BOLD cardiorespiratory pulsatility in the brain: from noise to signal of interest

Front Hum Neurosci. 2024 Jan 8:17:1327276. doi: 10.3389/fnhum.2023.1327276. eCollection 2023.

Abstract

Functional magnetic resonance imaging (fMRI) based on the Blood Oxygen Level Dependent (BOLD) contrast has been extensively used to map brain activity and connectivity in health and disease. Standard fMRI preprocessing includes different steps to remove confounds unrelated to neuronal activity. First, this narrative review explores how signal fluctuations due to cardiac and respiratory activity, usually considered as "physiological noise" and regressed out from fMRI time series. However, these signal components bear useful information about some mechanisms of brain functioning (e.g., glymphatic clearance) or cerebrovascular compliance in response to arterial pressure waves. Aging and chronic diseases can cause stiffening of the aorta and other main arteries, with a reduced dampening effect resulting in greater transmission of pressure impulses to the brain. Importantly, the continuous hammering of cardiac pulsations can produce local alterations of the mechanical properties of the small cerebral vessels, with a progressive deterioration that ultimately affects neuronal functionality. Second, the review emphasizes how fMRI can study the brain patterns most affected by cardiac pulsations in health and disease with high spatiotemporal resolution, offering the opportunity to identify much more specific risk markers than systemic factors based on measurements of the vascular compliance of large arteries or other global risk factors. In this regard, modern fast fMRI acquisition techniques allow a better characterization of these pulsatile signal components due to reduced aliasing effects, turning what has been traditionally considered as noise in a signal of interest that can be used to develop novel non-invasive biomarkers in different clinical contexts.

Keywords: BOLD; aging; fMRI; neurodegenerative; pulsatility.

Publication types

  • Review

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. SD acknowledges financial support from Search of Excellence (University “G. d’Annunzio” of Chieti- Pescara). SS acknowledges financial support from the Italian Ministry of Health, the AIRAlzh Onlus (ANCC-COOP), the Alzheimer’s Association–Part the Cloud: Translational Research Funding for Alzheimer’s Disease (18PTC-19-602325), and the Alzheimer’s Association–GAAIN Exploration to Evaluate Novel Alzheimer’s Queries (GEENA-Q-19-596282). AF acknowledges financial support from Strengthening of Research Structures and creation of R&D “Innovation Ecosystems,” National Recovery and Resilience Plan (NRRP), Mission 4, Component 2 Investment 1.5, funded from the European Union–NextGenerationEU–VITALITY, ECS00000041 (grant no. D73C22000840006).