Adenauer Girardi Casali

The paper constructs a normative TMS-EEG database with reliability analysis and identifies reliable features for individual-level comparison.

This study uses TMS-EEG to find reduced alpha-band phase coherence and cortical complexity in fibromyalgia patients compared to healthy controls.

This study uses a BiLSTM machine learning model to distinguish TMS-evoked EEG responses from sham stimulations across multiple datasets, achieving high accuracy with few trials.

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 examines how acute pain affects local and global cortical excitability in motor and prefrontal areas, revealing interindividual differences in pain processing.

This study measures cortical response complexity to electrical stimulation in rats under different anaesthetics, finding reduced complexity and altered connectivity during anaesthesia.

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 shows that different TMS pulse waveforms and coil orientations activate distinct neural populations in the premotor cortex, as evidenced by variations in TEP components.