Claudia A. M. Gandini Wheeler‐Kingshott

The paper uses virtual brain modelling to identify network-specific alterations in excitation/inhibition profiles in treatment-resistant schizophrenia and links them to symptom severity.

The paper presents a multiscale brain modelling framework combining DCM and TVB to study excitatory-inhibitory balance in multiple sclerosis, finding altered connectivity patterns and their association with clinical and behavioural outcomes.

This study uses brain digital twins to compare network changes in congenital and slowly progressive cerebellar ataxias, finding distinct patterns in network topology and dynamics that correlate with clinical symptoms.

The paper introduces Auto-MFM, a tool that automatically derives mean field models from spiking neural networks, accurately reproducing population dynamics and enabling exploration of physiological and pathological brain circuits.

This paper develops a region-specific mean field model for the cerebellum, improving virtual brain simulations of local and global dynamics compared to standard oscillators.

The paper uses DCM on fMRI data to show cerebellar control switches from excitatory to inhibitory during action execution versus observation, revealing distinct functional roles in motor planning and sensorimotor feedback.

This study shows body size parameters significantly correlate with brain and spinal cord MRI metrics and should be included in neuroimaging studies.

The paper proposes a method to quantify cerebral blood volume and intravascular water residence time using non-contrast MR fingerprinting, showing feasibility in vivo.

This paper introduces a multiscale modelling framework for hippocampal CA1 that bridges micro and macro scales using a novel mean-field model, validated against spiking network models.

The paper compares structural and connectivity parameters between non-progressive and slow-progressive cerebellar ataxia patients to identify compensation patterns in motor behavior.

The paper uses virtual brain simulations to compare network-specific parameters in Alzheimer's disease and Frontotemporal Dementia patients with healthy controls, revealing disease-specific alterations.

The paper investigates how parallel processing in the human brain relies on a distributed cortico-cerebellar architecture using fMRI data from dual-task experiments.

This study uses The Virtual Brain to simulate brain dynamics in neurodegenerative diseases, revealing differences in excitation/inhibition profiles that improve personalized diagnosis.

The paper investigates neurovascular coupling in the cerebellar cortex and finds non-linear frequency dependence due to competition between vasodilation and vasoconstriction pathways.

This study identifies specific white matter alterations in left and right temporal lobe epilepsy using diffusion imaging parameters and spatial statistical analysis.

This study compares two deep learning strategies for qMRI signal model fitting, finding that strategy 2 is more practical but may yield less accurate parameter estimation.

This study shows that multiple sclerosis alters higher-order BOLD responses in BA 4p but not BA 4a during grip force tasks, beyond the main effect of movement.

This paper introduces a unified signal readout approach for multi-parametric spinal cord MRI, combined with MP-PCA denoising, improving the quality and consistency of microstructural metrics.

This study investigates spinal cord atrophy in Alzheimer's disease and finds it contributes to distinguishing patients from controls and explains cognitive scores.

This paper investigates quantitative functional sodium imaging (fNaI) to measure 23Na concentration changes during motor tasks, showing sensitivity to distributed functional alterations in brain regions.

This study identifies the sequence of grey matter atrophy progression in multiple sclerosis using longitudinal MRI data and shows its association with disability accumulation in relapsing-remitting MS.

This study shows that deep grey matter volume loss predicts faster disability progression in multiple sclerosis, with specific patterns in different disease subtypes.