Vladimir Litvak A

This paper validates EEG beamforming for separating heartbeat-evoked potentials (HEP) from cardiac artefact (CA) using simulated and empirical data, showing reliable recovery and group differences in interoceptive regions.

This study validates MEG's ability to measure neural activity across frequency and depth using intracranial EEG data from epileptic patients, showing strong agreement for lower frequencies and superficial sources, and sensitivity to deep structures like the hippocampus.

This study shows lesion network maps still recover ground-truth networks despite low-dimensional bias and proposes a modification to reduce this bias.

The paper uses intracranial recordings from patients with chronic cluster headache to show that the human VTA encodes reward-related signals during learning.

The paper introduces a Caring Attributions task and identifies valence-partitioned temporal-difference Bayesian inference as a new neurocomputational mechanism for judging others' care or lack thereof.

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 identifies a frequency-following response in the subthalamic nucleus using auditory stimuli, suggesting potential for non-invasive deep brain stimulation.

This paper predicts subthalamic nucleus beta bursts in Parkinson's disease using deep learning, identifying a predictive biomarker for burst onset.

This paper develops and evaluates a radiation-free EEG framework to estimate directional DBS lead orientation in phantoms and human data, achieving sub-5 degree accuracy.

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.

The paper compares two models for simulating brain activity across modalities, showing they can replicate functional connectivity and dynamics but with varying performance across modalities.

The paper shows that metastable oscillatory modes in the brain emerge from synchronization in the spacetime connectome, matching MEG data from healthy individuals.

The paper examines neural correlates of conflict and evidence integration during sequential decision making, finding increased cortico-subthalamic coherence and prolonged subthalamic beta oscillations during conflict.

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

This paper demonstrates how connectivity in the cortico-basal-ganglia circuit influences beta oscillations and shows that phase-locked stimulation can modulate these oscillations based on network state.

This paper introduces a framework using Approximate Bayesian Computation to infer large-scale brain networks from empirical data, demonstrating its ability to identify generating models and estimate parameters accurately.

The paper investigates how cortical beta oscillations reflect contextual gating of visual action feedback during sensorimotor integration using MEG and virtual reality.

The paper examines the structural and functional connectivity of the nucleus basalis of Meynert in Parkinson's disease dementia and Lewy body dementia using MEG and MRI tractography.

The paper identifies signatures of the hyperdirect pathway and its role in pathological network disruption in Parkinson's disease through multimodal analysis.

The paper investigates how sedation with propofol affects predictive coding circuits and the double surprise acceleration effect using EEG source localization in a local-global task.

This paper validates and compares Non-Parametric Directionality (NPD) with Non-Parametric Granger Causality (NPG) for estimating directed functional connectivity in neural data, showing NPD's robustness to common confounds.

This study compares LCMV beamformer implementations across four MEG toolboxes, finding reliable source localization at typical SNR but differences in sensitivity to preprocessing parameters and SNR effects.

MEG-BIDS extends the BIDS standard to organize MEG data, enabling efficient storage, sharing, and integration with MRI data.

The paper investigates changes in directed connectivity within cortico-basal ganglia networks in Parkinsonian rats following dopamine depletion, finding dopamine-dependent beta and gamma rhythms and altered connections.