Kanber, B. | Search bioRxiv

bioRxiv2025

Causal inference and functional dynamics of a visuomotor network demonstrate excitatory/inhibitory alterations in Multiple Sclerosis

Balanced excitation and inhibition are essential for brain dynamics, and their disruption can lead to network dysfunction in neurological diseases. Here, we present a conceptually unified multiscale brain modelling framework combining Dynamic Causal Modelling (DCM) applied to task and resting-state functional Magnetic Resonance Imaging (fMRI) data and The Virtual Brain (TVB) to characterise the excitatory/inhibitory balance of the brain. We applied the framework to a visuomotor brain subnetwork in a cohort of 9 healthy controls and 17 people with multiple sclerosis (pwMS). Acquired data included an event-related task fMRI experiment with variable grip force, resting-state fMRI, and diffusion-weighted imaging. The visuomotor network comprised the bilateral primary visual cortex (V1), left primary motor cortex (M1), supplementary motor and premotor cortex (SMAPMC), cingulate cortex (CC), superior parietal lobule (SPL), and right cerebellar lobule VI (CR). Results from DCM showed that while the overall network architecture was preserved in MS, there were significant alterations in the excitatory/inhibitory nature of effective connectivity: at rest, a statistical change was observed in CR-to-V1 connectivity, which was inhibitory in healthy volunteers but excitatory in MS. During task, effective connectivity feedback, including cerebellar self-connection, was positive in healthy volunteers but negative in MS and became increasingly dysregulated with higher motor demand. Alterations in functional and effective connectivity were associated with behavioural performance (task reaction time) and clinical measures (disability severity). At the overall group level, TVB parameters linked reduced NMDA-mediated excitatory gain to slower task responses. Moreover, integrating DCM and TVB demonstrated that higher global excitatory gain was associated with stronger task-engaged effective connectivity across sensorimotor and visuomotor pathways, linking network-level excitability captured by TVB to context-dependent reconfiguration of directed interactions and to connection-level strength revealed by DCM.

neuroscience↗

bioRxiv2018

Physiological motion of the carotid atherosclerotic plaque quantified using ultrasound B-Mode image analysis

BackgroundPhysical motion throughout the cardiac cycle may contribute to the rupture of the atherosclerotic carotid plaque, resulting in ischaemic stroke. The purpose of this study was to quantify the physiological motion of the atherosclerotic carotid plaque and to investigate any relationship between the quantified motion parameters and the degree of stenosis, greyscale plaque characteristics, and the presence of cerebrovascular symptoms.\n\nMethodsDisplacement, velocity and acceleration of 81 plaques (51% symptomatic, stenosis range 10%-95%) from 51 patients were measured using an automated system employing a block matching algorithm relative to the ultrasound probe and relative to the periadventitial tissues, over a mean duration of 5 cardiac cycles.\n\nResultsAveraged across all plaques, the displacement amplitude was 1.2 mm relative to the probe, and 0.35 mm relative to the periadventitial tissues. Maximum and mean plaque velocities were 4.7 and 1.3 mm/s relative to the ultrasound probe, and 2.4 and 0.70 mm/s relative to the periadventitial tissues. The corresponding acceleration magnitudes were 69 and 22 mm/s2 relative to the probe, and 57 and 18 mm/s2 relative to the periadventitial tissues. There were no significant differences in any of the motion parameters, with respect to the presence of cerebrovascular symptoms, and none of the parameters showed a statistically significant relationship to the degree of stenosis, and the greyscale plaque characteristics (p[≤]0.05). The technique used was able to detect plaque motion amplitudes above 50m.\n\nConclusionsThis study provides quantitative data on the physiological motion of the atherosclerotic carotid plaque in-vivo. No significant relationship was found between the measured motion parameters and the presence of cerebrovascular symptoms, the degree of stenosis, and the greyscale plaque characteristics.

biophysics↗