}, number = {3}, issn = {0271-678X}, title = {Network analysis identifies consensus physiological measures of neurovascular coupling in humans}, keyword = {Neurovascular coupling, functional hyperemia, network analysis, parameter identification, spinal cord injury} }
@article{article, author = {Squair, Jordan W. and Lee, Amanda H. X. and Sarafis, Zoe K. and Chan, Franco and Barak, Otto F. and Duji\'{c}, \v{Z}eljko and Day, Trevor and Phillips, Aaron A.}, year = {2020}, pages = {656-666}, DOI = {10.1177/0271678X19831825}, keywords = {Neurovascular coupling, functional hyperemia, network analysis, parameter identification, spinal cord injury}, journal = {Journal of cerebral blood flow and metabolism}, doi = {10.1177/0271678X19831825}, volume = {40}, number = {3}, issn = {0271-678X}, title = {Network analysis identifies consensus physiological measures of neurovascular coupling in humans}, keyword = {Neurovascular coupling, functional hyperemia, network analysis, parameter identification, spinal cord injury} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


Citati:





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