Source-based morphometry of gray matter volume in patients with schizophrenia who have persistent auditory verbal hallucinations

Grey matter volume reduction in the frontotemporal cortex associated with persistent verbal auditory hallucinations in Chinese patients with chronic schizophrenia: Insights from a 3 T magnetic resonance imaging study

BACKGROUND

Persistent auditory verbal hallucinations (pAVHs) are a fundamental manifestation of schizophrenia (SCZ), yet the exact connection between pAVHs and brain structure remains contentious. This study aims to explore the potential correlation between pAVHs and alterations in grey matter volume (GMV) within specific brain regions among individuals diagnosed with SCZ.

METHODS

76 SCZ patients with pAVHs (pAVH group), 57 SCZ patients without AVHs (non-AVH group), and 83 healthy controls (HC group) were investigated using 3 T magnetic resonance imaging. The P3 hallucination item of the Positive and Negative Syndrome Scale was used to assess the severity of pAVHs. Voxel-based morphometry was used to analyze the GMV profile between the three groups.

RESULTS

Compared to the non-AVH and HC groups, the pAVH group exhibited extensive reduction in GMV within the frontotemporal cortex. Conversely, no significant difference in GMV was observed between the non-AVH and HC groups. The severity of pAVHs showed a negative correlation with GMV in several regions, including the right fusiform, right inferior temporal, right medial orbitofrontal, right superior frontal, and right temporal pole (p = 0.0036, Bonferroni correction). Stepwise linear regression analysis revealed that GMV in the right temporal pole (β = -0.29, p = 0.001) and right fusiform (β = -0.21, p = 0.01) were significantly associated with the severity of pAVHs.

CONCLUSIONS

Widespread reduction in GMV is observed within the frontotemporal cortex, particularly involving the right temporal pole and right fusiform, which potentially contribute to the pathogenesis of pAVHs in individuals with chronic SCZ.

Elevated intrinsic cortical curvature in treatment-resistant schizophrenia: Evidence of structural deformation in functional connectivity areas and comparison with alternate indices of structure

BACKGROUND

Research suggests structural and connectivity abnormalities in patients with treatment-resistant schizophrenia (TRS) compared to first-line responders and healthy-controls. However, measures of these abnormalities are often influenced by external factors like nicotine and antipsychotics, limiting their clinical utility. Intrinsic-cortical-curvature (ICC) presents a millimetre-scale measure of brain gyrification, highly sensitive to schizophrenia differences, and associated with TRS-like traits in early stages of the disorder. Despite this evidence, ICC in TRS remains unexplored. This study investigates ICC as a marker for treatment resistance in TRS, alongside structural indices for comparison.

METHODS

We assessed ICC in anterior cingulate, dorsolateral prefrontal, temporal, and parietal cortices of 38 first-line responders, 30 clozapine-resistant TRS, 37 clozapine-responsive TRS, and 52 healthy-controls. For comparative purposes, Fold and Curvature indices were also analyzed.

RESULTS

Adjusting for age, sex, nicotine-use, and chlorpromazine equivalence, principal findings indicate ICC elevations in the left hemisphere dorsolateral prefrontal (p < 0.001, η2partial = 0.142) and temporal cortices (LH p = 0.007, η2partial = 0.060; RH p = 0.011, η2partial = 0.076) of both TRS groups, and left anterior cingulate cortex of clozapine-resistant TRS (p = 0.026, η2partial = 0.065), compared to healthy-controls. Elevations that correlated with reduced cognition (p = 0.001) and negative symptomology (p < 0.034) in clozapine-resistant TRS. Fold and Curvature indices only detected group differences in the right parietal cortex, showing interactions with age, sex, and nicotine use. ICC showed interactions with age.

CONCLUSION

ICC elevations were found among patients with TRS, and correlated with symptom severity. ICCs relative independence from sex, nicotine-use, and antipsychotics, may support ICC's potential as a viable marker for TRS, though age interactions should be considered.

Correlation Between Cortical Thickness Abnormalities of the Olfactory Sulcus and Olfactory Identification Disorder and Persistent Auditory Verbal Hallucinations in Chinese Patients With Chronic Schizophrenia

BACKGROUND AND HYPOTHESIS

Persistent auditory verbal hallucinations (pAVHs) and olfactory identification impairment are common in schizophrenia (SCZ), but the neuroimaging mechanisms underlying both pAVHs and olfactory identification impairment are unclear. This study aimed to investigate whether pAVHs and olfactory identification impairment in SCZ patients are associated with changes in cortical thickness.

STUDY DESIGN

In this study, cortical thickness was investigated in 78 SCZ patients with pAVHs (pAVH group), 58 SCZ patients without AVHs (non-AVH group), and 83 healthy controls (HC group) using 3T magnetic resonance imaging. The severity of pAVHs was assessed by the Auditory Hallucination Rating Scale. Olfactory identification deficits were assessed using the Odor Stick Identification Test for Japanese (OSIT-J). In addition, the relationship between the severity of pAVHs and olfactory identification disorder and cortical thickness abnormalities was determined.

STUDY RESULTS

Significant reductions in cortical thickness were observed in the right medial orbital sulcus (olfactory sulcus) and right orbital sulcus (H-shaped sulcus) in the pAVH group compared to both the non-AVH and HC groups (P < .003, Bonferroni correction). Furthermore, the severity of pAVHs was found to be negatively correlated with the reduction in cortical thickness in the olfactory sulcus and H-shaped sulcus. Additionally, a decrease in cortical thickness in the olfactory sulcus showed a positive correlation with the OSIT-J scores (P < .05, false discovery rate correction).

CONCLUSIONS

Cortical thickness abnormalities in the olfactory sulcus may be a common neuroimaging mechanism for pAVHs and olfactory identification deficits in SCZ patients.

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.

Dissociation between neuroanatomical and symptomatic subtypes in schizophrenia

BACKGROUND

Schizophrenia is a complex and heterogeneous syndrome with high clinical and biological stratification. Identifying distinctive subtypes can improve diagnostic accuracy and help precise therapy. A key challenge for schizophrenia subtyping is understanding the subtype-specific biological underpinnings of clinical heterogeneity. This study aimed to investigate if the machine learning (ML)-based neuroanatomical and symptomatic subtypes of schizophrenia are associated.

METHODS

A total of 314 schizophrenia patients and 257 healthy controls from four sites were recruited. Gray matter volume (GMV) and Positive and Negative Syndrome Scale (PANSS) scores were employed to recognize schizophrenia neuroanatomical and symptomatic subtypes using K-means and hierarchical methods, respectively.

RESULTS

Patients with ML-based neuroanatomical subtype-1 had focally increased GMV, and subtype-2 had widespread reduced GMV than the healthy controls based on either K-means or Hierarchical methods. In contrast, patients with symptomatic subtype-1 had severe PANSS scores than subtype-2. No differences in PANSS scores were shown between the two neuroanatomical subtypes; similarly, no GMV differences were found between the two symptomatic subtypes. Cohen's Kappa test further demonstrated an apparent dissociation between the ML-based neuroanatomical and symptomatic subtypes (P > 0.05). The dissociation patterns were validated in four independent sites with diverse disease progressions (chronic vs. first episodes) and ancestors (Chinese vs. Western).

CONCLUSIONS

These findings revealed a replicable dissociation between ML-based neuroanatomical and symptomatic subtypes of schizophrenia, which provides a new viewpoint toward understanding the heterogeneity of schizophrenia.

Decoding reappraisal and suppression from neural circuits: A combined supervised and unsupervised machine learning approach

Emotion regulation is a core construct of mental health and deficits in emotion regulation abilities lead to psychological disorders. Reappraisal and suppression are two widely studied emotion regulation strategies but, possibly due to methodological limitations in previous studies, a consistent picture of the neural correlates related to the individual differences in their habitual use remains elusive. To address these issues, the present study applied a combination of unsupervised and supervised machine learning algorithms to the structural MRI scans of 128 individuals. First, unsupervised machine learning was used to separate the brain into naturally grouping grey matter circuits. Then, supervised machine learning was applied to predict individual differences in the use of different strategies of emotion regulation. Two predictive models, including structural brain features and psychological ones, were tested. Results showed that a temporo-parahippocampal-orbitofrontal network successfully predicted the individual differences in the use of reappraisal. Differently, insular and fronto-temporo-cerebellar networks successfully predicted suppression. In both predictive models, anxiety, the opposite strategy, and specific emotional intelligence factors played a role in predicting the use of reappraisal and suppression. This work provides new insights regarding the decoding of individual differences from structural features and other psychologically relevant variables while extending previous observations on the neural bases of emotion regulation strategies.

