A review of MRI findings in schizophrenia

Discriminant analysis using MRI asymmetry indices and cognitive scores of women with temporal lobe epilepsy or schizophrenia

PURPOSE

This study aims to assess the diagnostic power of brain asymmetry indices and neuropsychological tests for differentiating mesial temporal lobe epilepsy (MTLE) and schizophrenia (SCZ).

METHODS

We studied a total of 39 women including 13 MTLE, 13 SCZ, and 13 healthy individuals (HC). A neuropsychological test battery (NPT) was administered and scored by an experienced neuropsychologist, and NeuroQuant (CorTechs Labs Inc., San Diego, California) software was used to calculate brain asymmetry indices (ASI) for 71 different anatomical regions of all participants based on their 3D T1 MR imaging scans.

RESULTS

Asymmetry indices measured from 10 regions showed statistically significant differences between the three groups. In this study, a multi-class linear discriminant analysis (LDA) model was built based on a total of fifteen variables composed of the most five significantly informative NPT scores and ten significant asymmetry indices, and the model achieved an accuracy of 87.2%. In pairwise classification, the accuracy for distinguishing MTLE from either SCZ or HC was 94.8%, while the accuracy for distinguishing SCZ from either MTLE or HC was 92.3%.

CONCLUSION

The ability to differentiate MTLE from SCZ using neuroradiological and neuropsychological biomarkers, even within a limited patient cohort, could make a substantial contribution to research in larger patient groups using different machine learning techniques.

Diagnosing schizophrenia using deep learning: Novel interpretation approaches and multi-site validation

Schizophrenia is a profound and enduring mental disorder that imposes significant negative impacts on individuals, their families, and society at large. The development of more accurate and objective diagnostic tools for schizophrenia can be expedited through the employment of deep learning (DL), that excels at deciphering complex hierarchical non-linear patterns. However, the limited interpretability of deep learning has eroded confidence in the model and restricted its clinical utility. At the same time, if the data source is only derived from a single center, the model's generalizability is difficult to test. To enhance the model's reliability and applicability, leave-one-center-out validation with a large and diverse sample from multiple centers is crucial. In this study, we utilized Nine different global centers to train and test the 3D Resnet model's generalizability, resulting in an 82% classification performance (area under the curve) on all datasets sourced from different countries, employing a leave-one-center-out-validation approach. Per our approximation of the feature significance of each region on the atlas, we identified marked differences in the thalamus, pallidum, and inferior frontal gyrus between individuals with schizophrenia and healthy controls, lending credence to prior research findings. At the same time, in order to translate the model's output into clinically applicable insights, the SHapley Additive exPlanations (SHAP) permutation explainer method with an anatomical atlas have been refined, thereby offering precise neuroanatomical and functional interpretations of different brain regions.

Compensatory thickening of cortical thickness in early stage of schizophrenia

Brain structural abnormality has been observed in the prodromal and early stages of schizophrenia, but the mechanism behind it is not clear. In this study, to explore the association between cortical abnormalities, metabolite levels, inflammation levels and clinical symptoms of schizophrenia, 51 drug-naive first-episode schizophrenia (FES) patients, 51 ultra-high risk for psychosis (UHR), and 51 healthy controls (HC) were recruited. We estimated gray matter volume (GMV), cortical thickness (CT), concentrations of different metabolites, and inflammatory marks among four groups (UHR converted to psychosis [UHR-C], UHR unconverted to psychosis [UHR-NC], FES, HC). UHR-C group had more CT in the right lateral occipital cortex and the right medial orbito-frontal cortex (rMOF), while a significant reduction in CT of the right fusiform cortex was observed in FES group. UHR-C group had significantly higher concentration of IL-6, while IL-17 could significantly predict CT of the right fusiform and IL-4 and IL-17 were significant predictors of CT in the rMOF. To conclude, it is reasonable to speculate that the increased CT in UHR-C group is related to the inflammatory response, and may participate in some compensatory mechanism, but might become exhaustive with the progress of the disease due to potential neurotoxic effects.

Association of histone modification with the development of schizophrenia

Schizophrenia, influenced by genetic and environmental factors, may involve epigenetic alterations, notably histone modifications, in its pathogenesis. This review summarizes various histone modifications including acetylation, methylation, phosphorylation, ubiquitination, serotonylation, lactylation, palmitoylation, and dopaminylation, and their implications in schizophrenia. Current research predominantly focuses on histone acetylation and methylation, though other modifications also play significant roles. These modifications are crucial in regulating transcription through chromatin remodeling, which is vital for understanding schizophrenia's development. For instance, histone acetylation enhances transcriptional efficiency by loosening chromatin, while increased histone methyltransferase activity on H3K9 and altered histone phosphorylation, which reduces DNA affinity and destabilizes chromatin structure, are significant markers of schizophrenia.

Investigation of Skull Cortical Thickness Changes in Healthy Population and Patients With Schizophrenia on Computed Tomography Images

Cortical bone thickness is essential for the mechanical function of bone. Some factors including aging, sex, body size, hormone levels, behavior, and genetics lead to changes in cranial cortical robusticity. Moreover, the skull is one of the hardest and most durable structures in the human body. Schizophrenia is defined as a psychiatric disease characterized by delusions and hallucinations, and these patients have reduced brain volume; however, there is no study including cortical bone structure. For this reason, the aim of this study was to determine whether there is a difference in the skull cortical thickness of patients with schizophrenia and, compare it with healthy subjects. The cranial length, cranial width, anterior cortical thickness, right and left anterior cortical thickness, right and left lateral cortical thickness, right and left posterior lateral thickness, and posterior cortical thickness were measured with axial computed tomography images of 30 patients with schizophrenia and 132 healthy individuals aged between 18 and 69years. A statistically significant difference was found between the two groups in the measurements of right and left posterior lateral thickness, and posterior cortical thickness ( P = 0.006, P = 0.001, and P = 0.047, respectively). The sexes were compared, and it was found that the cranial width, anterior thickness, left anterior thickness, and right and left posterior thickness measurements of patients with schizophrenia showed a statistically significant difference compared with the control group ( P < 0.001, P = 0.003, P = 0.001, P < 0.001 and P < 0.001, respectively). The authors observed that skull cortical thickness may be different in schizophrenia. The results obtained from this study may be beneficial for evaluating these structures for clinical and pathological processes. Furthermore, knowledge about the skull cortical thickness in planning surgical procedures will increase the reliability and effectiveness of the surgical method, and this will minimize the risk of complications.

