AustralieFrV1, Ncbi, Curation, bibRecord, 003119

Electroencephalographic detection of respiratory-related cortical activity in humans: from event-related approaches to continuous connectivity evaluation

Identifieur interne : 003119 ( Ncbi/Curation ); précédent : 003118; suivant : 003120

Electroencephalographic detection of respiratory-related cortical activity in humans: from event-related approaches to continuous connectivity evaluation

Auteurs : Anna L. Hudson [Australie] ; Xavier Navarro-Sune [France] ; Jacques Martinerie [France] ; Pierre Pouget [France] ; Mathieu Raux [France] ; Mario Chavez [France] ; Thomas Similowski [France]

Source :

Journal of Neurophysiology [ 0022-3077 ] ; 2016.

RBID : PMC:4869487

Descripteurs français

KwdFr :
- Adulte, Cortex cérébral (physiologie), Femelle, Humains, Mâle, Potentiels évoqués moteurs, Respiration, Temps de réaction.
MESH :
- physiologie : Cortex cérébral.
- Adulte, Femelle, Humains, Mâle, Potentiels évoqués moteurs, Respiration, Temps de réaction.

English descriptors

KwdEn :
- Adult, Cerebral Cortex (physiology), Evoked Potentials, Motor, Female, Humans, Male, Reaction Time, Respiration.
MESH :
- physiology : Cerebral Cortex.
- Adult, Evoked Potentials, Motor, Female, Humans, Male, Reaction Time, Respiration.

Abstract

The presence of a respiratory-related cortical activity during tidal breathing is abnormal and a hallmark of respiratory difficulties, but its detection requires superior discrimination and temporal resolution. The aim of this study was to validate a computational method using EEG covariance (or connectivity) matrices to detect a change in brain activity related to breathing. In 17 healthy subjects, EEG was recorded during resting unloaded breathing (RB), voluntary sniffs, and breathing against an inspiratory threshold load (ITL). EEG were analyzed by the specially developed covariance-based classifier, event-related potentials, and time-frequency (T-F) distributions. Nine subjects repeated the protocol. The classifier could accurately detect ITL and sniffs compared with the reference period of RB. For ITL, EEG-based detection was superior to airflow-based detection (P < 0.05). A coincident improvement in EEG-airflow correlation in ITL compared with RB (P < 0.05) confirmed that EEG detection relates to breathing. Premotor potential incidence was significantly higher before inspiration in sniffs and ITL compared with RB (P < 0.05), but T-F distributions revealed a significant difference between sniffs and RB only (P < 0.05). Intraclass correlation values ranged from poor (−0.2) to excellent (1.0). Thus, as for conventional event-related potential analysis, the covariance-based classifier can accurately predict a change in brain state related to a change in respiratory state, and given its capacity for near “real-time” detection, it is suitable to monitor the respiratory state in respiratory and critically ill patients in the development of a brain-ventilator interface.

Url:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4869487

DOI: 10.1152/jn.01058.2015
PubMed: 26864771
PubMed Central: 4869487

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Le document en format XML

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<front><div type="abstract" xml:lang="en"><p>The presence of a respiratory-related cortical activity during tidal breathing is abnormal and a hallmark of respiratory difficulties, but its detection requires superior discrimination and temporal resolution. The aim of this study was to validate a computational method using EEG covariance (or connectivity) matrices to detect a change in brain activity related to breathing. In 17 healthy subjects, EEG was recorded during resting unloaded breathing (RB), voluntary sniffs, and breathing against an inspiratory threshold load (ITL). EEG were analyzed by the specially developed covariance-based classifier, event-related potentials, and time-frequency (T-F) distributions. Nine subjects repeated the protocol. The classifier could accurately detect ITL and sniffs compared with the reference period of RB. For ITL, EEG-based detection was superior to airflow-based detection (<italic>P</italic>
 < 0.05). A coincident improvement in EEG-airflow correlation in ITL compared with RB (<italic>P</italic>
 < 0.05) confirmed that EEG detection relates to breathing. Premotor potential incidence was significantly higher before inspiration in sniffs and ITL compared with RB (<italic>P</italic>
 < 0.05), but T-F distributions revealed a significant difference between sniffs and RB only (<italic>P</italic>
 < 0.05). Intraclass correlation values ranged from poor (−0.2) to excellent (1.0). Thus, as for conventional event-related potential analysis, the covariance-based classifier can accurately predict a change in brain state related to a change in respiratory state, and given its capacity for near “real-time” detection, it is suitable to monitor the respiratory state in respiratory and critically ill patients in the development of a brain-ventilator interface.</p>
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Electroencephalographic detection of respiratory-related cortical activity in humans: from event-related approaches to continuous connectivity evaluation

Electroencephalographic detection of respiratory-related cortical activity in humans: from event-related approaches to continuous connectivity evaluation

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Abstract

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