Correlation between abnormal N-acetyl-aspartate levels in posterior cingulate cortex and persistent auditory verbal hallucinations in Chinese patients with chronic schizophrenia

The aim of this study was to investigate the relationship between persistent auditory verbal hallucinations (pAVHs) and N-acetyl-aspartate (NAA) levels in posterior cingulate cortex (PCC). 117 schizophrenia (SCZ) patients (61 pAVHs and 56 non-AVHs) and 66 healthy controls were included. The P3 item of the Positive and Negative Syndrome Scale and the Auditory Hallucinations subscale of the Psychotic Symptom Rating Scale were used to assess the severity of pAVHs. NAA levels were significantly lower in the AVHs group, and were negatively correlated with pAVHs. Therefore, increasing the NAA levels in PCC may be helpful in treating pAVHs.

Decreased cortical gyrification and surface area in the left medial parietal cortex in patients with treatment-resistant and ultratreatment-resistant schizophrenia

AIM

Validating the vulnerabilities and pathologies underlying treatment-resistant schizophrenia (TRS) is an important challenge in optimizing treatment. Gyrification and surface area (SA), reflecting neurodevelopmental features, have been linked to genetic vulnerability to schizophrenia. The aim of this study was to identify gyrification and SA abnormalities specific to TRS.

METHODS

We analyzed 3T magnetic resonance imaging findings of 24 healthy controls (HCs), 20 responders to first-line antipsychotics (FL-Resp), and 41 patients with TRS, including 19 clozapine responders (CLZ-Resp) and 22 FL- and clozapine-resistant patients (patients with ultratreatment-resistant schizophrenia [URS]). The local gyrification index (LGI) and associated SA were analyzed across groups. Diagnostic accuracy was verified by receiver operating characteristic curve analysis.

RESULTS

Both CLZ-Resp and URS had lower LGI values than HCs (P = 0.041, Hedges g [g_H ] = 0.75; P = 0.013, g_H  = 0.96) and FL-Resp (P = 0.007, g_H  = 1.00; P = 0.002, g_H  = 1.31) in the left medial parietal cortex (Lt-MPC). In addition, both CLZ-Resp and URS had lower SA in the Lt-MPC than FL-Resp (P < 0.001, g_H  = 1.22; P < 0.001, g_H  = 1.75). LGI and SA were positively correlated in non-TRS (FL-Resp) (ρ = 0.64, P = 0.008) and TRS (CLZ-Resp + URS) (ρ = 0.60, P < 0.001). The areas under the receiver operating characteristic curve for non-TRS versus TRS with LGI and SA in the Lt-MPC were 0.79 and 0.85, respectively. SA in the Lt-MPC was inversely correlated with negative symptoms (ρ = -0.40, P = 0.018) and clozapine plasma levels (ρ = -0.35, P = 0.042) in TRS.

CONCLUSION

LGI and SA in the Lt-MPC, a functional hub in the default-mode network, were abnormally reduced in TRS compared with non-TRS. Thus, altered LGI and SA in the Lt-MPC might be structural features associated with genetic vulnerability to TRS.

Association of cortical thickness and cognition with schizophrenia treatment resistance

AIM

Approximately a third of patients with schizophrenia fail to adequately respond to antipsychotic medications, a condition known as treatment resistance (TR). We aimed to assess cognitive and cortical thickness deficits and their relationship to TR in schizophrenia.

METHOD

We recruited patients with schizophrenia (n = 127), including patients at treatment initiation (n = 45), treatment-responsive patients (n = 40) and TR patients (n = 42), and healthy controls (n = 83). Clinical symptoms, neurocognitive function, and structural images were assessed. We performed group comparisons, and explored association of cortical thickness and cognition with TR.

RESULTS

The TR patients showed significantly more severe clinical symptoms and cognitive impairment relative to the treatment-responsive group. Compared to healthy controls, 56 of 68 brain regions showed significantly reduced cortical thickness in patients with schizophrenia. Reductions in five regions were significantly associated with TR (reduction in TR relative to treatment-responsive patients), i.e. in the right caudal middle frontal gyrus, superior frontal cortex, fusiform gyrus, pars opercularis of the inferior frontal cortex, and supramarginal cortex. Cognition deficits were also significantly correlated with cortical thickness in these five regions in patients with schizophrenia. Cortical thickness of the right caudal middle frontal gyrus, superior frontal cortex and pars opercularis of the inferior frontal cortex also significantly mediated effects of cognitive deficits on TR.

CONCLUSION

Treatment resistance in schizophrenia was associated with reduced thickness in the right caudal middle frontal gyrus, superior frontal cortex, fusiform gyrus, pars opercularis of the inferior frontal cortex, and supramarginal cortex. Cortical abnormalities further mediate cognitive deficits known to be associated with TR.

Hearing voices in the head: Two meta-analyses on structural correlates of auditory hallucinations in schizophrenia

Past voxel-based morphometry (VBM) studies demonstrate reduced grey matter volume (GMV) in schizophrenia (SZ) patients' brains in various cortical and subcortical regions. Probably due to SZ symptoms' heterogeneity, these results are often inconsistent and difficult to integrate. We hypothesized that focusing on auditory verbal hallucinations (AVH) - one of the most common SZ symptoms - would allow reducing heterogeneity and discovering further compelling evidence of SZ neural correlates. We carried out two voxel-based meta-analyses of past studies that investigated the structural correlates of AVH in SZ. The review of whole-brain VBM studies published until June 2022 in PubMed and PsychInfo databases yielded (a) 13 studies on correlations between GMV and AVH severity in SZ patients (n = 472; 86 foci), and (b) 11 studies involving comparisons between hallucinating SZ patients (n = 504) and healthy controls (n = 524; 74 foci). Data were analyzed using the Activation Likelihood Estimation method. AVH severity was associated with decreased GMV in patients' left superior temporal gyrus (STG) and left posterior insula. Compared with healthy controls, hallucinating SZ patients showed reduced GMV on the left anterior insula and left inferior frontal gyrus (IFG). Our findings revealed important structural dysfunctions in a left lateralized cluster of brain regions, including the insula and temporo-frontal regions, that significantly contribute to the severity and persistence of AVH. Structural atrophy found in circuits involved in generating and perceiving speech, as well as in auditory signal processing, might reasonably be considered a biological marker of AVH in SZ.

Association between empathy and drinking among a community sample of heavy drinkers: Sex differences and neural correlates

Alcohol use disorder (AUD) is a major health problem, yet most individuals with AUD do not perceive a need for formal treatment and do not receive treatment. The lack of treatment seeking among individuals with AUD may suggest a lack of self-awareness and insight into the seriousness of AUD related problems, as well as lack of empathy for the impact of one's drinking on others. Recent work has suggested that empathy may be impaired among individuals seeking treatment for AUD. Further these impairments may differ by sex such that males with lower empathy reported more drinking consequences and greater drinking intensity, but there was no association between empathy and drinking among females. The current study used regression analyses (alpha = 0.05) to examine the association between empathy (as measured by the four scales of the Interpersonal Reactivity Index), independent components of gray matter volume in regions associated with empathy, and drinking variables among non-treatment seeking drinkers with AUD (N = 136) and also examined these effects by sex. Results showed greater perspective taking was associated with less temporoparietal and frontotemporal gray matter volume (B(SE) = -0.912 (0.043), p = 0.034). An interaction between perspective taking and sex was associated with craving, such that higher perspective taking was associated with less craving for males only (B(SE) = -0.48 (0.243), p = 0.049; R2 = 0.087). Empathic concern was related to lower percent heavy drinking days for both males and females (B(SE) = -1.57 (0.743), p = 0.035; R2 = 0.11). The current study found empathy may be an important predictor of craving for males and frequency of heavy drinking for males and females. Future work should investigate whether empathy predicts treatment seeking.

