Functional network interactions in patients with schizophrenia with persistent auditory verbal hallucinations: A multimodal MRI fusion approach using three-way pICA.

Over the last decade, there have been an increasing number of functional magnetic resonance imaging (fMRI) studies examining brain activity in schizophrenia (SZ) patients with persistent auditory verbal hallucinations (AVH) using either task-based or resting-state fMRI (rs-fMRI) paradigms. Such data have been conventionally collected and analyzed as distinct modalities, disregarding putative crossmodal interactions. Recently, it has become possible to incorporate two or more modalities in one comprehensive analysis to uncover hidden patterns of neural dysfunction not sufficiently captured by separate analysis. A novel multivariate fusion approach to multimodal data analysis, i.e., parallel independent component analysis (pICA), has been previously shown to be a powerful tool in this regard. We utilized three-way pICA to study covarying components among fractional amplitude of low-frequency fluctuations (fALFF) for rs-MRI and task-based activation computed from an alertness and a working memory (WM) paradigm of 15 SZ patients with AVH, 16 non-hallucinating SZ patients (nAVH), and 19 healthy controls (HC). The strongest connected triplet (false discovery rate (FDR)-corrected pairwise correlations) comprised a frontostriatal/temporal network (fALFF), a temporal/sensorimotor network (alertness task), and a frontoparietal network (WM task). Frontoparietal and frontostriatal/temporal network strength significantly differed between AVH patients and HC. Phenomenological features such as omnipotence and malevolence of AVH were associated with temporal/sensorimotor and frontoparietal network strength. The transmodal data confirm a complex interplay of neural systems subserving attentional processes and cognitive control interacting with speech and language processing networks. In addition, the data emphasize the importance of sensorimotor regions modulating specific symptom dimensions of AVH.

Structure/function interrelationships and illness insight in patients with schizophrenia: a multimodal MRI data fusion study.

Illness insight in schizophrenia (SZ) has an important impact on treatment outcome, integration into society and can vary over the course of the disorder. To deal with and treat reduced or absent illness insight, we need to better understand its functional and structural correlates. Previous studies showed regionally abnormal brain volume in brain areas related to cognitive control and self-reference. However, little is known about associations between illness insight and structural and functional network strength in patients with SZ. This study employed a cross-sectional design to examine structural and functional differences between patients with SZ (n = 74) and healthy controls (n = 47) using structural and resting-state functional magnetic resonance imaging (MRI). Voxel-based morphometry was performed on structural data, and the amplitude of low frequency fluctuations (ALFF) was calculated for functional data. To investigate abnormal structure/function interrelationships and their association with illness insight, we used parallel independent component analysis (pICA). Significant group (SZ vs. HC) differences were detected in distinct structural and functional networks, predominantly comprising frontoparietal, temporal and cerebellar regions. Significant associations were found between illness insight and two distinct structural networks comprising frontoparietal (pre- and postcentral gyrus, inferior parietal lobule, thalamus, and precuneus) and posterior cortical regions (cuneus, precuneus, lingual, posterior cingulate, and middle occipital gyrus). Finally, we found a significant relationship between illness insight and functional network comprising temporal regions (superior temporal gyrus). This study suggests that aberrant structural and functional integrity of neural systems subserving cognitive control, memory and self-reference are tightly coupled to illness insight in SZ.

Structural Correlates of Lifetime Voice-Hearing in Patients with Borderline Personality Disorder: A Pilot Study.

