Esther Florin

This study shows that endogenous pain inhibition in humans increases with certainty about action-outcome relationships during a gambling task involving pain relief and punishment.

This study manipulates GABA and NMDA receptors in humans to show that GABAergic inhibition increases neuronal timescales and alters large-scale network dynamics.

This study shows that aperiodic broadband power, not just beta oscillations, is linked to Parkinson's disease severity and is increased in the more affected hemisphere.

The paper shows that spontaneous brain network transitions during the pre-stimulus period predict correct or incorrect somatosensory perception in an ambiguous tactile task.

This paper introduces sMVGC, a sparse multivariate Granger causality method that improves scalability for causal inference in high-dimensional electrophysiological data.

This study compares DBS artefacts in MEG recordings using different DBS devices and cleaning methods, finding device-specific differences and potential spectral artefacts after cleaning.

This study tests the compatibility of telemetric LFP streaming with MEG in DBS patients, finding that Percept PC with SenSight leads generates limited interference and OPM systems are more resilient to artefacts.

This study examines how subthalamic stimulation-evoked cortical responses correlate with motor performance in Parkinson's disease patients.

This study uses simulated whole-brain connectomes to classify Parkinson's disease patients against healthy controls, showing improved classification when combining empirical and simulated data.

The paper investigates cortical oscillatory activity in atypical parkinsonian syndromes and finds that slowing of frontocentral beta oscillations distinguishes these syndromes from healthy controls and idiopathic Parkinson's disease.

The paper evaluates two methods for separating neural oscillations from aperiodic 1/f activity in electrophysiological data, highlighting challenges and providing recommendations.

This study examines how dopaminergic medication affects oscillatory brain networks in Parkinson's disease using combined STN and MEG recordings.

This study compares two MEG analysis methods for extracting resting state networks and finds that phase-amplitude coupling provides better alignment with fMRI results than Hilbert envelope ICA.

This study investigates brain network dynamics during pitch change detection, showing slow oscillations and phase-amplitude coupling in auditory and motor regions, with differences in amusia.

The paper shows that variability in stimulus-induced gamma responses is linked to spontaneous brain network states, with both trial-to-trial and subject-to-subject differences explained by pre-stimulus network dynamics.

This paper introduces a new source imaging method for MEG/EEG data that equalizes contributions of oscillatory sources consistent with experimental hypotheses, improving detection in noisy conditions.

This paper introduces a wavelet-based method to separate LFP signals into volume-conducted, local coherent, and local incoherent components, showing its application in Parkinson's disease data.