Brain Age Gap in Early Illness Schizophrenia and the Clinical High-Risk Syndrome: Associations With Experiential Negative Symptoms and Conversion to Psychosis

BACKGROUND AND HYPOTHESIS

Brain development/aging is not uniform across individuals,spawning efforts to characterize brain age from a biological perspective to model the effects of disease and maladaptive life processes on the brain. The brain age gap represents the discrepancy between estimated brain biological age and chronological age (in this case, based on structural magnetic resonance imaging, MRI). Structural MRI studies report an increased brain age gap (biological age > chronological age) in schizophrenia, with a greater brain age gap related to greater negative symptom severity. Less is known regarding the nature of this gap early in schizophrenia (ESZ), if this gap represents a psychosis conversion biomarker in clinical high-risk (CHR-P) individuals, and how altered brain development and/or agingmap onto specific symptom facets.

STUDY DESIGN

Using structural MRI, we compared the brain age gap among CHR-P (n = 51), ESZ (n = 78), and unaffected comparison participants (UCP; n = 90), and examined associations with CHR-P psychosis conversion (CHR-P converters n = 10; CHR-P non-converters; n = 23) and positive and negative symptoms.

STUDY RESULTS

ESZ showed a greater brain age gap relative to UCP and CHR-P (Ps < .010). CHR-P individuals who converted to psychosis showed a greater brain age gap (P = .043) relative to CHR-P non-converters. A larger brain age gap in ESZ was associated with increased experiential (P = .008), but not expressive negative symptom severity.

CONCLUSIONS

Consistent with schizophrenia pathophysiological models positing abnormal brain maturation, results suggest abnormal brain development is present early in psychosis. An increased brain age gap may be especially relevant to motivational and functional deficits in schizophrenia.

Optic nerve head neurovascular assessments in patients with schizophrenia: A cross-sectional study

Objective

The retina is a protrusion of the brain, so researchers have recently proposed retinal changes as a new marker for studying central nervous system diseases. To investigate optic nerve head neurovascular structure assessed by optical coherence tomography angiography (OCTA) in schizophrenia compared to healthy subjects.

Methods

The study was conducted from 2019 to 2021 at the Ibn Sina Psychiatric Hospital in Mashhad, Iran. We enrolled 22 hospitalized known cases of schizophrenia, treated with risperidone as an antipsychotic drug, and 22 healthy subjects. The two groups were matched in age and gender. In the schizophrenic group, the positive and negative syndrome scale test was used to assess the illness severity. All subjects underwent complete ophthalmic evaluations and OCTA imaging.

Results

We found that the cup/disc area ratio, vertical cup/disc ratio, and horizontal cup/disc ratio are significantly higher in patients with schizophrenia than in healthy subjects (with p-values of 0.019, 0.015, and 0.022, respectively). No statistically significant difference in the peripapillary retinal nerve fiber layer and vascular parameters of the optic nerve head was observed between schizophrenia and healthy groups.

Conclusion

We found evidence regarding the difference in the optic nerve head tomographic properties in schizophrenia compared to healthy subjects. However, ONH vascular parameters showed no significant difference. More studies are needed for a definite conclusion.

Changes in responses of the amygdala and hippocampus during fear conditioning are associated with persecutory beliefs

The persecutory delusion is the most common symptom of psychosis, yet its underlying neurobiological mechanisms are poorly understood. Prior studies have suggested that abnormalities in medial temporal lobe-dependent associative learning may contribute to this symptom. In the current study, this hypothesis was tested in a non-clinical sample of young adults without histories of psychiatric treatment (n = 64), who underwent classical Pavlovian fear conditioning while fMRI data were collected. During the fear conditioning procedure, participants viewed images of faces which were paired (the CS+) or not paired (the CS-) with an aversive stimulus (a mild electrical shock). Fear conditioning-related neural responses were measured in two medial temporal lobe regions, the amygdala and hippocampus, and in other closely connected brain regions of the salience and default networks. The participants without persecutory beliefs (n = 43) showed greater responses to the CS- compared to the CS+ in the right amygdala and hippocampus, while the participants with persecutory beliefs (n = 21) failed to exhibit this response. These between-group differences were not accounted for by symptoms of depression, anxiety or a psychosis risk syndrome. However, the severity of subclinical psychotic symptoms overall was correlated with the level of this aberrant response in the amygdala (p = .013) and hippocampus (p = .033). Thus, these findings provide evidence for a disruption of medial temporal lobe-dependent associative learning in young people with subclinical psychotic symptoms, specifically persecutory thinking.

A novel biomarker selection method using multimodal neuroimaging data

Identifying biomarkers is essential to obtain the optimal therapeutic benefit while treating patients with late-life depression (LLD). We compare LLD patients with healthy controls (HC) using resting-state functional magnetic resonance and diffusion tensor imaging data to identify neuroimaging biomarkers that may be potentially associated with the underlying pathophysiology of LLD. We implement a Bayesian multimodal local false discovery rate approach for functional connectivity, borrowing strength from structural connectivity to identify disrupted functional connectivity of LLD compared to HC. In the Bayesian framework, we develop an algorithm to control the overall false discovery rate of our findings. We compare our findings with the literature and show that our approach can better detect some regions never discovered before for LLD patients. The Hub of our discovery related to various neurobehavioral disorders can be used to develop behavioral interventions to treat LLD patients who do not respond to antidepressants.

