Temporal and spatial characterization of physiological noise in rs-fMRI at a high temporal resolution
Year: 2025
Type: article
Abstract: The fMRI signal contains "noise" components resulting from physiological processes that interfere with the component due to neuronal activation and obscure the understanding of brain function. Having the neuronal activation component as the unknown, it is crucial to characterize the spatial and temporal aspects of the signal component that is due to cardiac and breathing cycles. 17 fMRI exams were performed in 9 subjects with a 3T Philipps MRI scanner with high sampling frequency (repetition time 125 ms, one slice). Photoplethysmography was used to track the cardiac cycle, and a pneumatic thoracic respiration transducer was used to measure the breathing cycle. The impact of the physiological signal on fMRI signal was evaluated in four regions of interest: (1) a region encompassing all areas below the subarachnoid space (Global Signal - GS), (2) ventricles (CSF), (3) venous return (VR), and (4) the region surrounding Middle Cerebral Arteries (MCA). Physiological noise is found heterogeneous across the ROIs in terms of amplitude and phase. The impact of respiration on the fMRI signal is greater than that of the heart, and it may be mediated by modulation of the venous return.
Source: Scientific Reports
Authors: Olga Kuldavletova, Marin Mauboussin, Mikael Naveau, Anais Vandevelde, Nicolas Delcroix, Marc Joliot, Olivier Etard
Institutions: Inserm, COMETE - Mobilités : Vieillissement, pathologie, santé, Normandie Université, Centre Hospitalier Universitaire de Caen Normandie, Cyceron, Mobilités: Vieillissement, Pathologie, Santé, Université de Caen Normandie, Centre National de la Recherche Scientifique, Centre Hospitalier Universitaire de Tours, Université de Bordeaux, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Institut des Maladies Neurodégénératives
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,690
Funder: Agence Nationale de la Recherche
OpenAlex ID: W4310692429
