Simone Sarasso

This study evaluates how neural complexity metrics relate to network architecture by simulating neural dynamics across diverse network structures and analyzing both observational and perturbational measures.

This paper introduces a non-invasive framework linking consciousness measures to non-equilibrium thermodynamics by analyzing FDT violations in humans and rodents across different states of consciousness.

This paper introduces a whole-brain model linking resting-state EEG activity to TMS-evoked responses, showing it can predict TEPs without time-domain simulations.

The paper analyzes TMS-evoked potentials (TEPs) from different cortical regions to characterize their temporal features and relates them to network properties.

This paper models post-lesional slow waves in brain networks, identifying mechanisms for their generation and propagation.

This paper introduces gTRCA, a method to extract reproducible TEP components across trials and subjects, showing it reliably identifies key features of motor TEPs in TMS-EEG data.

This study shows that TMS-evoked potentials (TEPs) can have distinct spatiotemporal patterns lasting up to 300 ms when targeting specific cortical areas, challenging the view that later components are due to sensory inputs.

The paper investigates how cortical stimulation engages subcortical circuits in mice and humans, showing similar evoked potentials and thalamic contributions across species.

This study examines the electrophysiological state of the isolated cortex after hemispherotomy in awake humans, finding sleep-like activity without spindles.

The paper compares ten ESI methods using in-vivo EEG data to evaluate their accuracy and parameter sensitivity in localizing focal brain sources.

This paper compares cortico-cortical evoked potentials (CCEPs) recorded via invasive SEEG and non-invasive hd-EEG during SPES, showing hd-EEG's sensitivity to stimulation parameters and its ability to capture whole-brain dynamics.

This study uses the Spectral Exponent (SE) to assess stroke recovery by comparing EEG metrics in patients and healthy controls over time.

TAAC generates customized masking noises to reduce auditory confounds in TMS-EEG studies, achieving effective masking at lower sound pressure levels than standard methods.

The paper introduces rt-TEP, a real-time visualization tool for TMS-evoked potentials that improves signal quality and parameter optimization.

This study shows that focal brain injuries lead to local sleep-like dynamics in the surrounding cortex, disrupting signal complexity while coexisting with wakefulness patterns.

This paper provides an open dataset of EEG recordings from precisely known brain locations to evaluate source localization methods.

The paper introduces PCIST, a fast method to estimate perturbational complexity of brain signals, validated on TMS/hd-EEG and SEEG data, showing comparable accuracy to the original PCI with improved speed and applicability.

This study links pathological bistability in UWS patients to reduced brain complexity using TMS/EEG and PCI measurements.

This study investigates how the spectral features of TEPs from M1 TMS depend on MEP amplitude, finding a late ERD linked to MEP strength.