Dopaminergic dysfunction and excitatory/inhibitory imbalance in treatment-resistant schizophrenia and novel neuromodulatory treatment

Antipsychotic drugs are the mainstay in the treatment of schizophrenia. However, one-third of patients do not show adequate improvement in positive symptoms with non-clozapine antipsychotics. Additionally, approximately half of them show poor response to clozapine, electroconvulsive therapy, or other augmentation strategies. However, the development of novel treatment for these conditions is difficult due to the complex and heterogenous pathophysiology of treatment-resistant schizophrenia (TRS). Therefore, this review provides key findings, potential treatments, and a roadmap for future research in this area. First, we review the neurobiological pathophysiology of TRS, particularly the dopaminergic, glutamatergic, and GABAergic pathways. Next, the limitations of existing and promising treatments are presented. Specifically, this article focuses on the therapeutic potential of neuromodulation, including electroconvulsive therapy, repetitive transcranial magnetic stimulation, transcranial direct current stimulation, and deep brain stimulation. Finally, we propose multivariate analyses that integrate various perspectives of the pathogenesis, such as dopaminergic dysfunction and excitatory/inhibitory imbalance, thereby elucidating the heterogeneity of TRS that could not be obtained by conventional statistics. These analyses can in turn lead to a precision medicine approach with closed-loop neuromodulation targeting the detected pathophysiology of TRS.

Exploring Brain Structural and Functional Biomarkers in Schizophrenia via Brain-Network-Constrained Multi-View SCCA

Recent studies have proved that dynamic regional measures extracted from the resting-state functional magnetic resonance imaging, such as the dynamic fractional amplitude of low-frequency fluctuation (d-fALFF), could provide a great insight into brain dynamic characteristics of the schizophrenia. However, the unimodal feature is limited for delineating the complex patterns of brain deficits. Thus, functional and structural imaging data are usually analyzed together for uncovering the neural mechanism of schizophrenia. Investigation of neural function-structure coupling enables to find the potential biomarkers and further helps to understand the biological basis of schizophrenia. Here, a brain-network-constrained multi-view sparse canonical correlation analysis (BN-MSCCA) was proposed to explore the intrinsic associations between brain structure and dynamic brain function. Specifically, the d-fALFF was first acquired based on the sliding window method, whereas the gray matter map was computed based on voxel-based morphometry analysis. Then, the region-of-interest (ROI)-based features were extracted and further selected by performing the multi-view sparse canonical correlation analysis jointly with the diagnosis information. Moreover, the brain-network-based structural constraint was introduced to prompt the detected biomarkers more interpretable. The experiments were conducted on 191 patients with schizophrenia and 191 matched healthy controls. Results showed that the BN-MSCCA could identify the critical ROIs with more sparse canonical weight patterns, which are corresponding to the specific brain networks. These are biologically meaningful findings and could be treated as the potential biomarkers. The proposed method also obtained a higher canonical correlation coefficient for the testing data, which is more consistent with the results on training data, demonstrating its promising capability for the association identification. To demonstrate the effectiveness of the potential clinical applications, the detected biomarkers were further analyzed on a schizophrenia-control classification task and a correlation analysis task. The experimental results showed that our method had a superior performance with a 5–8% increment in accuracy and 6–10% improvement in area under the curve. Furthermore, two of the top-ranked biomarkers were significantly negatively correlated with the positive symptom score of Positive and Negative Syndrome Scale (PANSS). Overall, the proposed method could find the association between brain structure and dynamic brain function, and also help to identify the biological meaningful biomarkers of schizophrenia. The findings enable our further understanding of this disease.

Differences in Cortical Thickness in Schizophrenia Patients With and Without Auditory Verbal Hallucinations

Auditory verbal hallucinations (AVHs) are one of the most common and severe symptoms of schizophrenia (SCZ), but the neuroanatomical mechanisms underlying AVHs remain unclear. This study aimed to investigate whether persistent AVHs (pAVH) are associated with cortical thinning of certain brain regions in patients with SCZ. With the use of the 3T magnetic resonance imaging (MRI) technology, we acquired and analyzed data from 79 SCZ patients with pAVH (pAVH group), 60 SCZ patients without AVHs (non-AVH group), and 83 healthy controls (HC group). The severity of pAVH was assessed by the P3 hallucination items in the Positive and Negative Syndrome Scale (PANSS) and the Auditory Hallucinations Rating Scale (AHRS). Cortical thickness analysis was used to compare the region of interest (ROI) cortical thickness between the groups. The relationship between the severity of pAVH and cortical thickness was also explored. Compared with the non-AVH and HC groups, the pAVH group exhibited significantly reduced cortical thickness in the bilateral lateral orbitofrontal region (p < 0.0007, after Bonferroni correction); no significant difference was found between the non-AVH group and the HC group. The cortical thickness of the left lateral orbitofrontal cortex (P3: r = −0.44, p < 0.001; AHRS: r = −0.45, p < 0.001) and the right lateral orbitofrontal cortex (P3: r = −0.36, p = 0.002; AHRS: r = −0.33, p = 0.004) were negatively correlated with the severity of pAVH (after Bonferroni correction, p < 0.0125). Therefore, abnormal thickness of the bilateral lateral orbitofrontal cortices might be associated with pAVHs in SCZ patients.

Metabolite differences in the medial prefrontal cortex in schizophrenia patients with and without persistent auditory verbal hallucinations: a 1H MRS study

Studies of schizophrenia (SCZ) have associated auditory verbal hallucinations (AVH) with structural and functional abnormalities in frontal cortex, especially medial prefrontal cortex (mPFC). Although abnormal prefrontal network connectivity associated with language production has been studied extensively, the relationship between mPFC dysfunction (highly relevant to the pathophysiology of SCZ) and AVH has been rarely investigated. In this study, proton magnetic resonance spectroscopy was used to measure metabolite levels in the mPFC in 61 SCZ patients with persistent AVH (pAVH), 53 SCZ patients without AVH (non-AVH), and 59 healthy controls (HC). The pAVH group showed significantly lower levels of N-acetyl-aspartate + N-acetyl-aspartyl-glutamate (tNAA) and glutamate + glutamine (Glx), compared with the non-AVH (tNAA: p = 0.022, Glx: p = 0.012) and HC (tNAA: p = 0.001, Glx: p = 0.001) groups. No difference was found in the levels of tNAA and Glx between non-AVH and HC. The levels of tNAA and Glx in the mPFC was negatively correlated with the severity of pAVH (tNAA: r = -0.24, p = 0.014; Glx: r = -0.30, p = 0.002). In conclusion, pAVH in SCZ patients might be related to decreased levels of tNAA and Glx in the mPFC, indicating that tNAA or Glx might play a key role in the pathogenesis of pAVH.

Structural covariance networks in schizophrenia: A systematic review Part I

BACKGROUND

Schizophrenia is proposed as a disorder of dysconnectivity. However, examination of complexities of dysconnectivity has been challenging. Structural covariance networks (SCN) provide important insights into the nature of dysconnectivity. This systematic review examines the SCN studies that employed statistical approaches to elucidate covariation of regional morphometric variations.

METHODS

A systematic search of literature was conducted for peer-reviewed publications using different keywords and keyword combinations for schizophrenia. Fifty-two studies met the criteria.

RESULTS

Early SCN studies began using correlational structure of selected regions. Over the last 3 decades, methodological approaches have grown increasingly sophisticated from examining selected brain regions using correlation tests on small sample sizes to recent approaches that use advanced statistical methods to examine covariance structure of whole-brain parcellations on larger samples. Although the results are not fully consistent across all studies, a pattern of fronto-temporal, fronto-parietal and fronto-thalamic covariation is reported. Attempts to associate SCN alterations with functional connectivity, to differentiate between disease-related and neurodevelopment-related morphometric changes, and to develop "causality-based" models are being reported. Clinical correlation with outcome, psychotic symptoms, neurocognitive and social cognitive performance are also reported.

CONCLUSIONS

Application of advanced statistical methods are beginning to provide insights into interesting patterns of regional covariance including correlations with clinical and cognitive data. Although these findings appear similar to morphometric studies, SCNs have the advantage of highlighting topology of these regions and their relationship to the disease and associated variables. Further studies are needed to investigate neurobiological underpinnings of shared covariance, and causal links to clinical domains.

