Fulvia Palesi

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 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.

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

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

The paper evaluates tractography reproducibility using empirical data from a single healthy volunteer scanned on two scanners, finding high consistency among top algorithms but variability due to tract volume containment.

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.