Structure/function interrelationships in patients with schizophrenia who have persistent auditory verbal...

Area of Science:

• Neuroimaging
• Psychiatry
• Computational Neuroscience

Background:

• Schizophrenia patients with auditory verbal hallucinations (AVH) exhibit known structural and functional brain abnormalities.
• The direct links between these altered brain structures and functions in AVH remain unclear.
• Advanced data-driven fusion methods can uncover neural dysfunction patterns missed by analyzing modalities separately.

Purpose of the Study:

• To investigate the interrelationships between structural and functional brain changes in schizophrenia patients with and without AVH.
• To utilize parallel independent component analysis (p-ICA) to fuse structural MRI (sMRI) and resting-state fMRI (rs-fMRI) data.
• To explore associations between identified brain components and clinical symptom dimensions.

Main Methods:

• Employed parallel independent component analysis (p-ICA) to analyze gray matter volume (sMRI) and fractional amplitude of low-frequency fluctuations (fALFF) from rs-fMRI.
• Studied 15 schizophrenia patients with AVH, 16 non-hallucinating schizophrenia patients (nAVH), and 19 healthy controls (HC).
• Correlated imaging components with clinical data from the Psychotic Symptoms Rating Scale (PSYRATS).

Main Results:

• A significant correlation was found between a specific sMRI component (fronto-temporo-parietal regions) and an rs-fMRI component (temporal cortex, cortical midline regions).
• This structural-functional link differed significantly between the AVH and nAVH groups.
• Distinct rs-fMRI components correlated with physical (parietal network) and emotional (posterior cingulate/temporal cortex network) dimensions of AVH symptoms.

Conclusions:

• AVH in schizophrenia are associated with specific interrelationships between intrinsic brain network activity and gray matter volume.
• These findings suggest AVH-specific structural-functional coupling.
• Modality-specific associations link brain networks to distinct dimensions of AVH symptomatology.