Sergio Duca

A minimum Bayes Factor based threshold for activation likelihood estimation

The paper introduces a Bayesian thresholding method for activation likelihood estimation (ALE) and demonstrates its equivalence to frequentist thresholds, showing that lower Bayesian thresholds are statistically valid but indicate weaker hypothesis support.

Default Mode Network spatial configuration varies across task domains

This study uses meta-analysis to show that the Default Mode Network (DMN) varies spatially across different task domains, revealing a gradient from internal to external functions.

A meta-analytic approach to mapping co-occurrent grey matter volume increases and decreases in psychiatric disorders

This paper uses a meta-analytic network mapping approach to show that gray matter volume increases and decreases in psychiatric disorders are statistically related across different brain regions.

Hubs of long-distance co-alteration in brain pathology

The paper analyzes co-alterations in brain pathology across disorders, finding that long-distance co-alterations identify key pathological hubs and relate to functional connectivity.

Addressing reverse inference in structural brain alterations

The paper uses Bayes factor analysis on voxel-based morphometry data to assess the specificity of brain alterations in schizophrenia and Alzheimer's disease, finding that more disease-specific areas are altered earlier.

NODE DETECTION USING HIGH-DIMENSIONAL FUZZY PARCELLATION APPLIED TO THE INSULAR CORTEX

The paper introduces a fuzzy c-mean clustering method to detect nodes in the insular cortex, revealing new functional connectivity patterns beyond existing models.

PREDICTABILITY OF AUTISM, SCHIZOPHRENIC AND OBSESSIVE SPECTRA DIAGNOSIS. TOWARD A DAMAGE NETWORK APPROACH

This study uses neuroimaging to challenge the distinction between autism, schizophrenia, and obsessive-compulsive disorders, finding common brain damage patterns and proposing a two-cluster damage network model.