Stefano Moia

This study identifies early cerebrovascular reactivity impairments in 22q11.2DS as a biomarker for psychosis susceptibility, particularly in regions like the anterior cingulate cortex and globi pallidi.

The paper introduces NSI, an objective measure to assess data quality for precision functional MRI, aligning with expert evaluations and enabling principled decisions on data sufficiency.

The paper introduces Emo-FilM, a multimodal dataset combining fMRI, physiological recordings, and detailed emotion annotations from films to study emotion processing.

The paper examines individual variability in the relationship between resting-state fMRI metrics and cerebrovascular reactivity (CVR) using longitudinal data from 7 subjects with 10 sessions each.

This paper introduces a variational Bayesian approach for cerebrovascular reactivity mapping using fMRI data and compares it to a standard GLM method, showing improved computational efficiency and handling of noisy voxels.

This study evaluates ME-ICA's effectiveness in reducing task-correlated head motion artifacts in motor-task fMRI data, showing improved signal clarity and stability in both subject and group analyses.

The paper identifies a two-fold expansion of the frontostriatal salience network in individuals with depression using longitudinal neuroimaging data and shows its stability over time and predictive value for future symptoms.

This paper introduces a method using fMRI spectral signatures on high-resolution cortical graphs to improve individual identification by addressing limitations of conventional connectivity-based approaches.

This paper compares alternative reference signals for mapping cerebrovascular reactivity using breath-hold task BOLD fMRI, showing that RVT and GM-BOLD can produce comparable CVR maps when PETCO2 quality is insufficient.

The paper investigates how data acquisition and modelling choices affect the relationship between baseline cerebral blood flow and BOLD cerebrovascular reactivity, finding that breathing task data and lag-optimization improve correlations.

This paper modifies a resting-state fMRI protocol by adding breathing tasks to improve cerebrovascular reactivity (CVR) characterization and hemodynamic lag estimation.

This study evaluates ICA-based denoising strategies for improving CVR estimates in multi-echo BOLD fMRI during breath-hold tasks, finding that a conservative ICA model reduces motion effects best.

This paper introduces ME-SPFM, a deconvolution algorithm for multiecho fMRI that estimates transverse relaxation changes without prior event timing knowledge, showing high concordance with standard analysis.