Large-scale coupling of prefrontal activity patterns as a mechanism for cognitive control in health and disease: evidence from rodent models

Cognitive control of behavior is crucial for well-being, as allows subject to adapt to changing environments in a goal-directed way. Changes in cognitive control of behavior is observed during cognitive decline in elderly and in pathological mental conditions. Therefore, the recovery of cognitive control may provide a reliable preventive and therapeutic strategy. However, its neural basis is not completely understood. Cognitive control is supported by the prefrontal cortex, structure that integrates relevant information for the appropriate organization of behavior. At neurophysiological level, it is suggested that cognitive control is supported by local and large-scale synchronization of oscillatory activity patterns and neural spiking activity between the prefrontal cortex and distributed neural networks. In this review, we focus mainly on rodent models approaching the neuronal origin of these prefrontal patterns, and the cognitive and behavioral relevance of its coordination with distributed brain systems. We also examine the relationship between cognitive control and neural activity patterns in the prefrontal cortex, and its role in normal cognitive decline and pathological mental conditions. Finally, based on these body of evidence, we propose a common mechanism that may underlie the impaired cognitive control of behavior.

Brain Abnormalities in Schizophrenia: A Comparative Imagistic Study

Background and Objectives: Neuroimaging reveals a link between psychiatric conditions and brain structural-functional changes, prompting a paradigm shift in viewing schizophrenia as a neurodevelopmental disorder. This study aims to identify and compare structural brain changes found during the first schizophrenia episode with those found after more than 5 years of illness. Materials and Methods: This prospective study involved 149 participants enrolled between 1 January 2019 and 31 December 2021. The participants were categorized into three groups: the first comprises 51 individuals with an initial psychotic episode, the second consists of 49 patients diagnosed with schizophrenia for over 5 years, and a control group comprising 50 individuals without a diagnosis of schizophrenia or any other psychotic disorder. All participants underwent brain CT examinations. Results: The study examined all three groups: first-episode schizophrenia (FES), schizophrenia (SCZ), and the control group. The FES group had a mean age of 26.35 years and a mean duration of illness of 1.2 years. The SCZ group, with a mean age of 40.08 years, had been diagnosed with schizophrenia for an average of 15.12 years. The control group, with a mean age of 34.60 years, had no schizophrenia diagnosis. Structural measurements revealed widening of frontal horns and lateral ventricles in the SCZ group compared to FES and the FES group compared to the control group. Differences in the dimensions of the third ventricle were noted between SCZ and FES, while no distinction was observed between FES and the control group. The fourth ventricle had similar measurements in FES and SCZ groups, both exceeding those of the control group. Our results showed higher densities in the frontal lobe in schizophrenia patients compared to FES and the control group, with the control group consistently displaying the lowest densities. Conclusions: In summary, our comparative imaging analysis of schizophrenia patients, first-episode schizophrenia, and control patients revealed distinct ventricular patterns, with SCZ showing greater widening than FES and FES wider than the control group. Frontal lobe density, assessed via cerebral CT scans, indicated a higher density in the SCZ group in both anterior and posterior cortex portions compared to FES and the control group, while the left posterior cortex in FES had the highest density. These findings highlight unique neuroanatomical features across groups, shedding light on structural differences associated with different stages of schizophrenia.

Estrogen and psychosis - a review and future directions

The link between sex hormones and schizophrenia has been suspected for over a century; however, scientific evidence supporting the pharmacotherapeutic effects of exogenous estrogen has only started to emerge during the past three decades. Accumulating evidence from epidemiological and basic research suggests that estrogen has a protective effect in women vulnerable to schizophrenia. Such evidence has led multiple researchers to investigate the role of estrogen in schizophrenia and its use in treatment. This narrative review provides an overview of the effects of estrogen as well as summarizes the recent work regarding estrogen as a treatment for schizophrenia, particularly the use of new-generation selective estrogen receptor modulators.

Proteomic profiling in the progression of psychosis: Analysis of clinical high-risk, first episode psychosis, and healthy controls

BACKGROUND AND HYPOTHESIS

Recent evidence has highlighted the benefits of early detection and treatment for better clinical outcomes in patients with psychosis. Biological markers of the disease have become a focal point of research. This study aimed to identify protein markers detectable in the early stages of psychosis and indicators of progression by comparing them with those of healthy controls (HC) and first episode psychosis (FEP).

STUDY DESIGN

The participants comprised 28 patients in the clinical high-risk (CHR) group, 49 patients with FEP, and 61 HCs aged 15-35 years. Blood samples were collected and analyzed using multiple reaction monitoring-mass spectrometry to measure the expression of 158 peptide targets. Data were adjusted for age, sex, and use of psychotropic drugs.

STUDY RESULTS

A total of 18 peptides (17 proteins) differed significantly among the groups. The protein PRDX2 was higher in the FEP group than in the CHR and HC groups and showed increased expression according to disease progression. The levels of six proteins were significantly higher in the FEP group than in the CHR group. Nine proteins differed significantly in the CHR group compared to the other groups. Sixteen proteins were significantly correlated with symptom severity. These proteins are primarily related to the coagulation cascade, inflammatory response, brain structure, and synaptic plasticity.

CONCLUSIONS

Our findings suggested that peripheral protein markers reflect disease progression in patients with psychosis. Further longitudinal research is needed to confirm these findings and to identify the specific roles of these markers in the pathogenesis of schizophrenia.

