Tommaso Costa

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.

A meta-analysis of areas of structural variation in grey matter in individuals with Autism Spectrum Disorder (ASD) in relation to gene expression of candidate ASD genes

This study correlates gene expression of ASD candidate genes with structural brain changes in ASD using meta-analysis and gene expression maps.

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.

Specific patterns of bold variability associated with the processing of pain stimuli

The paper uses multivoxel pattern analysis to show that BOLD signal variability distinguishes pain stimulation from rest conditions and reveals entropy differences across brain regions.

Boredom begets creativity: a solution to the exploitation-exploration trade-off in predictive coding

The paper explores whether predictive coding systems can exhibit creativity by incorporating boredom as a key factor in behavior.

The foraging brain: evidence of Levy dynamics in brain networks

This paper models fMRI signal dynamics using a generalized Langevin equation with stable noise, showing a spectrum of activity modes related to Levy motion in brain networks.

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.

Can mindfulness meditation alter consciousness? An integrative interpretation

This paper reviews hypotheses on mindfulness meditation's effects and cerebral correlates, proposing an integration with consciousness through shared brain areas.

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.