The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure

Abstract

Humans differ from each other in a wide range of biometrics, but to what extent brain connectivity varies between individuals remains largely unknown. By combining diffusion-weighted imaging (DWI) and magnetoencephalography (MEG), this study characterizes the inter-subject variability (ISV) of multimodal brain connectivity. Structural connectivity is characterized by higher ISV in association cortices including the core multiple-demand network and lower ISV in the sensorimotor cortex. MEG ISV exhibits frequency-dependent signatures, and the extent of MEG ISV is consistent with that of structural connectivity ISV in selective macroscopic cortical clusters. Across the cortex, the ISVs of structural connectivity and beta-band MEG functional connectivity are negatively associated with cortical myelin content indexed by the quantitative T1 relaxation rate measured by high-resolution 7 T MRI. Furthermore, MEG ISV from alpha to gamma bands relates to the hindrance and restriction of the white-matter tissue estimated by DWI microstructural models. Our findings depict the inter-relationship between the ISV of brain connectivity from multiple modalities, and highlight the role of tissue microstructure underpinning the ISV.

Dynamics of Brain Connectivity across the Alzheimer’s Disease Spectrum: a magnetoencephalography study

“…The relevance of the regions and brain networks found using seed-based dFC (including orbitofrontal and temporal areas for both alpha and beta bands, and also precuneus, IFG, anterior and posterior cingulate gyrus, and superior medial frontal gyrus for the latter) has been highlighted in former research on brain changes throughout the AD continuum, such as functional alterations, 2,6,8,9,23 volumetric atrophy observed with MRI, 61,62 and amyloid neuropathological disturbances measured with positron emission tomography. 63 Interestingly, the distribution of the dFC changes found between MCI and HC correspond to multiple results in Karahan et al 58 Brain areas with decreased hindrance of white matter pathways display a similar distribution as the significant cluster found in the alpha band, and the location of the areas with the lowest cortical R1, e.g., with the lowest myelination, is alike the cluster found in the beta band. These areas are characterized by a lower neuronal density, large dendritic arborization, more spine density, more synapses, and higher aerobic glycolysis, which may be a neurobiological feature of the association cortices, enabling adaptable and plastic neural circuitry.…”

“…55 At the same time, several studies have drawn a connection between myelin abnormalities and brain connectivity, highlighting the importance of tract myelination, transmission speed, and the resulting coupling and synchrony patterns observed in the brain. 56,57 More specifically, it has been observed that the relations between structural and FC are spatial and frequency-dependent 58,59 and varies with age. 60 Importantly, multiple works, such as Karahan and colleagues, 58 have established a connection between the frequency bands affected in this study and myelination distribution and white matter properties.…”

“…56,57 More specifically, it has been observed that the relations between structural and FC are spatial and frequency-dependent 58,59 and varies with age. 60 Importantly, multiple works, such as Karahan and colleagues, 58 have established a connection between the frequency bands affected in this study and myelination distribution and white matter properties. In their work, they showed negative correlations between beta sFC inter-subject variability (ISV) and myelination, with alpha sFC-ISV failing to maintain significance due to statistical corrections, and significant negative correlations between alpha and beta sFC-ISV and the hindrance of white matter pathways.…”

Identification of Parkinson's disease subtypes with distinct brain atrophy progression and its association with clinical progression

“…Studies in humans have also found a relationship between brain connectivity and clinical symptoms as well as atrophy progression in PD (De Micco et al ., 2021 ; Vo et al ., 2023 ). However, humans vary in their brain connectivity, suggesting that the alpha-synuclein aggregation pattern in PD patients also exhibits a high level of heterogeneity (Karahan et al ., 2022 ; Zhang et al ., 2017 ). Furthermore, other demographic characteristics, such as genetic factors and lifestyles also relate to the progression of PD (Guo et al ., 2019 ; Li et al ., 2023 ; Pu et al ., 2022 ; Saunders-Pullman et al ., 2018 ).…”