Dimitrios Pantazis

This study uses frequency-tagging and machine learning to separate neural responses to mixed melodies, showing that musicality improves top-down attention and reduces bottom-up distractions.

This study investigates how the brain processes face identity, age, and gender across time and space using MEG data, revealing temporal hierarchies and task-dependent modulation.

This study uses hyperbolic neural networks to analyze MEG brain networks from the Cam-CAN dataset, revealing age-related hierarchical changes in brain subnetworks.

The paper introduces PATCH-AP, a source localization method for MEG that outperforms existing techniques in localizing both discrete and extended neural sources.

This study investigates the spatiotemporal evolution of braille letter representations in blind and sighted readers using MEG and pattern analysis, finding slower processing and a transformation from peripheral to high-level representations in blind individuals.

This study uses hyperbolic graph embedding to analyze MEG brain networks in individuals with subjective cognitive decline, identifying hierarchical differences linked to cognitive impairment.

This paper introduces FLEX-AP, an enhanced alternating projection method for localizing spatially extended brain sources, showing improved accuracy over existing methods.

This study uses MEG to investigate hierarchical brain mechanisms during auditory memory recognition and predictive coding, showing feedforward and backward connections and distinct power dynamics in different brain regions.

This study decodes hue and luminance polarity from MEG data, showing distinct temporal dynamics and neural mechanisms for each feature.

This study investigates error-monitoring failure in early Alzheimer's disease patients with subjective memory complaints, linking it to anosognosia.

The paper identifies a dual simultaneous processing mechanism in the human brain for temporal pattern recognition using MEG and MRI.

This study uses MEG to analyze neural activity patterns and decode color space geometry through similarity relationships in brain responses to different colors.

The paper investigates brain dynamics during musical pattern recognition using MEG, finding increased activity and connectivity in a widespread network over time.

This study investigates whether detecting social interactions is a rapid perceptual process or a slower post-perceptual inference using MEG decoding and computational modeling.

This paper quantifies functional brain connectomic changes in aMCI patients during cognitive training using a Gaussian embedding method, identifying key brain regions with significant variation.

The paper identifies an early and prolonged neural signal of memorability during visual processing using MEG, detected outside subjective awareness.

This study investigates the time course of face perception by analyzing neural responses to faces and finds that gender and age information emerge before identity information, with familiar faces showing enhanced early processing.

This study uses ultra-rapid serial visual presentation with MEG to distinguish feedforward and feedback processing stages in the ventral visual pathway.

This study compares multivariate pattern analysis of MEG and EEG data to assess their representational structures in time and space, finding convergent and unique insights into visual processing.

This study uses multivariate pattern analysis on MEG data to show that gamma oscillations encode orientation information, with stronger decoding for cardinal than oblique orientations.

This study uses MEG and deep neural networks to show that spatial layout processing in scene recognition occurs around 250ms and is captured by a deep neural network model.