Year: 2020
Type: article
Abstract: Slow changes in systemic brain physiology can elicit large fluctuations in fMRI time series, which manifest as structured spatial patterns of temporal correlations between distant brain regions. Here, we investigated whether such "physiological networks"-sets of segregated brain regions that exhibit similar responses following slow changes in systemic physiology-resemble patterns associated with large-scale networks typically attributed to remotely synchronized neuronal activity. By analyzing a large group of subjects from the 3T Human Connectome Project (HCP) database, we demonstrate brain-wide and noticeably heterogenous dynamics tightly coupled to either respiratory variation or heart rate changes. We show, using synthesized data generated from physiological recordings across subjects, that these physiologically-coupled fluctuations alone can produce networks that strongly resemble previously reported resting-state networks, suggesting that, in some cases, the "physiological networks" seem to mimic the neuronal networks. Further, we show that such physiologically-relevant connectivity estimates appear to dominate the overall connectivity observations in multiple HCP subjects, and that this apparent "physiological connectivity" cannot be removed by the use of a single nuisance regressor for the entire brain (such as global signal regression) due to the clear regional heterogeneity of the physiologically-coupled responses. Our results challenge previous notions that physiological confounds are either localized to large veins or globally coherent across the cortex, therefore emphasizing the necessity to consider potential physiological contributions in fMRI-based functional connectivity studies. The rich spatiotemporal patterns carried by such "physiological" dynamics also suggest great potential for clinical biomarkers that are complementary to large-scale neuronal networks.
Source: NeuroImage
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,000
Funders: Centre d'Imagerie BioMédicale, National Institutes of Health, McDonnell Center for Systems Neuroscience, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Institute of Environmental Health Sciences, National Institute of Biomedical Imaging and Bioengineering, National Center for Research Resources
Awards: Tracking brain arousal fluctuations for fMRI Big Data discovery, G1360098495, G1960588227, G2483948867, G2614185620, Resting state connectivity: Biophysical basis for and improved fMRI measurements, Mapping the Human Connectome: Structure, Function, and Heritability, G3848525072, G393103480, Imaging neural dynamics at high temporal resolution in sleep and sleep deprivation, G4906623738, fMRI Technologies for Imaging at the Limit of Biological Spatiotemporal Resolution, Improving Human fMRI through Modeling and Imaging Microvascular Dynamics, 7T Translational MRI System, Center for Functional Imaging Technologies, Relating Vigilance to Connectivity and Neurocognition in Temporal Lobe Epilepsy, G9000001300, G9000200654, G9000315933, Technology to Realize the Full Potential of UHF MRI, Silicon Graphics Prism Extreme 128P/1TB
OpenAlex ID: W3009669872