The biological role of local and global fMRI BOLD signal variability in human brain organization

Abstract

Variability drives the organization and behavior of complex systems, including the human brain. Understanding the variability of brain signals is thus necessary to broaden our window into brain function and behavior. Few empirical investigations of macroscale brain signal variability have yet been undertaken, given the difficulty in separating biological sources of variance from artefactual noise. Here, we characterize the temporal variability of the most predominant macroscale brain signal, the fMRI BOLD signal, and systematically investigate its statistical, topographical and neurobiological properties. We contrast fMRI acquisition protocols, and integrate across histology, microstructure, transcriptomics, neurotransmitter receptor and metabolic data, fMRI static connectivity, and empirical and simulated magnetoencephalography data. We show that BOLD signal variability represents a spatially heterogeneous, central property of multi-scale multi-modal brain organization, distinct from noise. Our work establishes the biological relevance of BOLD signal variability and provides a lens on brain stochasticity across spatial and temporal scales.

The neurophysiological brain-fingerprint of Parkinson’s disease

“… 85 fMRI research has linked moment-to-moment brain activity variability with cognitive performance, 86 , 87 , 88 and recent studies have related BOLD signal variability to the arrhythmic components of electrophysiology. 89 Consequently, we hypothesize that the heightened variability in PD behavioural markers may be associated with the observed increased temporal variability in arrhythmic brain activity.…”

Mapping multi-modal dynamic network activity during naturalistic music listening

“…This work represents an authentic look at quantifying and interpreting naturalistic behaviour and provides a viable method for navigating through high-dimensional datasets. Future directions could also include constructing participant-level models and comparing between-participants for cohort- and/or population-level differences (the STATIS method (Abdi et al, 2005) may be particularly useful here, see Baracchini et al, 2023), adding another dimension to existing work on the link between brain and behavior. These methods are new, unfamiliar, and have great potential, particularly for those interested in understanding the brain as part of a larger interconnected system.…”

The neurophysiological brain-fingerprint of Parkinson’s disease

“…The biological basis of this behavioral variability increase remains poorly understood 75 . fMRI research has linked moment-to-moment brain activity variability with cognitive performance [76][77][78] , and recent studies have related BOLD signal variability to the arrhythmic components of electrophysiology 79 . Consequently, we hypothesize that the heightened variability in PD behavioral markers may be associated with the observed increased temporal variability in arrhythmic brain activity.…”