Structural and functional pathology in cocaine use disorder with polysubstance use: A multimodal fusion approach structural-functional pathology in cocaine use disorder

Cocaine use disorder (CUD) is described as a compulsive urge to seek and consume cocaine despite the inimical consequences. MRI studies from different modalities have shown that CUD patients exhibit structural and/or functional connectivity pathology among several brain regions. Nevertheless, both connectivities are commonly studied and analyzed separately, which may potentially obscure its relationship between them, and with the clinical pathology. Here, we compare structural and functional brain networks in CUD patients and healthy controls (HC) using multimodal fusion. The sample consisted of 63 (8 females) CUD patients and 42 (9 females) healthy controls (HC), recruited as part of the SUDMEX CONN database. For this, we computed a battery of graph-based measures from multi-shell diffusion-weighted imaging and resting state fc-fMRI to quantify local and global connectivity. Then we used multimodal canonical component analysis plus joint independent component analysis (mCCA+jICA) to compare between techniques and evaluate group differences and its association with clinical alteration. Unimodal results showed a striatal decrease in the participation coefficient but applied supervised data fusion revealed other regions with cocaine-related alterations in joint functional communication. When performing multimodal fusion analysis, we observed a higher centrality of the interrelationship and a lower participation coefficient in patients with CUD. In contrast to the unimodal approach, the multimodal fusion method was able to reveal latent information about brain regions involved in impairment due to cocaine abuse. The present results could help in understanding the pathology of CUD to develop better pre-treatment/post-treatment intervention designs.

A Multimodal Fusion Analysis of Pretreatment Anatomical and Functional Cortical Abnormalities in Responsive and Non-responsive Schizophrenia

Background: Antipsychotic medications provide limited long-term benefit to ~30% of schizophrenia patients. Multimodal magnetic resonance imaging (MRI) data have been used to investigate brain features between responders and nonresponders to antipsychotic treatment; however, these analytical techniques are unable to weigh the interrelationships between modalities. Here, we used multiset canonical correlation and joint independent component analysis (mCCA + jICA) to fuse MRI data to examine the shared and specific multimodal features between the patients and healthy controls (HCs) and between the responders and non-responders. Method: Resting-state functional and structural MRI data were collected from 55 patients with drug-naïve first-episode schizophrenia (FES) and demographically matched HCs. Based on the decrease in Positive and Negative Syndrome Scale scores from baseline to the 1-year follow-up, FES patients were divided into a responder group (RG) and a non-responder group (NRG). Gray matter volume (GMV), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo) maps were used as features in mCCA + jICA. Results: Between FES patients and HCs, there were three modality-specific discriminative independent components (ICs) showing the difference in mixing coefficients (GMV-IC7, GMV-IC8, and fALFF-IC5). The fusion analysis indicated one modality-shared IC (GMV-IC2 and ReHo-IC2) and three modality-specific ICs (GMV-IC1, GMV-IC3, and GMV-IC6) between the RG and NRG. The right postcentral gyrus showed a significant difference in GMV features between FES patients and HCs and modality-shared features (GMV and ReHo) between responders and nonresponders. The modality-shared component findings were highlighted by GMV, mainly in the bilateral temporal gyrus and the right cerebellum associated with ReHo in the right postcentral gyrus. Conclusions: This study suggests that joint anatomical and functional features of the cortices may reflect an early pathophysiological mechanism that is related to a 1-year treatment response.

Patterns of co-altered brain structure and function underlying neurological soft signs in schizophrenia spectrum disorders

Neurological soft signs (NSS) comprise a broad range of subtle neurological deficits and are considered to represent external markers of sensorimotor dysfunction frequently found in mental disorders of presumed neurodevelopmental origin. Although NSS frequently occur in schizophrenia spectrum disorders (SSD), specific patterns of co-altered brain structure and function underlying NSS in SSD have not been investigated so far. It is unclear whether gray matter volume (GMV) alterations or aberrant brain activity or a combination of both, are associated with NSS in SSD. Here, 37 right-handed SSD patients and 37 matched healthy controls underwent motor assessment and magnetic resonance imaging (MRI) at 3 T. NSS were examined on the Heidelberg NSS scale. We used a multivariate data fusion technique for multimodal MRI data-multiset canonical correlation and joint independent component analysis (mCCA + jICA)-to investigate co-altered patterns of GMV and intrinsic neural fluctuations (INF) in SSD patients exhibiting NSS. The mCCA + jICA model indicated two joint group-discriminating components (temporoparietal/cortical sensorimotor and frontocerebellar/frontoparietal networks) and one modality-specific group-discriminating component (p < .05, FDR corrected). NSS motor score was associated with joint frontocerebellar/frontoparietal networks in SSD patients. This study highlights complex neural pathomechanisms underlying NSS in SSD suggesting aberrant structure and function, predominantly in cortical and cerebellar systems that critically subserve sensorimotor dynamics and psychomotor organization.