Interplay between functional connectivity and scale-free dynamics in intrinsic fMRI networks

Studies employing functional connectivity-type analyses have established that spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals are organized within large-scale brain networks. Meanwhile, fMRI signals have been shown to exhibit 1/f-type power spectra — a hallmark of sc...

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Bibliographic Details
Published in:NeuroImage (Orlando, Fla.) Fla.), 2014-07, Vol.95, p.248-263
Main Authors: Ciuciu, Philippe, Abry, Patrice, He, Biyu J.
Format: Article
Language:English
Subjects:
Adolescent
Adult
Behavior
Bioengineering
Biological and medical sciences
Brain
Brain - physiology
Brain Mapping - methods
Cognitive Sciences
Computer Science
Cross-temporal dynamics
Female
fMRI
Fundamental and applied biological sciences. Psychology
Humans
Image Processing, Computer-Assisted - methods
Imaging
Intrinsic brain activity
Life Sciences
Magnetic Resonance Imaging
Male
Medical Imaging
Models, Theoretical
Neural Pathways - physiology
Neurons and Cognition
Principal components analysis
Scale-free dynamics
Signal and Image Processing
Task modulation
Vertebrates: nervous system and sense organs
Wavelet transforms
Young Adult
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Summary:Studies employing functional connectivity-type analyses have established that spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals are organized within large-scale brain networks. Meanwhile, fMRI signals have been shown to exhibit 1/f-type power spectra — a hallmark of scale-free dynamics. We studied the interplay between functional connectivity and scale-free dynamics in fMRI signals, utilizing the fractal connectivity framework — a multivariate extension of the univariate fractional Gaussian noise model, which relies on a wavelet formulation for robust parameter estimation. We applied this framework to fMRI data acquired from healthy young adults at rest and while performing a visual detection task. First, we found that scale-invariance existed beyond univariate dynamics, being present also in bivariate cross-temporal dynamics. Second, we observed that frequencies within the scale-free range do not contribute evenly to inter-regional connectivity, with a systematically stronger contribution of the lowest frequencies, both at rest and during task. Third, in addition to a decrease of the Hurst exponent and inter-regional correlations, task performance modified cross-temporal dynamics, inducing a larger contribution of the highest frequencies within the scale-free range to global correlation. Lastly, we found that across individuals, a weaker task modulation of the frequency contribution to inter-regional connectivity was associated with better task performance manifesting as shorter and less variable reaction times. These findings bring together two related fields that have hitherto been studied separately — resting-state networks and scale-free dynamics, and show that scale-free dynamics of human brain activity manifest in cross-regional interactions as well. •Scale-free dynamics and functional connectivity are intertwined in brain networks.•Scale-free dynamics in two different regions/networks can be related to each other.•Lower frequencies contribute more to inter-regional functional connectivity.•Task modulates cross-temporal dynamics by moderating the lowest frequencies.•The smaller the magnitude of this modulation, the better the behavioral performance.
ISSN:1053-8119
1095-9572
DOI:10.1016/j.neuroimage.2014.03.047