Pathologic complete response prediction in breast cancer lesion segmentation and neoadjuvant therapy

Objectives

Predicting whether axillary lymph nodes could achieve pathologic Complete Response (pCR) after breast cancer patients receive neoadjuvant chemotherapy helps make a quick follow-up treatment plan. This paper presents a novel method to achieve this prediction with the most effective medical imaging method, Dynamic Contrast-enhanced Magnetic Resonance Imaging (DCE-MRI).

Methods

In order to get an accurate prediction, we first proposed a two-step lesion segmentation method to extract the breast cancer lesion region from DCE-MRI images. With the segmented breast cancer lesion region, we then used a multi-modal fusion model to predict the probability of axillary lymph nodes achieving pCR.

Results

We collected 361 breast cancer samples from two hospitals to train and test the proposed segmentation model and the multi-modal fusion model. Both segmentation and prediction models obtained high accuracy.

Conclusion

The results show that our method is effective in both the segmentation task and the pCR prediction task. It suggests that the presented methods, especially the multi-modal fusion model, can be used for the prediction of treatment response in breast cancer, given data from noninvasive methods only.

ROI-based analysis of diffusion indices in healthy subjects and subjects with deficit or non-deficit syndrome schizophrenia

We analyzed DTI data involving 22 healthy subjects (HC), 15 patients with deficit syndrome schizophrenia (DSZ), and 25 patients with non-deficit syndrome schizophrenia (NDSZ). We used a 1.5-T MRI scanner to collect diffusion-weighted images and T1 images, which were employed to correct distortions and deformations within the diffusion-weighted images. For 156 regions of interest (ROI), we calculated the average fractional anisotropy (FA), mean diffusion (MD), and radial diffusion (RD). Each ROI underwent a group-wise comparison using permutation F-test, followed by post hoc pairwise comparisons with Bonferroni correction. In general, we observed lower FA in both schizophrenia groups compared to HC (i.e., HC>(DSZ=NDSZ)), while MD and RD showed the opposite pattern. Notably, specific ROIs with reduced FA in schizophrenia patients included bilateral nucleus accumbens, left fusiform area, brain stem, anterior corpus callosum, left rostral and caudal anterior cingulate, right posterior cingulate, left thalamus, left hippocampus, left inferior temporal cortex, right superior temporal cortex, left pars triangularis and right lingual gyrus. Significantly, the right cuneus exhibited lower FA in the DSZ group compared to other groups ((HC=NDSZ)>DSZ), without affecting MD and RD. These results indicate that compromised neural integrity in the cuneus may contribute to the pathophysiological distinctions between DSZ and NDSZ.

Clinical and biological correlates of optical coherence tomography findings in schizophrenia

There is a growing body of evidence indicating retinal layer thinning in schizophrenia. However, neuropathological processes underlying these retinal structural changes and its clinical correlates are yet to be known. Here, we aim to investigate the clinical and biological correlates of OCT findings in schizophrenia. 50 schizophrenia patients and 40 healthy controls were recruited. Retinal nerve fiber layer (RNFL), ganglion cell layer (GCL), inner plexiform layer (IPL), and macular and choroidal thicknesses were recorded. A comprehensive battery of neuropsychological tests was applied. Fasting glucose, triglycerides and HDL-cholesterol levels, TNF-α, IL-1β and IL-6 levels were measured. Right IPL was significantly thinner in patients than the controls after controlling for various confounders (F = 5.42, p = .02). Higher IL-6, IL-1β, and TNF-α levels were associated with decreased left macular thickness (r =  - 0.26, p = .027, r =  - 0.30, p = 0.012, and r =  - 0.24, p = .046, respectively) and higher IL-6 was associated with thinning of right IPL (r =  - 0.27, p = 0.023) and left choroid (r =  - 0.23, p = .044) in the overall sample. Thinning of right IPL and left macula were also associated with worse executive functioning (r = 0.37, p = 0.004 and r = 0.33, p = 0.009) and attention (r = 0.31, p = 0.018 and r = 0.30, p = 0.025). In patients with schizophrenia, IPL thinning was associated with increased BMI (r =  - 0.44, p = 0.009) and decreased HDL levels (r = 0.43, p = 0.021). Decreased TNF-α level was related to IPL thinning, especially in the left eye (r = 0.40, p = 0.022). These findings support the hypothesis that OCT might provide the opportunity to establish an accessible and non-invasive probe of brain pathology in schizophrenia and related disorders. However, future studies investigating retinal structural changes as a biological marker for schizophrenia should also consider the metabolic state of the subjects.

Predicting narcissistic personality traits from brain and psychological features: A supervised machine learning approach

Narcissism is a multifaceted construct often linked to pathological conditions whose neural correlates are still poorly understood. Previous studies have reported inconsistent findings related to the neural underpinnings of narcissism, probably due to methodological limitations such as the low number of participants or the use of mass univariate methods. The present study aimed to overcome the previous methodological limitations and to build a predictive model of narcissistic traits based on neural and psychological features. In this respect, two machine learning-based methods (Kernel Ridge Regression and Support Vector Regression) were used to predict narcissistic traits from brain structural organization and from other relevant normal and abnormal personality features. Results showed that a circuit including the lateral and middle frontal gyri, the angular gyrus, Rolandic operculum, and Heschl's gyrus successfully predicted narcissistic personality traits (p < 0.003). Moreover, narcissistic traits were predicted by normal (openness, agreeableness, conscientiousness) and abnormal (borderline, antisocial, insecure, addicted, negativistic, machiavellianism) personality traits. This study is the first to predict narcissistic personality traits via a supervised machine learning approach. As such, these results may expand the possibility of deriving personality traits from neural and psychological features.

Mean Intracranial Volume of Brain among Patients with Normal Magnetic Resonance Imaging Referred to the Department of Radiology and Imaging of a Tertiary Care Centre

Introduction

The measurement of brain volume is an important aspect of the assessment of brain structure and function. However, limited data is available on brain volumetry in the Nepalese population. The study aimed to find the mean intracranial volume of the brain among patients with normal magnetic resonance imaging referred to the Department of Radiology and Imaging of a tertiary care centre.