Decreased gray matter volume is associated with theory of mind deficit in adolescents with schizophrenia

Schizophrenia patients often suffer from deficit in theory of mind (TOM). Prior neuroimaging studies revealed neuroimaging correlates of TOM deficit in adults with schizophrenia, neuroimaging correlates of TOM in adolescents is less well established. This study aimed to investigate gray matter volume (GMV) abnormalities and TOM deficits in schizophrenic adolescents, and examine the relationship between them. Twenty adolescent schizophrenic patients and 25 age, sex-matched healthy controls underwent T1-weighted magnetic resonance imaging (MRI) scans, and were examined for TOM based on the Reading the Mind in the Eyes test (RMET). Univariate voxel-based morphometry (VBM) and multivariate source-based morphometry (SBM) were employed to examine alterations of two GMV phenotypes in schizophrenic adolescents: voxel-wise GMV and covarying structural brain patterns (SBPs). Compared with controls, our results revealed a significant deficit in RMET performance of the patients, Voxel-wise VBM analysis revealed that patients exhibited decreased GMV in bilateral insula, orbitofrontal cortex, and right rolandic operculum, and GMV of these brain regions were positively correlated with RMET performance. Multivariate SBM analysis identified a significantly different between-group SBP comprising of bilateral insula and inferior frontal cortex, bilateral superior temporal cortex, and bilateral lateral parietal cortex and right rolandic operculum. The loading scores of this SBP was positively correlated with RMET performance. This study revealed impairment of TOM ability in schizophrenic adolescents and revealed an association between TOM deficit and decreased GMV in regions which are crucial for social cognition, thereby provided insight and possible target regions for understanding the neural pathology and normalizing TOM deficit in adolescent schizophrenia patients.

Cognitive dysfunction and cortical structural abnormalities in first-episode drug-naïve schizophrenia patients with auditory verbal hallucination

OBJECTIVE

The current study aimed to examine the cognitive profiles and cortical structural alterations in first-episode drug-naïve schizophrenia with AVH (auditory verbal hallucination).

METHODS

Cortical structural parameters including cortical thickness and local gyrification index (LGI) estimated using FreeSurfer as well as cognitive performance assessed on the MATRICS Consensus Cognitive Battery (MCCB) were acquired from 78 schizophrenia patients with AVH, 74 schizophrenia patients without AVH (non-AVH), and 76 healthy controls (HC). Hoffman Auditory Hallucination Rating Scale (HAHRS) was applied to assess the severity of AVH.

RESULTS

The results revealed extensive deficits in all cognitive domains among AVH, non-AVH, and HC groups. Compared to non-AVH group, the AVH group showed poorer performance on visual learning and verbal learning domains. There were six brain regions with cortical thinning in the right hemisphere of inferior temporal gyrus, superior temporal gyrus, lateral orbito frontal cortex, rostral anterior cingulate cortex, supramarginal gyrus and insula, and two brain regions with increased LGI in the left hemisphere of superior parietal gyrus and the right hemisphere of caudal anterior cingulate cortex on AVH group relative to non-AVH group. Correlation analysis revealed that the cortical thickness in the right hemisphere of lateral orbito frontal cortex was negatively correlated with the severity of AVH in schizophrenia patients with AVH.

CONCLUSION

Visual learning, verbal learning dysfunction, and specific disruption of cortical structure may characterize schizophrenia patients with AVH during early stages of the disorder. Right lateral orbito frontal cortical deficits may be the pathological mechanisms underlying AVH in first-episode drug-naïve schizophrenia.

The Etiology of Auditory Hallucinations in Schizophrenia: From Multidimensional Levels

Enormous efforts have been made to unveil the etiology of auditory hallucinations (AHs), and multiple genetic and neural factors have already been shown to have their own roles. Previous studies have shown that AHs in schizophrenia vary from those in other disorders, suggesting that they have unique features and possibly distinguishable mechanisms worthy of further investigation. In this review, we intend to offer a comprehensive summary of current findings related to AHs in schizophrenia from aspects of genetics and transcriptome, neurophysiology (neurometabolic and electroencephalogram studies), and neuroimaging (structural and functional magnetic resonance imaging studies and transcriptome–neuroimaging association study). Main findings include gene polymorphisms, glutamate level change, electroencephalographic alterations, and abnormalities of white matter fasciculi, cortical structure, and cerebral activities, especially in multiple regions, including auditory and language networks. More solid and comparable research is needed to replicate and integrate ongoing findings from multidimensional levels.

Structural Covariance of Depth-Dependent Intracortical Myelination in the Human Brain and Its Application to Drug-Naïve Schizophrenia: A T1w/T2w MRI Study

Aberrations in intracortical myelination are increasingly being considered as a cardinal feature in the pathophysiology of schizophrenia. We investigated the network-level distribution of intracortical myelination across various cortex depths. We enrolled 126 healthy subjects and 106 first-episode drug-naïve schizophrenia patients. We used T1w/T2w ratio as a proxy of intracortical myelination, parcellated cortex into several equivolumetric surfaces based on cortical depths and mapped T1w/T2w ratios to each surface. Non-negative matrix factorization was used to generate depth-dependent structural covariance networks (dSCNs) of intracortical myelination from 2 healthy controls datasets-one from our study and another from 100-unrelated dataset of the Human Connectome Project. For patient versus control comparisons, partial least squares approach was used; we also related myelination to clinical features of schizophrenia. We found that dSCNs were highly reproducible in 2 independent samples. Network-level myelination was reduced in prefrontal and cingulate cortex and increased in perisylvian cortex in schizophrenia. The abnormal network-level myelination had a canonical correlation with symptom burden in schizophrenia. Moreover, myelination of prefrontal cortex correlated with duration of untreated psychosis. In conclusion, we offer a feasible and sensitive framework to study depth-dependent myelination and its relationship with clinical features.

[Cognitive control in the research domain criteria system: clinical implications for auditory verbal hallucinations]

Cognitive control (CC) represents one of six constructs within the research domain criteria (RDoC) domain of cognitive systems, which can be examined using different units of analyses (from genetic and molecular mechanisms to neural circuits and self-reports). The CC is defined as the ability to execute top-down control over task-specific processes and to coordinate thought and actions to achieve a specific goal. Within the field of cognitive neuroscience, recent studies provided important findings about central neuronal components of the CC network and the interactions with other relevant functional systems. In the development and maintenance of distinct psychiatrically relevant symptoms, such as auditory verbal hallucinations (AVH) or hearing voices, dysfunctional CC is thought to play an essential transdiagnostic role. This selective literature review addresses the specific and clinically relevant question of the extent to which the RDoC construct of CC has been incorporated into studies investigating the neurobiological mechanisms of AVH. In addition, an overview of the extent to which findings exploring the underlying mechanisms have been transferred into daily clinical routine is provided. Furthermore, future research perspectives and therapeutic approaches are discussed. Based on currently preferred neurobiological models of AVH, nonpharmacological strategies, such as brain stimulation techniques and psychotherapy can be derived. Further research perspectives arise in the field of interventional studies oriented towards the RDoC matrix.

Interhemispheric co-alteration of brain homotopic regions

Asymmetries in gray matter alterations raise important issues regarding the pathological co-alteration between hemispheres. Since homotopic areas are the most functionally connected sites between hemispheres and gray matter co-alterations depend on connectivity patterns, it is likely that this relationship might be mirrored in homologous interhemispheric co-altered areas. To explore this issue, we analyzed data of patients with Alzheimer’s disease, schizophrenia, bipolar disorder and depressive disorder from the BrainMap voxel-based morphometry database. We calculated a map showing the pathological homotopic anatomical co-alteration between homologous brain areas. This map was compared with the meta-analytic homotopic connectivity map obtained from the BrainMap functional database, so as to have a meta-analytic connectivity modeling map between homologous areas. We applied an empirical Bayesian technique so as to determine a directional pathological co-alteration on the basis of the possible tendencies in the conditional probability of being co-altered of homologous brain areas. Our analysis provides evidence that: the hemispheric homologous areas appear to be anatomically co-altered; this pathological co-alteration is similar to the pattern of connectivity exhibited by the couples of homologues; the probability to find alterations in the areas of the left hemisphere seems to be greater when their right homologues are also altered than vice versa, an intriguing asymmetry that deserves to be further investigated and explained.

Systemic inflammation and grey matter volume in schizophrenia and bipolar disorder: Moderation by childhood trauma severity

BACKGROUND

Elevated levels of systemic inflammation are consistently reported in both schizophrenia (SZ) and bipolar-I disorder (BD), and are associated with childhood trauma exposure. We tested whether childhood trauma exposure moderates associations between systemic inflammation and brain morphology in people with these diagnoses.

