Jan‐Mathijs Schoffelen

This study shows that learned visual priorities from instrumental learning influence perceptual inference in an unrelated audiovisual task, shifting sound perception toward previously relevant visual targets.

The paper examines how inter-subject correlations (ISC) and their behavioral associations vary across different movies, highlighting the lack of generalizability across stimuli.

This study shows that defensive freezing enhances threat-reward processing in the dACC during approach-avoidance decisions, improving decision-making under threat.

This paper shows that CSF-filled cavities significantly affect scalp EEG amplitude and topography, making group comparisons difficult to interpret without accounting for this confounding factor.

This paper introduces a new analysis scheme to improve the robustness of non-invasive functional connectivity assessment by addressing signal leakage and baseline assumptions.

This paper introduces a strategy to automate the creation of standardized MATLAB scripts for EEG/MEG analysis using the FieldTrip toolbox, improving reproducibility with minimal user effort.

This study investigates how attention affects auditory and visual processing and their integration during multimodal communication using MEG and RIFT.

This study uses brain recordings and a deep neural network to show that predictions occur at multiple levels during language comprehension.

This study examines how syntactic complexity affects sentence processing in the human brain across speech and reading, identifying supramodal and modality-specific neural responses in over 200 participants.

This paper compares frequency-domain connectivity measures for cerebro-peripheral analysis using simulated and real MEG data, finding that wppc and gcmi perform best overall.

This study shows that pre-stimulus alpha-band activity in occipital-parietal regions enhances perceptual sensitivity and information content in visual detection tasks.

The paper investigates how lexical frequency and sentence context affect brain responses to words using MEG data, finding frequency has independent effects while context influences brain signals differently.

This study uses MEG and MVPA to investigate if the brain encodes hierarchical linguistic structure during sentence comprehension, finding no evidence of such representations.

This study investigates brain activity during the processing of adjective-noun phrases in Dutch using MEG, finding no composition effect in LATL despite previous reports.

The paper investigates whether sustained attention modulates visual stimulus representation in a rhythmic way by analyzing MEG signals and decoding visual orientation.

The paper examines how pre-stimulus cortical synchrony relates to behavior during a Simon task, finding no significant differences in synchrony that explain behavioral outcomes.

The paper shows that the peak frequency of brain oscillations decreases along the posterior-anterior axis in the human cortex, aligning with cortical hierarchy and thickness.

This study uses MEG and computational language models to show that brain activity in specific regions correlates with contextualized vs. non-contextualized word embeddings during language comprehension.

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.

The paper identifies a brain network for language processing that is independent of sensory modality by analyzing neuromagnetic signals from reading and listening tasks.

This study investigates whether alpha/beta oscillations reflect language prediction by measuring neural responses to sentences with varying predictability levels, finding non-monotonic power modulations that suggest a role in attention or control rather than direct prediction.

The paper investigates brain rhythms during attention shifting and deployment in macaques, finding distinct frequency band modulations in different brain areas.

This study investigates altered oscillatory connectivity in the visual system of individuals with autism spectrum disorder, finding reduced feedback connectivity and local processing dysregulation.

This study examines how theta and beta brain oscillations relate to language prediction metrics during auditory narrative comprehension.

The paper shows that higher gamma-band power before a visual stimulus predicts stronger evoked responses and faster reaction times.

The paper describes a protocol for integrating anatomical and electrophysiological human intracranial EEG data using an open-source toolbox, enabling rapid and reproducible analysis.

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

This study shows that stimulus familiarity and expectation independently suppress neural activity in the visual ventral stream, with familiarity also sharpening response dynamics in early visual cortex.

The paper shows that even advanced MEG/EEG connectivity measures can produce false positive 'ghost' interactions due to signal mixing, and quantifies this effect through simulations.

The paper uses CNNs to model visual object recognition in MEG data, showing a feedforward sweep across the visual hierarchy and achieving high decoding accuracy.