Methods

A descriptive cross-sectional study was conducted among patients with normal magnetic resonance imaging referred to the Department of Radiology and Imaging in a tertiary care centre. All magnetic resonance imaging of the brain during the study period was reviewed by a radiologist. Magnetic resonance imaging with abnormal findings, clinical signs of neurological deficit, dementia and psychiatric symptoms were excluded from the study. A convenience sampling method was used. The point estimate was calculated at a 95% Confidence Interval.

Results

Among 285 Magnetic Resonance Imaging datasets, the mean intracranial volume was 1286.30±129.88 cc (1271.22-1301.38, 95% of Confidence Interval). The mean cerebral volume was 985.06±106.4 cc, cerebellar volume was 126.99±13.05 cc and brain stem volume was 19.97±2.54 cc.

Conclusions

The mean intracranial volume of the brain among patients with normal magnetic resonance imaging was found to be lower than other studies done in similar settings.

Keywords

brainstem; cerebellum; cerebrum; magnetic resonance imaging.

Effects of Substance Use and Antisocial Personality on Neuroimaging-Based Machine Learning Prediction of Schizophrenia

BACKGROUND AND HYPOTHESIS

Neuroimaging-based machine learning (ML) algorithms have the potential to aid the clinical diagnosis of schizophrenia. However, literature on the effect of prevalent comorbidities such as substance use disorder (SUD) and antisocial personality (ASPD) on these models' performance has remained unexplored. We investigated whether the presence of SUD or ASPD affects the performance of neuroimaging-based ML models trained to discern patients with schizophrenia (SCH) from controls.

STUDY DESIGN

We trained an ML model on structural MRI data from public datasets to distinguish between SCH and controls (SCH = 347, controls = 341). We then investigated the model's performance in two independent samples of individuals undergoing forensic psychiatric examination: sample 1 was used for sensitivity analysis to discern ASPD (N = 52) from SCH (N = 66), and sample 2 was used for specificity analysis to discern ASPD (N = 26) from controls (N = 25). Both samples included individuals with SUD.

STUDY RESULTS

In sample 1, 94.4% of SCH with comorbid ASPD and SUD were classified as SCH, followed by patients with SCH + SUD (78.8% classified as SCH) and patients with SCH (60.0% classified as SCH). The model failed to discern SCH without comorbidities from ASPD + SUD (AUC = 0.562, 95%CI = 0.400-0.723). In sample 2, the model's specificity to predict controls was 84.0%. In both samples, about half of the ASPD + SUD were misclassified as SCH. Data-driven functional characterization revealed associations between the classification as SCH and cognition-related brain regions.

CONCLUSION

Altogether, ASPD and SUD appear to have effects on ML prediction performance, which potentially results from converging cognition-related brain abnormalities between SCH, ASPD, and SUD.

Spectral and phase-coherence correlates of impaired auditory mismatch negativity (MMN) in schizophrenia: A MEG study

BACKGROUND

Reduced auditory mismatch negativity (MMN) is robustly impaired in schizophrenia. However, mechanisms underlying dysfunctional MMN generation remain incompletely understood. This study aimed to examine the role of evoked spectral power and phase-coherence towards deviance detection and its impairments in schizophrenia.

METHODS

Magnetoencephalography data was collected in 16 male schizophrenia patients and 16 male control participants during an auditory MMN paradigm. Analyses of event-related fields (ERF), spectral power and inter-trial phase-coherence (ITPC) focused on Heschl's gyrus, superior temporal gyrus, inferior/medial frontal gyrus and thalamus.

RESULTS

MMNm ERF amplitudes were reduced in patients in temporal, frontal and subcortical regions, accompanied by decreased theta-band responses, as well as by a diminished gamma-band response in auditory cortex. At theta/alpha frequencies, ITPC to deviant tones was reduced in patients in frontal cortex and thalamus. Patients were also characterized by aberrant responses to standard tones as indexed by reduced theta-/alpha-band power and ITPC in temporal and frontal regions. Moreover, stimulus-specific adaptation was decreased at theta/alpha frequencies in left temporal regions, which correlated with reduced MMNm spectral power and ERF amplitude. Finally, phase-reset of alpha-oscillations after deviant tones in left thalamus was impaired, which correlated with impaired MMNm generation in auditory cortex. Importantly, both non-rhythmic and rhythmic components of spectral activity contributed to the MMNm response.

CONCLUSIONS

Our data indicate that deficits in theta-/alpha- and gamma-band activity in cortical and subcortical regions as well as impaired spectral responses to standard sounds could constitute potential mechanisms for dysfunctional MMN generation in schizophrenia, providing a novel perspective towards MMN deficits in the disorder.

A Network Model of the Modulation of γ Oscillations by NMDA Receptors in Cerebral Cortex

Psychotic drugs such as ketamine induce symptoms close to schizophrenia and stimulate the production of γ oscillations, as also seen in patients, but the underlying mechanisms are still unclear. Here, we have used computational models of cortical networks generating γ oscillations, and have integrated the action of drugs such as ketamine to partially block NMDA receptors (NMDARs). The model can reproduce the paradoxical increase of γ oscillations by NMDA receptor antagonists, assuming that antagonists affect NMDA receptors with higher affinity on inhibitory interneurons. We next used the model to compare the responsiveness of the network to external stimuli, and found that when NMDA channels are blocked, an increase of γ power is observed altogether with an increase of network responsiveness. However, this responsiveness increase applies not only to γ states, but also to asynchronous states with no apparent γ. We conclude that NMDA antagonists induce an increased excitability state, which may or may not produce γ oscillations, but the response to external inputs is exacerbated, which may explain phenomena such as altered perception or hallucinations.

fMRI fluctuations within the language network are correlated with severity of hallucinatory symptoms in schizophrenia