METHODS

Participants were 55 SZ cases, 52 BD cases and 59 healthy controls (HC) who underwent magnetic resonance imaging. Systemic inflammation was measured using a composite z-score derived from serum concentrations of interleukin 6, tumor necrosis factor alpha and C-reactive protein. Indices of grey matter volume covariation (GMC) were derived from independent component analysis. Childhood trauma was measured using the Childhood Trauma Questionnaire (CTQ Total score).

RESULTS

A series of moderated moderation analyses indicated that increased systemic inflammation were associated with increased GMC in the striatum and cerebellum among all participants. Severity of childhood trauma exposure moderated the relationship between systemic inflammation and GMC in one component, differently among the groups. Specifically, decreased GMC in the PCC/precuneus, parietal lobule and postcentral gyrus, and increased GMC in the left middle temporal gyrus was associated with increased systemic inflammation in HC individuals exposed to high (but not low or average) levels of trauma and in SZ cases exposed to low (but not average or high) levels of trauma, but not in BD cases.

CONCLUSIONS

Increased systemic inflammation is associated with grey matter changes in people with psychosis, and these relationships may be partially and differentially moderated by childhood trauma exposure according to diagnosis.

Out of control: An altered parieto-occipital-cerebellar network for impulsivity in bipolar disorder

Bipolar disorder is an affective disorder characterized by rapid fluctuations in mood ranging from episodes of depression to mania, as well as by increased impulsivity. Previous studies investigated the neural substrates of bipolar disorder mainly using univariate methods, with a particular focus on the neural circuitry underlying emotion regulation difficulties. In the present study, capitalizing on an innovative whole-brain multivariate method to structural analysis known as Source-based Morphometry, we investigated the neural substrates of bipolar disorder and their relation with impulsivity, assessed with both self-report measures and performance-based tasks. Structural images from 46 patients with diagnosis of bipolar disorder and 60 healthy controls were analysed. Compared to healthy controls, patients showed decreased gray matter concentration in a parietal-occipital-cerebellar network. Notably, the lower the gray matter concentration in this circuit, the higher the self-reported impulsivity. In conclusion, we provided new evidence of an altered brain network in bipolar disorder patients related to their abnormal impulsivity. Taken together, these findings extend our understanding of the neural and symptomatic characterization of bipolar disorder.

Inhibitory Top-Down Control Deficits in Schizophrenia With Auditory Verbal Hallucinations: A Go/NoGo Task

Objective: Auditory verbal hallucinations (AVH), with unclear mechanisms, cause extreme distresses to schizophrenia patients. Deficits of inhibitory top-down control may be linked to AVH. Therefore, in this study, we focused on inhibitory top-down control in schizophrenia patients with AVH. Method: The present study recruited 40 schizophrenia patients, including 20 AVH patients and 20 non-AVH patients, and 23 healthy controls. We employed event-related potentials to investigate the N2 and P3 amplitude and latency differences among these participants during a Go/NoGo task. Results: Relative to healthy controls, the two patient groups observed longer reaction time (RT) and reduced accuracy. The two patient groups had smaller NoGo P3 amplitude than the healthy controls, and the AVH patients showed smaller NoGo P3 amplitude than the non-AVH patients. In all the groups, the parietal area showed smaller NoGo P3 than frontal and central areas. However, no significant difference was found in N2 and Go P3 amplitude between the three groups. Conclusions: AVH patients might have worse inhibitory top-down control, which might be involved in the occurrence of AVH. Hopefully, our results could enhance understanding of the pathology of AVH.

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.

Hallucination-Specific structure-function associations in schizophrenia

Combining structural (sMRI) and functional magnetic resonance imaging (fMRI) data in schizophrenia patients with and without auditory hallucinations (9 SZ_AVH, 12 SZ_nAVH), 18 patients with bipolar disorder, and 22 healthy controls, we examined whether cortical thinning was associated with abnormal activity in functional brain networks associated with auditory hallucinations. Language-task fMRI data were combined with mean cortical thickness values from 148 brain regions in a constrained principal component analysis (CPCA) to identify brain structure-function associations predictable from group differences. Two components emerged from the multimodal analysis. The "AVH component" highlighted an association of frontotemporal and cingulate thinning with altered brain activity characteristic of hallucinations among patients with AVH. In contrast, the "Bipolar component" distinguished bipolar patients from healthy controls and linked increased activity in the language network with cortical thinning in the left occipital-temporal lobe. Our findings add to a body of evidence of the biological underpinnings of hallucinations and illustrate a method for multimodal data analysis of structure-function associations in psychiatric illness.

Neurological Soft Signs Predict Auditory Verbal Hallucinations in Patients With Schizophrenia

Neurological soft signs (NSS) are well documented in individuals with schizophrenia (SZ), yet so far, the relationship between NSS and specific symptom expression is unclear. We studied 76 SZ patients using magnetic resonance imaging (MRI) to determine associations between NSS, positive symptoms, gray matter volume (GMV), and neural activity at rest. SZ patients were hypothesis-driven stratified according to the presence or absence of auditory verbal hallucinations (AVH; n = 34 without vs 42 with AVH) according to the Brief Psychiatric Rating Scale. Structural MRI data were analyzed using voxel-based morphometry, whereas intrinsic neural activity was investigated using regional homogeneity (ReHo) measures. Using ANCOVA, AVH patients showed significantly higher NSS in motor and integrative functions (IF) compared with non-hallucinating (nAVH) patients. Partial correlation revealed that NSS IF were positively associated with AVH symptom severity in AVH patients. Such associations were not confirmed for delusions. In region-of-interest ANCOVAs comprising the left middle and superior temporal gyri, right paracentral lobule, and right inferior parietal lobule (IPL) structure and function, significant differences between AVH and nAVH subgroups were not detected. In a binary logistic regression model, IF scores and right IPL ReHo were significant predictors of AVH. These data suggest significant interrelationships between sensorimotor integration abilities, brain structure and function, and AVH symptom expression.

Progressive subcortical volume loss in treatment-resistant schizophrenia patients after commencing clozapine treatment

The association of antipsychotic medication with abnormal brain morphometry in schizophrenia remains uncertain. This study investigated subcortical morphometric changes 6 months after switching treatment to clozapine in patients with treatment-resistant schizophrenia compared with healthy volunteers, and the relationships between longitudinal volume changes and clinical variables. In total, 1.5T MRI images were acquired at baseline before commencing clozapine and again after 6 months of treatment for 33 patients with treatment-resistant schizophrenia and 31 controls, and processed using the longitudinal pipeline of Freesurfer v.5.3.0. Two-way repeated MANCOVA was used to assess group differences in subcortical volumes over time and partial correlations to determine association with clinical variables. Whereas no significant subcortical volume differences were found between patients and controls at baseline (F(8,52) = 1.79; p = 0.101), there was a significant interaction between time, group and structure (F(7,143) = 52.54; p < 0.001). Corrected post-hoc analyses demonstrated that patients had significant enlargement of lateral ventricles (F(1,59) = 48.89; p < 0.001) and reduction of thalamus (F(1,59) = 34.85; p < 0.001), caudate (F(1,59) = 59.35; p < 0.001), putamen (F(1,59) = 87.20; p < 0.001) and hippocampus (F(1,59) = 14.49; p < 0.001) volumes. Thalamus and putamen volume reduction was associated with improvement in PANSS (r = 0.42; p = 0.021, r = 0.39; p = 0.033), SANS (r = 0.36; p = 0.049, r = 0.40; p = 0.027) and GAF (r = -0.39; p = 0.038, r = -0.42; p = 0.024) scores. Reduced thalamic volume over time was associated with increased serum clozapine level at follow-up (r = -0.44; p = 0.010). Patients with treatment-resistant schizophrenia display progressive subcortical volume deficits after switching to clozapine despite experiencing symptomatic improvement. Thalamo-striatal progressive volumetric deficit associated with symptomatic improvement after clozapine exposure may reflect an adaptive response related to improved outcome rather than a harmful process.

Genetic Contributions to Multivariate Data-Driven Brain Networks Constructed via Source-Based Morphometry

Identifying genetic factors underlying neuroanatomical variation has been difficult. Traditional methods have used brain regions from predetermined parcellation schemes as phenotypes for genetic analyses, although these parcellations often do not reflect brain function and/or do not account for covariance between regions. We proposed that network-based phenotypes derived via source-based morphometry (SBM) may provide additional insight into the genetic architecture of neuroanatomy given its data-driven approach and consideration of covariance between voxels. We found that anatomical SBM networks constructed on ~ 20 000 individuals from the UK Biobank were heritable and shared functionally meaningful genetic overlap with each other. We additionally identified 27 unique genetic loci that contributed to one or more SBM networks. Both GWA and genetic correlation results indicated complex patterns of pleiotropy and polygenicity similar to other complex traits. Lastly, we found genetic overlap between a network related to the default mode and schizophrenia, a disorder commonly associated with neuroanatomic alterations.

