兰州大学机构库 >物理科学与技术学院
Neural Mechanisms Underlying Breathing Complexity
Hess, A; Yu, LC(俞连春); Klein, I; De Mazancourt, M; Jebrak, G; Mal, H; Brugiere, O; Fournier, M; Courbage, M; Dauriat, G; Schouman-Clayes, E; Clerici, C; Mangin, L; Mangin, L (reprint author), Univ Paris 07, CNRS, Lab Mat & Syst Complexes, UMR 7057, Paris, France.
2013-10-03
Source PublicationPLoS One   Impact Factor & Quartile Of Published Year  The Latest Impact Factor & Quartile
ISSN1932-6203
Volume8Issue:10Pages:-
AbstractBreathing is maintained and controlled by a network of automatic neurons in the brainstem that generate respiratory rhythm and receive regulatory inputs. Breathing complexity therefore arises from respiratory central pattern generators modulated by peripheral and supra-spinal inputs. Very little is known on the brainstem neural substrates underlying breathing complexity in humans. We used both experimental and theoretical approaches to decipher these mechanisms in healthy humans and patients with chronic obstructive pulmonary disease (COPD). COPD is the most frequent chronic lung disease in the general population mainly due to tobacco smoke. In patients, airflow obstruction associated with hyperinflation and respiratory muscles weakness are key factors contributing to load-capacity imbalance and hence increased respiratory drive. Unexpectedly, we found that the patients breathed with a higher level of complexity during inspiration and expiration than controls. Using functional magnetic resonance imaging (fMRI), we scanned the brain of the participants to analyze the activity of two small regions involved in respiratory rhythmogenesis, the rostral ventro-lateral (VL) medulla (pre-Botzinger complex) and the caudal VL pons (parafacial group). fMRI revealed in controls higher activity of the VL medulla suggesting active inspiration, while in patients higher activity of the VL pons suggesting active expiration. COPD patients reactivate the parafacial to sustain ventilation. These findings may be involved in the onset of respiratory failure when the neural network becomes overwhelmed by respiratory overload We show that central neural activity correlates with airflow complexity in healthy subjects and COPD patients, at rest and during inspiratory loading. We finally used a theoretical approach of respiratory rhythmogenesis that reproduces the kernel activity of neurons involved in the automatic breathing. The model reveals how a chaotic activity in neurons can contribute to chaos in airflow and reproduces key experimental fMRI findings.
Subject AreaScience & Technology - Other Topics
PublisherPLOS
DOI10.1371/journal.pone.0075740
Publication PlaceSAN FRANCISCO
Indexed BySCIE ; PubMed ; MEDLINE
Language英语
First Inst
Funding Project国家自然科学基金项目
Project NumberPHRC [P100136] ; BQR Paris 7 University ; Fond de Dotation Recherche Respiratoire ; National Natural Science Foundation of China [11105062]
WOS IDWOS:000325483600022
Funding OrganizationNSFC
SubtypeArticle
PMID 24098396
Department
[Hess, Agathe;
Yu, Lianchun;
De Mazancourt, Marine;
Courbage, Maurice;
Mangin, Laurence] Univ Paris 07, CNRS, Lab Mat & Syst Complexes, UMR 7057, Paris, France;
[Hess, Agathe;
Klein, Isabelle;
Schouman-Clayes, Elisabeth] Hop Bichat Claude Bernard, AP HP, Serv Radiol, F-75877 Paris 18, France;
[Yu, Lianchun] Lanzhou Univ, Inst Theoret Phys, Lanzhou 730000, Peoples R China;
[Klein, Isabelle] Univ Paris 07, INSERM, U698, Paris, France...更多
Citation statistics
Cited Times:25[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttps://ir.lzu.edu.cn/handle/262010/105938
Collection物理科学与技术学院
Corresponding AuthorMangin, L (reprint author), Univ Paris 07, CNRS, Lab Mat & Syst Complexes, UMR 7057, Paris, France.
Recommended Citation
GB/T 7714
Hess, A,Yu, LC,Klein, I,et al. Neural Mechanisms Underlying Breathing Complexity[J]. PLoS One,2013,8(10):-.
APA Hess, A.,Yu, LC.,Klein, I.,De Mazancourt, M.,Jebrak, G.,...&Mangin, L .(2013).Neural Mechanisms Underlying Breathing Complexity.PLoS One,8(10),-.
MLA Hess, A,et al."Neural Mechanisms Underlying Breathing Complexity".PLoS One 8.10(2013):-.
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