INTRODUCTION: Auditory verbal hallucinations (AVH) are transdiagnostic phenomena that can occur in several mental disorders, including borderline personality disorder (BPD). Despite the transdiagnostic relevance of these symptoms, very little is known about neural signatures of AVH in BPD. METHODS: We used structural magnetic resonance imaging to investigate multiple markers of brain morphology in BPD patients presenting with a lifetime history of AVH (AVH, n = 6) versus BPD patients without AVH (nAVH, n = 10) and healthy controls (HC, n = 12). The Computational Anatomy Toolbox (CAT12) was used for surface-based morphometric analyses that considered cortical thickness (CTh), gyrification (CG), and complexity of cortical folding (CCF). Factorial models were used to explore differences between AVH patients and HC, as well as between the patient groups. RESULTS: Compared to HC, AVH patients showed distinct abnormalities in key regions of the language network, i.e., aberrant CTh and CG in right superior temporal gyrus and abnormal CCF in left inferior frontal gyrus. Further abnormalities were found in right prefrontal cortex (CTh) and left orbitofrontal cortex (CCF). Compared to nAVH patients, individuals with AVH showed abnormal CTh in right prefrontal cortex, along with CCF differences in right transverse temporal, superior parietal, and parahippocampal gyri. CG differences between the patient groups were found in left orbitofrontal cortex. CONCLUSION: The data suggest a transdiagnostic neural signature of voice-hearing that converges on key regions involved in speech generation and perception, memory and executive control. It is possible that cortical features of distinct evolutionary and genetic origin, i.e., CTh and CG/CCF, differently contribute to AVH vulnerability in BPD.

Cortical morphology and illness insight in patients with schizophrenia.

Insight into illness in schizophrenia (SZ) patients has a major impact on treatment adherence and outcome. Previous studies have linked distinct deviations of brain structure to illness insight, specifically in frontoparietal and subcortical regions. Some of these abnormalities are thought to reflect aberrant cortical development. In this study, we used cross-sectional data to examine associations between illness insight and two cortical surface markers that are known to follow distinct neurodevelopmental trajectories, i.e. cortical gyrification (CG) and thickness (CT). CG and CT was investigated in SZ patients (n = 82) and healthy controls (HC, n = 48) using 3 T structural magnetic resonance imaging. Illness insight in SZ patients was measured using the OSSTI scale, an instrument that provides information on two distinct dimensions of illness insight, i.e. treatment adherence (OSSTI-A) and identification of disease-related symptoms (OSSTI-I). CT and CG were computed using the Computational Anatomy Toolbox (CAT12). Whole-brain and regions-of-interest (ROI)-based analyses were performed. SZ patients showed higher CG in anterior cingulate, superior frontal and temporal gyrus and reduced CG in insular and superior frontal cortex when compared to HC. SZ patients showed decreased CT in pre- and paracentral, occipital, cingulate, frontoparietal and temporal regions. Illness insight in SZ patients was significantly associated with both CG and CT in the left inferior parietal lobule (OSSTI-A) and the right precentral gyrus (CG/OSSTI-A, CT/OSSTI-I). The data support a multi-parametric neuronal model with both pre- and postnatal brain developmental factors having an impact on illness insight in patients with SZ.

Structural alterations in brainstem, basal ganglia and thalamus associated with parkinsonism in schizophrenia spectrum disorders.

The relative roles of brainstem, thalamus and striatum in parkinsonism in schizophrenia spectrum disorder (SSD) patients are largely unknown. To determine whether topographical alterations of the brainstem, thalamus and striatum contribute to parkinsonism in SSD patients, we conducted structural magnetic resonance imaging (MRI) of SSD patients with (SSD-P, n = 35) and without (SSD-nonP, n = 64) parkinsonism, as defined by a Simpson and Angus Scale (SAS) total score of ≥ 4 and < 4, respectively, in comparison with healthy controls (n = 20). FreeSurfer v6.0 was used for segmentation of four brainstem regions (medulla oblongata, pons, superior cerebellar peduncle and midbrain), caudate nucleus, putamen and thalamus. Patients with parkinsonism had significantly smaller medulla oblongata (p = 0.01, false discovery rate (FDR)-corrected) and putamen (p = 0.02, FDR-corrected) volumes when compared to patients without parkinsonism. Across the entire patient sample (n = 99), significant negative correlations were identified between (a) medulla oblongata volumes and both SAS total (p = 0.034) and glabella-salivation (p = 0.007) scores, and (b) thalamic volumes and both SAS total (p = 0.033) and glabella-salivation (p = 0.007) scores. These results indicate that brainstem and thalamic structures as well as basal ganglia-based motor circuits play a crucial role in the pathogenesis of parkinsonism in SSD.