Left cerebral cortex complexity differences in sporadic healthy individuals with auditory verbal hallucinations: A pilot study

In the present pilot study, we aimed to characterize the brain surface differences between 42 sporadic healthy individuals with AVHs (Hi-AVHs) and 50 healthy individuals without AVHs. The Auditory Hallucinations Rating Scale (AHRS) was used to assess the severity of AVHs, while the gyrification index and fractal dimensions were used to evaluate cerebral cortex complexity. We observed a significant increase of the gyrification index was located in the left superior temporal gyrus, the left temporoparietal junction, the left superior frontal gyrus, and the left parietal lobe. The fractal dimensions had significantly increased in the left Wernicke's area, the left Broca's areas and the left parietal lobe. Our pilot findings indicated gyrification index and fractal dimensions differences were only located in the left hemisphere between the groups of Hi-with and without AVHs. However, these differences did not correlate with the AVHs symptoms, and the non-hallucinating healthy individuals did not demonstrate corresponding reverse changes; hence we cannot postulate that cerebral cortex complexity alterations are related to AVHs. Our pilot study provides a clue for further studies aimed at investigating the brain features of Hi-AVHs.

Associations between brain structural networks and neurological soft signs in healthy adults

Neurological soft signs (NSS), as minor neurological deficits, have been identified in several psychiatric disorders, especially in schizophrenia. However, it's unclear how the neuropathological processes of the disease affect NSS related brain morphological changes and whether it is confounded by the use of medication. As NSS also exist in healthy people, the potential confounding effects of psychopathology or medication will be excluded if NSS are investigated in healthy people. Therefore, we applied a novel multivariate approach, source-based morphometry (SBM), to study structural networks in relation to NSS in healthy adults based on structural magnetic resonance imaging (MRI) data. The Heidelberg Scale was applied to evaluate NSS. Using SBM, we constructed structural networks and investigated their associations with NSS in healthy adults. Six grey matter (GM) structural networks were identified. Sensory integration subscores were associated with the cerebellar component and the cortico-basal ganglia-thalamic component. Motor coordination subscores and total NSS scores were associated with the sensorimotor component. The present findings indicated that structural network abnormalities in cerebellar, subcortical and cortical sensorimotor areas contribute to NSS performance in healthy adults.

Source-based morphometry: a decade of covarying structural brain patterns

In this paper, we review and discuss brain imaging studies which have used the source-based morphometry (SBM) approach over the past decade. SBM is a data-driven linear multivariate approach for decomposing structural brain imaging data into commonly covarying imaging components and subject-specific loading parameters. It is a well-established technique which has predominantly been used to study neuroanatomic differences between healthy controls and patients with neuropsychiatric diseases. We start by discussing the advantages of this technique over univariate analysis for imaging studies, followed by a discussion of results from recent studies which have successfully applied this methodology. We also present recent extensions of this framework including nonlinear SBM, biclustered independent component analysis (B-ICA) and conclude with the possible directions of work for future.

Structure/function interrelationships in patients with schizophrenia who have persistent auditory verbal hallucinations: A multimodal MRI study using parallel ICA

There is accumulating neuroimaging evidence for both structural and functional abnormalities in schizophrenia patients with persistent auditory verbal hallucinations (AVH). So far, the direct interrelationships between altered structural and functional changes underlying AVH are unknown. Recently, it has become possible to reveal hidden patterns of neural dysfunction not sufficiently captured by separate analysis of these two modalities. A data-driven fusion method called parallel independent component analysis (p-ICA) is able to identify maximally independent components of each imaging modality as well as the link between them. In the present study, we utilized p-ICA to study covarying components among gray matter volume maps computed from structural MRI (sMRI) and fractional amplitude of low-frequency fluctuations (fALFF) maps computed from resting-state functional MRI (rs-fMRI) data of 15 schizophrenia patients with AVH, 16 non-hallucinating schizophrenia patients (nAVH), and 19 healthy controls (HC). We found a significant correlation (r = 0.548, n = 50, p < .001) between a sMRI component and a rs-fMRI component, which was significantly different between the AVH and non AVH group (nAVH). The rs-fMRI component comprised temporal cortex and cortical midline regions, the sMRI component included predominantly fronto-temporo-parietal regions. Distinct clinical features, as measured by the Psychotic Symptoms Rating Scale (PSYRATS), were associated with two different modality specific rs-fMRI components. There was a significant correlation between a predominantly parietal resting-state network and the physical dimension of PSYRATS and the posterior cingulate/temporal cortex network and the emotional dimension of PSYRATS. These data suggest AVH-specific interrelationships between intrinsic network activity and GMV, together with modality-specific associations with distinct symptom dimensions of AVH.

Understanding auditory verbal hallucinations in healthy individuals and individuals with psychiatric disorders

Auditory verbal hallucinations(AVHs) are psychiatric manifestations that are common in patients with psychiatric disorders and can occur in healthy individuals. This review summarizes the existing literature on the phenomenological features of auditory verbal hallucinations, imaging findings, and interventions, focusing on patients with schizophrenia who experience auditory verbal hallucinations, in addition to patients with borderline personality disorder, bipolar disorder, major depressive disorder, and posttraumatic stress disorder, as well as healthy individuals. The phenomenological features of AVHs vary in different psychiatric disorders, and the symptoms are associated with changes in specific brain structures and disturbances in brain function, blood flow, and metabolism. Interventions for auditory verbal hallucinations include antipsychotic drugs, neurostimulation, and cognitive behavioral therapy.

Meta-analytic Evidence for the Plurality of Mechanisms in Transdiagnostic Structural MRI Studies of Hallucination Status

BACKGROUND

Hallucinations are transmodal and transdiagnostic phenomena, occurring across sensory modalities and presenting in psychiatric, neurodegenerative, neurological, and non-clinical populations. Despite their cross-category occurrence, little empirical work has directly compared between-group neural correlates of hallucinations.

METHODS

We performed whole-brain voxelwise meta-analyses of hallucination status across diagnoses using anisotropic effect-size seed-based d mapping (AES-SDM), and conducted a comprehensive systematic review in PubMed and Web of Science until May 2018 on other structural correlates of hallucinations, including cortical thickness and gyrification.

FINDINGS

3214 abstracts were identified. Patients with psychiatric disorders and hallucinations (eight studies) exhibited reduced gray matter (GM) in the left insula, right inferior frontal gyrus, left anterior cingulate/paracingulate gyrus, left middle temporal gyrus, and increased in the bilateral fusiform gyrus, while patients with neurodegenerative disorders with hallucinations (eight studies) showed GM decreases in the left lingual gyrus, right supramarginal gyrus/parietal operculum, left parahippocampal gyrus, left fusiform gyrus, right thalamus, and right lateral occipital gyrus. Group differences between psychiatric and neurodegenerative hallucination meta-analyses were formally confirmed using Monte Carlo randomizations to determine statistical significance, and a jackknife sensitivity analysis established the reproducibility of results across nearly all study combinations. For other structural measures (28 studies), the most consistent findings associated with hallucination status were reduced cortical thickness in temporal gyri in schizophrenia and altered hippocampal volume in Parkinson's disease and dementia. Additionally, increased severity of hallucinations in schizophrenia correlated with GM reductions within the left superior temporal gyrus, right middle temporal gyrus, bilateral supramarginal and angular gyri.

INTERPRETATION

Distinct patterns of neuroanatomical alteration characterize hallucination status in patients with psychiatric and neurodegenerative diseases, suggesting a plurality of anatomical signatures. This approach has implications for treatment, theoretical frameworks, and generates refutable predictions for hallucinations in other diseases and their occurrence within the general population.

FUNDING

None.

