Authors :
Presenting Author: Ke Xie, MSc – McGill University
Jessica Royer, PsyD – Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; Raul Rodriguez-Cruces, PhD – Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; Hans Auer, BSc – Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; Alexander Ngo, BSc – Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; Ella Sahlas, BSc – Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; Judy Chen, BSc – Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; Donna Cabalo, MSc – Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; Shahin Tavakol, MSc – Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; Birgit Frauscher, MD, PhD – Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada; Andrea Bernasconi, MD – Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada; Neda Bernasconi, MD, PhD – Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada; Boris Bernhardt, PhD – Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
Rationale: Despite the existing evidence of widespread structural and functional connectome alterations in temporal lobe epilepsy (TLE), the extent to which these shifts constrain brain function remains poorly understood. To bridge this gap, this study employs a dynamic structure-function coupling (SFC) framework to investigate the impact of white-matter architectural changes on neural activity in TLE from a dynamic perspective.
Methods:
This work included 35 individuals with drug-resistant TLE (16 males; 25 left-sided focus; mean ± standard deviation [SD] age = 35.7 ± 10.7 years), and 40 age and sex matched healthy controls (20 males; mean ± SD age = 34.4 ± 3.9 years). All participants underwent T1-weighted MRI, resting-state fMRI, and diffusion MRI scans. We constructed temporal co-fluctuation matrices by calculating the element-wise product of z-scored resting-state fMRI time series between pairs of brain areas (Fig 1a). We then applied a multilinear model to predict the co-fluctuation profile of node i at time point t using its geometric and structural connectivity profiles (Fig 1b), where the SFC was determined by the coefficient of determination Rit2 between the predicted and the empirical functional profile (Fig 1c). To quantify the variability of SFC across time, we calculated the coefficient of variation of R2 (i.e., cv(R2)) that was the ratio of the standard deviation of R2 to the mean of R2 (Fig 1c). Surface-based linear models were used to compare dynamic SFC between TLE patients and healthy controls while controlling for age and sex.
Results:
In the control group, dynamic SFC was regionally heterogeneous, with the highest values observed in the medial occipital, prefrontal, and limbic cortices, indicating greater fluctuations in SFC over time (Fig 2a). The surface-wide analysis demonstrated extensive alterations in dynamic SFC in TLE patients compared to healthy controls, with the strongest effects observed in bilateral frontal, medial parietal, and occipital cortices (FDR < 0.05, Fig 2b); patients with TLE, therefore, exhibited higher moment-to-moment fluctuations in SFC in these regions. Further stratification analysis using a well-established atlas of twelve intrinsic functional networks revealed higher dynamic SFC values in TLE patients compared to healthy controls across several systems, including the default mode, frontoparietal, cingulo-opercular and attention networks (FDR < 0.05, Fig 2c).
Conclusions: These findings contribute to a better understanding of the impact of structural alterations on dynamic brain function in TLE patients, revealing higher temporal variations in SFC across widespread regions. Future work will determine the associations between these findings with cognitive alterations as well as clinical outcomes.
Funding: Ke Xie (CSC: 202006070175)