White-matter degradation and dynamical compensation support age-related functional alterations in human brain

Abstract

Structural connectivity of the brain at different ages is analyzed using diffusion-weighted Magnetic Resonance Imaging (MRI) data. The largest decrease of the number and average length of stream- lines is found for the long inter-hemispheric links, with the strongest impact for frontal regions. From the BOLD functional MRI (fMRI) time series we identify age-related changes of dynamic functional connectivity (dFC) and spatial covariation features of the FC links captured by meta- connectivity (MC). They indicate more constant dFC, but wider range and variance of MC. Finally we applied computational whole-brain network model based on oscillators, which mechanistically expresses the impact of the spatio-temporal structure of the brain (weights and the delays) to the dynamics. With this we tested several hypothesis, which revealed that the spatio-temporal reorga- nization of the brain with ageing, supports the observed functional fingerprints only if the model accounts for: (i) compensation of the individual brains for the overall loss of structural connectivity, and (ii) decrease of propagation velocity due to the loss of myelination. We also show that having these two conditions, it is sufficient to decompose the time-delays as bimodal distribution that only distinguishes between intra- and inter-hemispheric delays, and that the same working point also captures the static FC the best.

State switching and high-order spatiotemporal organization of dynamic Functional Connectivity are disrupted by Alzheimer’s Disease

“…Further, individual FC links do not fluctuate independently but with network reconfigurations governed by higher order coordination patterns, manifest by: non-trivial inter-link covariance patterns (Davison et al, 2015;Faskowitz et al, 2020;Petkoski et al, 2023); "back-bones" partially scaffolding dFC (Braun et al, 2015); and dFC flowing under the influence of competing "meta-hubs (Lombardo et al, 2020). Reiterating, our hypothesis suggests that spatiotemporal structure of dFC between order and randomness allows for rich computation to emerge from the systems' collective activity (cf.…”

“…The dFC random walk approach (Arbabyazd et al, 2020;Battaglia et al, 2020;Lombardo et al, 2020;Petkoski et al, 2023) models rs dFC as a temporal network as well, but focuses on the variation from one network frame to the next, more than on the geometry of individual network frames. dFC is seen as a flow in network space and the non-randomness of network reconfiguration was investigated via a time-to-time correlation approach known as Meta-Connectivity (Lombardo et al, 2020).…”

“…This stochastic walk however is not trivial, as different inter-regional links covary according to a specific higher-order correlation structure called meta-connectivity (Lombardo et al, 2020). State-free and smoothly varying dFC temporal networks were extracted using a sliding window approach, adopting the randomwalks and meta-connectivity approaches (Battaglia et al, 2020;Lombardo et al, 2020;Petkoski et al, 2023) released within the dFCwalk toolbox (Arbabyazd et al, 2020).…”

“…A number of studies have quantified dFC changes in healthy aging (Battaglia et al, 2020;Davison et al, 2016;Hutchison and Morton, 2015;Lavanga et al, 2022;Petkoski et al, 2023;Qin et al, 2015;Viviano et al, 2017) and in conditions such as schizophrenia (Damaraju et al, 2014;Sakoğlu et al, 2010), epilepsy (Liao et al, 2014;Liu et al, 2017) and Parkinson's disease (Fiorenzato et al, 2019;Kim et al, 2017). In AD, probabilities of temporal transitions between alternative FC states have been shown to be altered (Jones et al, 2011;Fu et al, 2019;Gu et al, 2020;Schumacher et al, 2019).…”