Depression, auditory-verbal hallucinations, and delusions in patients with schizophrenia: Different patterns of association with prefrontal gray and white matter volume

Structural brain abnormalities, including decreased gray matter (GM) and white matter (WM) volume, have been observed in patients with schizophrenia. These decrements were found to be associated with positive and negative symptoms, but affective symptoms (depression and anxiety) were poorly explored. We hypothesized that abnormalities in GM and WM volume might also be related to affective symptoms. GM and WM volumes were calculated from high-resolution T1 structural images acquired from 24 patients with schizophrenia and 26 healthy controls, and the associations of positive, negative, and affective symptoms with the brain volumes that showed significant reduction in patients were investigated. Patients demonstrated GM volume reductions in the bilateral prefrontal cortex, and WM volume reductions in the right frontal and left corpus callosum. Prefrontal cortex volume was significantly and inversely associated with both auditory-verbal hallucinations and depression severity. WM volume alterations, in contrast, were related to alogia, anhedonia, and delusions. The combined impact of auditory-verbal hallucinations and depression on similar sub-regions of the prefrontal cortex suggests that depression is involved in hearing voices. Further, this adverse impact of depression on prefrontal GM volume may underlie the impairment demonstrated by these patients in cognitive tasks that rely on executive processes.

Treatment resistant schizophrenia: Clinical, biological, and therapeutic perspectives

Treatment resistant schizophrenia (TRS) refers to the significant proportion of schizophrenia patients who continue to have symptoms and poor outcomes despite treatment. While many definitions of TRS include failure of two different antipsychotics as a minimum criterion, the wide variability in inclusion criteria has challenged the consistency and reproducibility of results from studies of TRS. We begin by reviewing the clinical, neuroimaging, and neurobiological characteristics of TRS. We further review the current treatment strategies available, addressing clozapine, the first-line pharmacological agent for TRS, as well as pharmacological and non-pharmacological augmentation of clozapine including medication combinations, electroconvulsive therapy, repetitive transcranial magnetic stimulation, deep brain stimulation, and psychotherapies. We conclude by highlighting the most recent consensus for defining TRS proposed by the Treatment Response and Resistance in Psychosis Working Group, and provide our overview of future perspectives and directions that could help advance the field of TRS research, including the concept of TRS as a potential subtype of schizophrenia.

Common variation in ZNF804A (rs1344706) is not associated with brain morphometry in schizophrenia or healthy participants

BACKGROUND

The single nucleotide polymorphism (SNP) rs1344706 [A>C] within intron 2 of the zinc finger protein 804A gene (ZNF804A) is associated with schizophrenia at the genome-wide level, but its function in relation to the development of psychotic disorders, including its influence on brain morphology remains unclear.

METHODS

Using both univariate (voxel-based morphometry, VBM; cortical thickness) and multivariate (source-based morphometry, SBM) approaches, we examined the effects of variation of the rs1344706 polymorphism on grey matter integrity in 214 Caucasian schizophrenia cases and 94 Caucasian healthy individuals selected from the Australian Schizophrenia Research Bank.

RESULTS

Neither univariate nor multivariate analyses showed any associations between indices of grey matter and rs1344706 variation in schizophrenia or healthy participants. This was revealed in the context of the typical pattern of decreased grey matter integrity in schizophrenia compared to healthy individuals, including: (1) large grey matter volume reductions in the orbitofrontal and anterior cingulate cortices and the left fusiform/inferior temporal gyri; (2) decreased cortical thickness in the left inferior temporal and fusiform gyri, the left orbitofrontal gyrus, as well as in the right pars opercularis/precentral gyrus; and (3) decreased covariation of grey matter concentration in frontal and limbic brain regions emerging from the SBM analyses.

CONCLUSIONS

Contrary to some - but not all - previous findings, this study of a large sample of schizophrenia cases and healthy controls reveals no evidence for association between grey matter alterations and variation in rs1344706 (ZNF804A). Differences in sample sizes and ethnicities may account for discrepant findings between the present and previous studies.

Cortical folding abnormalities in patients with schizophrenia who have persistent auditory verbal hallucinations

In schizophrenia temporal cortical volume loss differs between patients presenting with persistent auditory verbal hallucinations (pAVH) in contrast to those without hallucinatory symptoms (nAVH). However, it is unknown whether this deficit reflects a neural signature of neurodevelopmental origin or if abnormal temporal cortical volume is reflective of factors which may be relevant at later stages of the disorder. Here, we tested the hypothesis that local gyrification index (LGI) in regions of the temporal cortex differs between patients with pAVH (n=10) and healthy controls (n=14), and that abnormal temporal LGI discriminates between pAVH and nAVH (n=10). Structural magnetic resonance imaging at 3T along with surface-based data analysis methods was used. Contrary to our expectations, patients with pAVH showed lower LGI in Broca´s region compared to both healthy persons and nAVH. Compared to nAVH, those individuals presenting with pAVH also showed lower LGI in right Broca's homologue and right superior middle frontal cortex, together with increased LGI in the precuneus and superior parietal cortex. Regions with abnormal LGI common to both patient samples were found in anterior cingulate and superior frontal areas. Inferior cortical regions exhibiting abnormal LGI in pAVH patients were associated with overall symptom load (BPRS), but not with measures of AVH symptom severity. The pattern of abnormal cortical folding in this sample suggests a neurodevelopmental signature in Broca's region, consistent with current AVH models emphasizing the pivotal role of language circuits and inner speech. Temporal cortical deficits may characterize patients with pAVH during later stages of the disorder.

Distinguishing Between Treatment-Resistant and Non-Treatment-Resistant Schizophrenia Using Regional Homogeneity

Background: Patients with treatment-resistant schizophrenia (TRS) and non-treatment-resistant schizophrenia (NTRS) respond to antipsychotic drugs differently. Previous studies demonstrated that patients with TRS or NTRS exhibited abnormal neural activity in different brain regions. Accordingly, in the present study, we tested the hypothesis that a regional homogeneity (ReHo) approach could be used to distinguish between patients with TRS and NTRS. Methods: A total of 17 patients with TRS, 17 patients with NTRS, and 29 healthy controls (HCs) matched in sex, age, and education levels were recruited to undergo resting-state functional magnetic resonance imaging (RS-fMRI). ReHo was used to process the data. ANCOVA followed by post-hoc t-tests, receiver operating characteristic curves (ROC), and correlation analyses were applied for the data analysis. Results: ANCOVA analysis revealed widespread differences in ReHo among the three groups in the occipital, frontal, temporal, and parietal lobes. ROC results indicated that the optimal sensitivity and specificity of the ReHo values in the left postcentral gyrus, left inferior frontal gyrus/triangular part, and right fusiform could differentiate TRS from NTRS, TRS from HCs, and NTRS from HCs were 94.12 and 82.35%, 100 and 86.21%, and 82.35 and 93.10%, respectively. No correlation was found between abnormal ReHo and clinical symptoms in patients with TRS or NTRS. Conclusions: TRS and NTRS shared most brain regions with abnormal neural activity. Abnormal ReHo values in certain brain regions might be applied to differentiate TRS from NTRS, TRS from HC, and NTRS from HC with high sensitivity and specificity.

Mismatch negativity (MMN) to spatial deviants and behavioral spatial discrimination ability in the etiology of auditory verbal hallucinations and thought disorder in schizophrenia

Persistent auditory verbal hallucinations (AVH) in schizophrenia are increasingly tied to dysfunction at the level of auditory cortex. AVH may reflect in part misattribution of internally generated thoughts to external spatial locations. Here, we investigated the association between persistent AVH and spatial localization abilities assessed both behaviorally and by mismatch negativity (MMN) to location deviants.

METHODS

Spatial- and tonal- discrimination abilities were assessed in patients (n=20) and controls (n=20) using free-field tones. MMN was assessed to spatial-location-, pitch- and duration-deviants. AVH and thought disorder were assessed using clinical evaluation.

RESULTS

As predicted, patients showed significant reductions in behavioral spatial-discrimination (p<0.0001) and tone-matching (p<0.001) ability, along with impaired MMN generation to location (p<0.03) and pitch (p<0.05) deviants. Hallucinating (AVH+) and non-hallucinating (AVH-) subjects showed similar deficits in location MMN to left-hemifield stimuli (p<0.0001 vs. control). By contrast, AVH- patients differed significantly from controls (p=0.009) and AVH+ patients (p=0.018) for MMN to right-lateral hemifield (left auditory cortex) stimuli, whereas AVH+ patients showed paradoxically preserved MMN generation (p=0.99 vs. controls). Severity of thought disorder correlated with impaired spatial discrimination, especially to right-hemifield stimuli (p=0.013), but did not correlate significantly with MMN or tone matching deficits.

