Georgios D. Mitsis

Denoising the central autonomic network: characterizing processes jointly associated with arousal and non-neuronal physiological artefacts in dynamic fMRI analyses

This study investigates how denoising systemic low frequency oscillations affects dynamic signatures of central autonomic regulation and their relation to physiological states using multimodal data.

When Can Brain Connectivity Track the Working Mind? A Large-Scale Benchmark of Dynamic Functional Connectivity Across Cognitive Paradigms

This study benchmarks seven dynamic functional connectivity methods across 16 fMRI datasets to assess their reliability in tracking cognitive engagement during various tasks.

Spatiotemporal Propagation of Sensorimotor Beta Bursts Across Adulthood

This study examines how beta bursts propagate across the cortex during motor tasks and rest, finding age-related changes in propagation patterns and their correlation with receptor distributions.

Investigating the variability of physiological response functions across individuals and brain regions in functional magnetic resonance imaging

This study examines how physiological response functions (PRFs) vary across individuals and brain regions in fMRI data and shows that allowing spatial and subject-specific variability improves PRF model performance.

Global signal regression reduces connectivity patterns related to physiological signals and does not alter EEG-derived connectivity

This study examines the impact of global signal regression on resting-state fMRI connectivity, finding it reduces physiological artifacts while preserving electrophysiological connectivity patterns.

Towards the implementation and interpretation of masked ICA for identifying signatures of autonomic activation in the brainstem with resting-state BOLD fMRI

This study evaluates masked ICA (mICA) for identifying autonomic activation signatures in the brainstem using resting-state BOLD fMRI, showing that cerebrospinal fluid denoising significantly improves results.

Investigation of the effect of physiological factors on resting-state and task-based functional connectivity

This study evaluates how physiological factors affect functional connectivity in brain signals, finding that multivariate methods are more robust than bivariate ones and that physiological artifacts significantly distort connectivity estimates.

On the variability of dynamic functional connectivity assessment methods

This study evaluates the variability of dynamic functional connectivity methods using fMRI data, showing significant differences between methods and emphasizing the need for multi-analysis approaches.

A calibration and uncertainty quantification analysis of classical, fractional and multiscale logistic models of tumour growth

This study evaluates classical, fractional, and multiscale logistic models of tumour growth using Bayesian inference and uncertainty quantification to assess their fit under different treatment conditions.

Quantifying the Morphology and Mechanisms of Cancer Progression in 3D in-vitro environments: Integrating Experiments and Multiscale Models

This study integrates experimental and computational approaches to quantify cancer morphology and mechanisms in 3D cultures using a multiscale model and spatial analysis.

Bringing language to dynamic brain states: the default network dominates neural responses to evolving movie stories

The paper uses natural language processing to analyze how brain states respond to movie narratives, finding the default network is most involved in semantic integration.

Modeling the hemodynamic response function using EEG-fMRI data during eyes-open resting-state conditions and motor task execution

This paper models the hemodynamic response function using EEG-fMRI data during resting-state and motor tasks, finding frequency-specific and region-specific contributions to BOLD signal variance.

A multi-measure approach for assessing the performance of fMRI preprocessing strategies in resting-state functional connectivity

The paper evaluates fMRI preprocessing strategies using a multi-measure framework to assess their impact on data quality, finding that removing global signal and 17% of white matter components improves QC metrics most.

Physiological noise modeling in fMRI based on the pulsatile component of photoplethysmograph

This study introduces a new cardiac pulsatility model (CPM) for fMRI noise correction, showing it outperforms existing methods in explaining fMRI signal variance.

Physiological and head motion signatures in static and time-varying functional connectivity and their subject discriminability

The paper investigates how physiological and motion processes affect functional connectivity and subject identifiability using fMRI data from the Human Connectome Project.

Estimating brain age from structural MRI and MEG data: Insights from dimensionality reduction techniques

This study combines structural MRI and MEG data to predict brain age using dimensionality reduction techniques, finding that a stacked model outperforms individual modalities.

Phase dynamics of cerebral blood flow in subarachnoid haemorrhage in response to sodium nitrite infusion

This study examines how sodium nitrite affects cerebral blood flow phase synchronisation in SAH patients, finding increased synchronisation in those without delayed cerebral ischemia.

Modeling the hemodynamic response function using simultaneous EEG-fMRI data and convolutional sparse coding analysis with rank-1 constraints

This paper proposes using simultaneous EEG-fMRI and convolutional sparse coding to model the hemodynamic response function, finding that lower amplitude BOLD peaks also contain important activity information.

Identification of Physiological Response Functions to Correct for Fluctuations in Resting-State fMRI related to Heart Rate and Respiration

This paper develops a framework to estimate physiological response functions (PRF) for resting-state fMRI, showing they vary across subjects and sessions and are linked to heart rate and breathing patterns.

Modeling of dynamic cerebrovascular reactivity to spontaneous and externally induced CO2 fluctuations in the human brain using BOLD-fMRI

This paper models dynamic cerebrovascular reactivity to CO2 fluctuations using BOLD-fMRI, revealing regional variability and distinct dCVR patterns under different conditions.