Anita Monteverdi

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 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.

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 introduces a 3D high-density CMOS multi-electrode array with microneedles for improved recording from 3D brain tissue and spheroids, showing enhanced signal quality and tissue vitality.

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.