CONCLUSION

These findings demonstrate a significant relationship between auditory cortical spatial localization abilities and AVH susceptibility, with relatively preserved function of left vs. right auditory cortex predisposing to more severe AVH, and support models that attribute persistent AVH to impaired source-monitoring. The findings suggest new approaches for therapeutic intervention for both AVH and thought disorder in schizophrenia.

Multidimensional Connectomics and Treatment-Resistant Schizophrenia: Linking Phenotypic Circuits to Targeted Therapeutics

Schizophrenia is a very complex syndrome that involves widespread brain multi-dysconnectivity. Neural circuits within specific brain regions and their links to corresponding regions are abnormal in the illness. Theoretical models of dysconnectivity and the investigation of connectomics and brain network organization have been examined in schizophrenia since the early nineteenth century. In more recent years, advancements have been achieved with the development of neuroimaging tools that have provided further clues to the structural and functional organization of the brain and global neural networks in the illness. Neural circuitry that extends across prefrontal, temporal and parietal areas of the cortex as well as limbic and other subcortical brain regions is disrupted in schizophrenia. As a result, many patients have a poor response to antipsychotic treatment and treatment failure is common. Treatment resistance that is specific to positive, negative, and cognitive domains of the illness may be related to distinct circuit phenotypes unique to treatment-refractory disease. Currently, there are no customized neural circuit-specific and targeted therapies that address this neural dysconnectivity. Investigation of targeted therapeutics that addresses particular areas of substantial regional dysconnectivity is an intriguing approach to precision medicine in schizophrenia. This review examines current findings of system and circuit-level brain dysconnectivity in treatment-resistant schizophrenia based on neuroimaging studies. Within a connectome context, on-off circuit connectivity synonymous with excitatory and inhibitory neuronal pathways is discussed. Mechanistic cellular, neurochemical and molecular studies are included with specific emphasis given to cell pathology and synaptic communication in glutamatergic and GABAergic systems. In this review we attempt to deconstruct how augmenting treatments may be applied within a circuit context to improve circuit integration and treatment response. Clinical studies that have used a variety of glutamate receptor and GABA interneuron modulators, nitric oxide-based therapies and a variety of other strategies as augmenting treatments with antipsychotic drugs are included. This review supports the idea that the methodical mapping of system-level networks to both on (excitatory) and off (inhibitory) cellular circuits specific to treatment-resistant disease may be a logical and productive approach in directing future research toward the advancement of targeted pharmacotherapeutics in schizophrenia.

Cortical features of distinct developmental trajectories in patients with delusional infestation

BACKGROUND

Although there is strong neuroimaging evidence that cortical alterations are a core feature of schizophrenia spectrum disorders, it still remains unclear to what extent such abnormalities occur in monothematic delusional disorders. In individuals with delusional infestation (DI), the delusional belief to be infested with pathogens, previous structural MRI studies have shown prefrontal, temporal, parietal, insular, thalamic and striatal gray matter volume changes. Differential contributions of cortical features of evolutionary and genetic origin (such as cortical thickness, area and folding) which may distinctly contribute to DI pathophysiology are unclear at present.

METHODS

In this study, 18 patients with DI and 20 healthy controls (HC) underwent MRI scanning at 1.0T. Using surface-based analyses we calculated cortical thickness, surface area and local gyrification index (LGI). Whole-brain differences between patients and controls were investigated.

RESULTS

Surface analyses revealed frontoparietal patterns exhibiting altered cortical thickness, surface area and LGI in DI patients compared to controls. Higher cortical thickness was found in the right medial orbitofrontal cortex (p<0.05, cluster-wise probability [CWP] corrected). Smaller surface area in patients was found in the left inferior temporal gyrus, the precuneus, the pars orbitalis of the right frontal gyrus, and the lingual gyrus (p<0.05, CWP corr.). Lower LGI was found in the left postcentral, bilateral precentral, right middle temporal, inferior parietal, and superior parietal gyri (p<0.01, CWP corr.).

CONCLUSION

This study lends further support to the hypothesis that cortical features of distinct evolutionary and genetic origin differently contribute to the pathogenesis of delusional disorders. Regions in which atrophy was observed are part of neural circuits associated with perception, visuospatial control and self-awareness. The data are in line with the notion of a content-specific neural signature of DI.

Resting State Effective Connectivity Allows Auditory Hallucination Discrimination

Hallucinations are elusive phenomena that have been associated with psychotic behavior, but that have a high prevalence in healthy population. Some generative mechanisms of Auditory Hallucinations (AH) have been proposed in the literature, but so far empirical evidence is scarce. The most widely accepted generative mechanism hypothesis nowadays consists in the faulty workings of a network of brain areas including the emotional control, the audio and language processing, and the inhibition and self-attribution of the signals in the auditive cortex. In this paper, we consider two methods to analyze resting state fMRI (rs-fMRI) data, in order to measure effective connections between the brain regions involved in the AH generation process. These measures are the Dynamic Causal Modeling (DCM) cross-covariance function (CCF) coefficients, and the partially directed coherence (PDC) coefficients derived from Granger Causality (GC) analysis. Effective connectivity measures are treated as input classifier features to assess their significance by means of cross-validation classification accuracy results in a wrapper feature selection approach. Experimental results using Support Vector Machine (SVM) classifiers on an rs-fMRI dataset of schizophrenia patients with and without a history of AH confirm that the main regions identified in the AH generative mechanism hypothesis have significant effective connection values, under both DCM and PDC evaluation.

Abnormal Degree Centrality of Bilateral Putamen and Left Superior Frontal Gyrus in Schizophrenia with Auditory Hallucinations: A Resting-state Functional Magnetic Resonance Imaging Study

BACKGROUND

Dysconnectivity hypothesis of schizophrenia has been increasingly emphasized. Recent researches showed that this dysconnectivity might be related to occurrence of auditory hallucination (AH). However, there is still no consistent conclusion. This study aimed to explore intrinsic dysconnectivity pattern of whole-brain functional networks at voxel level in schizophrenic with AH.

METHODS

Auditory hallucinated patients group (n = 42 APG), no hallucinated patients group (n = 42 NPG) and normal controls (n = 84 NCs) were analyzed by resting-state functional magnetic resonance imaging. The functional connectivity metrics index (degree centrality [DC]) across the entire brain networks was calculated and evaluated among three groups.

RESULTS

DC decreased in the bilateral putamen and increased in the left superior frontal gyrus in all the patients. However, in APG, the changes of DC were more obvious compared with NPG. Symptomology scores were negatively correlated with the DC of bilateral putamen in all patients. AH score of APG positively correlated with the DC in left superior frontal gyrus but negatively correlated with the DC in bilateral putamen.

CONCLUSION

Our findings corroborated that schizophrenia was characterized by functional dysconnectivity, and the abnormal DC in bilateral putamen and left superior frontal gyrus might be crucial in the occurrence of AH.

Patterns of Co-Occurring Gray Matter Concentration Loss across the Huntington Disease Prodrome

Huntington disease (HD) is caused by an abnormally expanded cytosine-adenine-guanine (CAG) trinucleotide repeat in the HTT gene. Age and CAG-expansion number are related to age at diagnosis and can be used to index disease progression. However, observed onset-age variability suggests that other factors also modulate progression. Indexing prodromal (pre-diagnosis) progression may highlight therapeutic targets by isolating the earliest-affected factors. We present the largest prodromal HD application of the univariate method voxel-based morphometry (VBM) and the first application of the multivariate method source-based morphometry (SBM) to, respectively, compare gray matter concentration (GMC) and capture co-occurring GMC patterns in control and prodromal participants. Using structural MRI data from 1050 (831 prodromal, 219 control) participants, we characterize control-prodromal, whole-brain GMC differences at various prodromal stages. Our results provide evidence for (1) regional co-occurrence and differential patterns of decline across the prodrome, with parietal and occipital differences commonly co-occurring, and frontal and temporal differences being relatively independent from one another, (2) fronto-striatal circuits being among the earliest and most consistently affected in the prodrome, (3) delayed degradation in some movement-related regions, with increasing subcortical and occipital differences with later progression, (4) an overall superior-to-inferior gradient of GMC reduction in frontal, parietal, and temporal lobes, and (5) the appropriateness of SBM for studying the prodromal HD population and its enhanced sensitivity to early prodromal and regionally concurrent differences.