Although schizophrenia (SZ) represents a complex multiform psychiatric disorder, one of its most striking symptoms are auditory verbal hallucinations (AVH). While the neurophysiological origin of this pervasive symptom has been extensively studied, there is so far no consensus conclusion on the neural correlates of the vulnerability to hallucinate. With a network-based fMRI approach, following the hypothesis of altered hemispheric dominance (Crow, 1997), we expected that LN alterations might result in self-other distinction impairments in SZ patients, and lead to the distressing subjective experiences of hearing voices. We used the independent component analysis of resting-state fMRI data, to first analyze LN connectivity in three groups of participants: SZ patients with and without hallucinations (AVH/D+ and AVH/D-, respectively), and a matched healthy control (HC) group. Then, we assessed the fMRI fluctuations using additional analyses based on fractional Amplitude of Low Frequency-Fluctuations (fALFF), both at the network- and region of interest (ROI)-level. Specific LN nodes were recruited in the right hemisphere (insula and Broca homologous area) for AVH/D+ , but not for HC and AVH/D-, consistent with a left hemisphere deficit in AVH patients. The fALFF analysis at the ROI level showed a negative correlation between fALFF Slow-4 and P1 Delusions PANSS subscale and a positive correlation between the fALFF Slow-5 and P3 Hallucination PANSS subscale for AVH/D+ only. These effects were not a consequence of structural differences between groups, as morphometric analysis did not evidence any group differences. Given the role of language as an emerging property resulting from the integration of many high-level cognitive processes and the underlying cortical areas, our results suggest that LN features from fMRI connectivity and fluctuations can be a marker of neurophysiological features characterizing SZ patients depending on their vulnerability to hallucinate.

Abnormal and Changing Information Interaction in Adults with Attention-Deficit/Hyperactivity Disorder Based on Network Motifs

Network motif analysis approaches provide insights into the complexity of the brain's functional network. In recent years, attention-deficit/hyperactivity disorder (ADHD) has been reported to result in abnormal information interactions in macro- and micro-scale functional networks. However, most existing studies remain limited due to potentially ignoring meso-scale topology information. To address this gap, we aimed to investigate functional motif patterns in ADHD to unravel the underlying information flow and analyze motif-based node roles to characterize the different information interaction methods for identifying the abnormal and changing lesion sites of ADHD. The results showed that the interaction functions of the right hippocampus and the right amygdala were significantly increased, which could lead patients to develop mood disorders. The information interaction of the bilateral thalamus changed, influencing and modifying behavioral results. Notably, the capability of receiving information in the left inferior temporal and the right lingual gyrus decreased, which may cause difficulties for patients in processing visual information in a timely manner, resulting in inattention. This study revealed abnormal and changing information interactions based on network motifs, providing important evidence for understanding information interactions at the meso-scale level in ADHD patients.

Social Withdrawal, Loneliness, and Health in Schizophrenia: Psychological and Neural Mechanisms

BACKGROUND AND HYPOTHESIS

Some of the most debilitating aspects of schizophrenia and other serious mental illnesses (SMI) are the impairments in social perception, motivation, and behavior that frequently accompany these conditions. These impairments may ultimately lead to chronic social disconnection (ie, social withdrawal, objective isolation, and perceived social isolation or loneliness), which may contribute to the poor cardiometabolic health and early mortality commonly observed in SMI. However, the psychological and neurobiological mechanisms underlying relationships between impairments in social perception and motivation and social isolation and loneliness in SMI remain incompletely understood.

STUDY DESIGN

A narrative, selective review of studies on social withdrawal, isolation, loneliness, and health in SMI.

STUDY RESULTS

We describe some of what is known and hypothesized about the psychological and neurobiological mechanisms of social disconnection in the general population, and how these mechanisms may contribute to social isolation and loneliness, and their consequences, in individuals with SMI.

CONCLUSIONS

A synthesis of evolutionary and cognitive theories with the "social homeostasis" model of social isolation and loneliness represents one testable framework for understanding the dynamic cognitive and biological correlates, as well as the health consequences, of social disconnection in SMI. The development of such an understanding may provide the basis for novel approaches for preventing or treating both functional disability and poor physical health that diminish the quality and length of life for many individuals with these conditions.

Detecting schizophrenia with 3D structural brain MRI using deep learning

Schizophrenia is a chronic neuropsychiatric disorder that causes distinct structural alterations within the brain. We hypothesize that deep learning applied to a structural neuroimaging dataset could detect disease-related alteration and improve classification and diagnostic accuracy. We tested this hypothesis using a single, widely available, and conventional T1-weighted MRI scan, from which we extracted the 3D whole-brain structure using standard post-processing methods. A deep learning model was then developed, optimized, and evaluated on three open datasets with T1-weighted MRI scans of patients with schizophrenia. Our proposed model outperformed the benchmark model, which was also trained with structural MR images using a 3D CNN architecture. Our model is capable of almost perfectly (area under the ROC curve = 0.987) distinguishing schizophrenia patients from healthy controls on unseen structural MRI scans. Regional analysis localized subcortical regions and ventricles as the most predictive brain regions. Subcortical structures serve a pivotal role in cognitive, affective, and social functions in humans, and structural abnormalities of these regions have been associated with schizophrenia. Our finding corroborates that schizophrenia is associated with widespread alterations in subcortical brain structure and the subcortical structural information provides prominent features in diagnostic classification. Together, these results further demonstrate the potential of deep learning to improve schizophrenia diagnosis and identify its structural neuroimaging signatures from a single, standard T1-weighted brain MRI.

