Denis Schwartz

Detecting movement preparation with HYDRE: a hybrid model of temporal and spectral brain signals

This study introduces HYDRE, a hybrid model combining temporal, spectral, and Riemannian features to decode motor preparation from brain signals, achieving above-chance decoding up to 1400ms before movement.

Distinct beta burst motifs exhibit opposing error relationships during motor adaptation

Dynamic and task-dependent decoding of the human attentional spotlight from MEG

This study uses MEG and machine learning to decode spatial attention in humans during different tasks, showing dynamic, task-dependent attentional patterns similar to those in non-human primates.

Cerebral plasticity after hypoglosso-facial anastomosis in facial palsy: a magnetoencephalography study

This study uses MEG to investigate cerebral plasticity in patients who underwent hypoglosso-facial anastomosis, finding altered somatotopy compared to healthy controls.

The Mismatch Negativity compared: EEG, SQUID-MEG and novel 4Helium-OPMs

The paper compares EEG, SQUID-MEG, and 4Helium-OPMs in measuring auditory mismatch negativity using a passive oddball paradigm, finding comparable performance across all modalities.

Beta burst waveform extraction using novel 4He-OPMs

The paper develops a beta burst extraction pipeline using Helium-OPMs to study motor preparation and execution, finding similar waveform patterns to SQUID-MEG with task-related modulations.

Multilayer MEG source modelling enables depth-resolved laminar inference in humans

This paper introduces a multilayer MEG source modelling framework to enable depth-resolved laminar inference in humans, showing it aligns with known neural circuit motifs.

NIRSTORM: a Brainstorm extension dedicated to functional Near Infrared Spectroscopy (fNIRS) data analysis, advanced 3D reconstructions, and optimal probe design.

NIRSTORM extends Brainstorm for fNIRS analysis, offering 3D hemodynamic reconstructions and optimal probe design within a multimodal framework.

Emergence of Anticipatory Beta Activity to Facilitate Behavioral Stability Following Environmental Changes

The paper shows that beta activity in a cerebello-cortical network predicts performance based on prior outcomes, facilitating behavioral stability during environmental changes.

Measuring Neuronal Avalanches to inform Brain-Computer Interfaces

This study uses neuronal avalanches to improve brain-computer interfaces by showing their task-specific differences can be decoded better than current methods.

Auditory selective attention during a working memory task with melodies: a MEG study

This study investigates how auditory working memory and selective attention interact during a melody-based task using MEG, finding reciprocal influences between the two processes.

Diverse beta burst waveform motifs characterize movement-related cortical dynamics

The paper identifies diverse beta burst waveform motifs in human MEG data during movement tasks and shows they reflect distinct computational processes.

Theta band-power shapes amyloid-driven longitudinal EEG changes in pre-clinical Alzheimer's Disease

The paper examines longitudinal EEG changes in pre-clinical Alzheimer's Disease, finding increased theta-band power in specific brain regions in amyloid-positive individuals.

Functional disconnection of associative cortical areas predicts performance during BCI learning

This study shows that increased task-related activity and reduced connectivity between non-targeted brain regions predict better performance during BCI learning.