Structural brain networks in schizophrenia based on nonnegative matrix factorization

Schizophrenia is a severe mental disease with significant morphometric reductions in gray matter volume and cortical thickness in a variety of brain regions. However, most studies only focused on the voxel level alterations in specific cerebral regions and ignored the spatial relationship between voxels. In the present study, we used a novel, data-driven technique-nonnegative matrix factorization (NMF) to group voxels with similar information into a network, and studied the structural covariance at the network level in schizophrenia. Our sample included 36 patients with schizophrenia and 21 healthy controls. Compared with healthy controls, patients with schizophrenia showed significant gray matter volume reductions in six structural covariance networks (dorsal striatum, thalamus, hippocampus-parahippocampus, supplementary motor area-fusiform, middle/inferior temporal network, frontal-parietal-occipital network). Our findings confirmed the assumption of a disturbance in the cortical-subcortical circuit in schizophrenia and suggested that NMF is a useful multivariate method to identify brain networks, which provides a new perspective to study the neural mechanism in schizophrenia.

Reduced cortical neuron number and neuron density in schizophrenia with focus on area 24: a post-mortem case-control study

Structural and functional abnormalities of the anterior cingulate cortex (ACC) have frequently been identified in schizophrenia. Alterations of von Economo neurons (VENs), a class of specialized projection neurons, have been found in different neuropsychiatric disorders and are also suspected in schizophrenia. To date, however, no definitive conclusions can be drawn about quantitative histologic changes in the ACC in schizophrenia because of a lack of rigorous, design-based stereologic studies. In the present study, the volume, total neuron number and total number of VENs in layer V of area 24 were determined in both hemispheres of postmortem brains from 12 male patients with schizophrenia and 11 age-matched male controls. To distinguish global from local effects, volume and total neuron number were also determined in the whole area 24 and whole cortical gray matter (CGM). Measurements were adjusted for hemisphere, age, postmortem interval and fixation time using an ANCOVA model. Compared to controls, patients with schizophrenia showed alterations, with lower mean total neuron number in CGM (- 14.9%, P = 0.007) and in layer V of area 24 (- 21.1%, P = 0.002), and lower mean total number of VENs (- 28.3%, P = 0.027). These data provide evidence for ACC involvement in the pathophysiology of schizophrenia, and complement neuroimaging findings of impaired ACC connectivity in schizophrenia. Furthermore, these results support the hypothesis that the clinical presentation of schizophrenia, particularly deficits in social cognition, is associated with pathology of VENs.

Hippocampal Connectivity with the Default Mode Network is Linked to Hippocampal Volume in the Clinical High Risk for Psychosis Syndrome and Healthy Individuals

Reduced hippocampal volume (HV) is an established brain morphological feature of psychiatric conditions. HV is associated with brain connectivity in humans and non-human animals and altered connectivity is associated with risk for psychiatric illness. Associations between HV and connectivity remain poorly characterized in humans, and especially in phases of psychiatric illness that precede disease onset. This study examined associations between HV and hippocampal functional connectivity (FC) during rest in 141 healthy controls and 248 individuals at-risk for psychosis. Significant inverse associations between HV and hippocampal FC with the inferior parietal lobe (IPL) and thalamus were observed. Select associations between hippocampal FC and HV were moderated by diagnostic group. Significant moderation results shifted from implicating the IPL to the temporal pole after excluding participants on antipsychotic medication. Considered together, this work implicates hippocampal FC with the temporoparietal junction, within a specialized subsystem of the default mode network, as sensitive to HV.

Morphological and transcriptomic analyses of stem cell-derived cortical neurons reveal mechanisms underlying synaptic dysfunction in schizophrenia

BACKGROUND

Postmortem studies in schizophrenia consistently show reduced dendritic spines in the cerebral cortex but the mechanistic underpinnings of these deficits remain unknown. Recent genome-wide association studies and exome sequencing investigations implicate synaptic genes and processes in the disease biology of schizophrenia.

METHODS

We generated human cortical pyramidal neurons by differentiating iPSCs of seven schizophrenia patients and seven healthy subjects, quantified dendritic spines and synapses in different cortical neuron subtypes, and carried out transcriptomic studies to identify differentially regulated genes and aberrant cellular processes in schizophrenia.

RESULTS

Cortical neurons expressing layer III marker CUX1, but not those expressing layer V marker CTIP2, showed significant reduction in dendritic spine density in schizophrenia, mirroring findings in postmortem studies. Transcriptomic experiments in iPSC-derived cortical neurons showed that differentially expressed genes in schizophrenia were enriched for genes implicated in schizophrenia in genome-wide association and exome sequencing studies. Moreover, most of the differentially expressed genes implicated in schizophrenia genetic studies had lower expression levels in schizophrenia cortical neurons. Network analysis of differentially expressed genes led to identification of NRXN3 as a hub gene, and follow-up experiments showed specific reduction of the NRXN3 204 isoform in schizophrenia neurons. Furthermore, overexpression of the NRXN3 204 isoform in schizophrenia neurons rescued the spine and synapse deficits in the cortical neurons while knockdown of NRXN3 204 in healthy neurons phenocopied spine and synapse deficits seen in schizophrenia cortical neurons. The antipsychotic clozapine increased expression of the NRXN3 204 isoform in schizophrenia cortical neurons and rescued the spine and synapse density deficits.

CONCLUSIONS

Taken together, our findings in iPSC-derived cortical neurons recapitulate cell type-specific findings in postmortem studies in schizophrenia and have led to the identification of a specific isoform of NRXN3 that modulates synaptic deficits in schizophrenia neurons.

Cortical and subcortical brain morphometry abnormalities in youth at clinical high-risk for psychosis and individuals with early illness schizophrenia

Neuroimaging studies have documented morphometric brain abnormalities in schizophrenia, but less is known about them in individuals at clinical high-risk for psychosis (CHR-P), including how they compare with those observed in early schizophrenia (ESZ). Accordingly, we implemented multivariate profile analysis of regional morphometric profiles in CHR-P (n = 89), ESZ (n = 93) and healthy controls (HC; n = 122). ESZ profiles differed from HC and CHR-P profiles, including 1) cortical thickness: significant level reduction and regional non-parallelism reflecting widespread thinning, except for entorhinal and pericalcarine cortex, 2) basal ganglia volume: significant level increase and regional non-parallelism reflecting larger caudate and pallidum, and 3) ventricular volume: significant level increase with parallel regional profiles. CHR-P and ESZ cerebellar profiles showed significant non-parallelism with HC profiles. Regional profiles did not significantly differ between groups for cortical surface area or subcortical volume. Compared to CHR-P followed for ≥18 months without psychosis conversion (n = 31), CHR-P converters (n = 17) showed significant non-parallel ventricular volume expansion reflecting specific enlargement of lateral and inferolateral regions. Antipsychotic dosage in ESZ was significantly correlated with frontal cortical thinning. Results suggest that morphometric abnormalities in ESZ are not present in CHR-P, except for ventricular enlargement, which was evident in CHR-P who developed psychosis.

Structural aging of human neurons is opposite of the changes in schizophrenia

Human mentality develops with age and is altered in psychiatric disorders, though their underlying mechanism is unknown. In this study, we analyzed nanometer-scale three-dimensional structures of brain tissues of the anterior cingulate cortex from eight schizophrenia and eight control cases. The distribution profiles of neurite curvature of the control cases showed a trend depending on their age, resulting in an age-correlated decrease in the standard deviation of neurite curvature (Pearson's r = -0.80, p = 0.018). In contrast to the control cases, the schizophrenia cases deviate upward from this correlation, exhibiting a 60% higher neurite curvature compared with the controls (p = 7.8 × 10-4). The neurite curvature also showed a correlation with a hallucination score (Pearson's r = 0.80, p = 1.8 × 10-4), indicating that neurite structure is relevant to brain function. This report is based on our 3D analysis of human brain tissues over a decade and is unprecedented in terms of the number of cases. We suggest that neurite curvature plays a pivotal role in brain aging and can be used as a hallmark to exploit a novel treatment of schizophrenia.

The Effect of Physical Exercise on People with Psychosis: A Qualitative Critical Review of Neuroimaging Findings

Recently, genuine motor abnormalities have been recognized as prodromal and predictive signs of psychosis onset and progression. Therefore, physical exercise could represent a potentially relevant clinical tool in promoting the reshaping of neural connections in motor circuitry. The aim of this review is to provide an overview of the literature on neuroimaging findings as a result of physical treatment in psychosis cohorts. Twenty-one studies, all research articles, were included and discussed in this narrative review. Here, we first outlined how the psychotic brain is susceptible to structural plastic changes after aerobic physical training in pathognomic brain areas (i.e., temporal, hippocampal and parahippocampal regions). Secondly, we focused on functional changes, both region-specific and in terms of connections, to gain insights into the involvement of distant but inter-related neural regions in the plastic process occurring after treatment. Third, we attempted to bridge neural plastic changes occurring after physical interventions with clinical and cognitive outcomes of psychotic patients in order to assess the relevance of such neural reshaping in the psychiatric rehabilitation field. In conclusion, we suggest that the current state of the art is presenting physical intervention as effective in promoting neural changes for patients with psychosis; it is not only useful at the onset of the pathology but also in improving the course of the illness and its functional outcome. However, more evidence is needed to improve our knowledge of the efficacy of physical exercise in plastically reorganizing the psychotic brain in the long term, especially within regions lacking specific investigations, such as motor circuitry.

Negative symptoms in First-Episode Schizophrenia related to morphometric alterations in orbitofrontal and superior temporal cortex: the OPTiMiSE study

BACKGROUND

Negative symptoms are one of the most incapacitating features of Schizophrenia but their pathophysiology remains unclear. They have been linked to alterations in grey matter in several brain regions, but findings have been inconsistent. This may reflect the investigation of relatively small patient samples, and the confounding effects of chronic illness and exposure to antipsychotic medication. We sought to address these issues by investigating concurrently grey matter volumes (GMV) and cortical thickness (CTh) in a large sample of antipsychotic-naïve or minimally treated patients with First-Episode Schizophrenia (FES).

METHODS

T1-weighted structural MRI brain scans were acquired from 180 antipsychotic-naïve or minimally treated patients recruited as part of the OPTiMiSE study. The sample was stratified into subgroups with (N = 88) or without (N = 92) Prominent Negative Symptoms (PMN), based on PANSS ratings at presentation. Regional GMV and CTh in the two groups were compared using Voxel-Based Morphometry (VBM) and FreeSurfer (FS). Between-group differences were corrected for multiple comparisons via Family-Wise Error (FWE) and Monte Carlo z-field simulation respectively at p < 0.05 (2-tailed).

RESULTS

The presence of PMN symptoms was associated with larger left inferior orbitofrontal volume (p = 0.03) and greater CTh in the left lateral orbitofrontal gyrus (p = 0.007), but reduced CTh in the left superior temporal gyrus (p = 0.009).

CONCLUSIONS

The findings highlight the role of orbitofrontal and temporal cortices in the pathogenesis of negative symptoms of Schizophrenia. As they were evident in generally untreated FEP patients, the results are unlikely to be related to effects of previous treatment or illness chronicity.

Unraveling the pathophysiology of schizophrenia: insights from structural magnetic resonance imaging studies

Background

Schizophrenia affects about 1% of the global population. In addition to the complex etiology, linking this illness to genetic, environmental, and neurobiological factors, the dynamic experiences associated with this disease, such as experiences of delusions, hallucinations, disorganized thinking, and abnormal behaviors, limit neurological consensuses regarding mechanisms underlying this disease.

Methods

In this study, we recruited 72 patients with schizophrenia and 74 healthy individuals matched by age and sex to investigate the structural brain changes that may serve as prognostic biomarkers, indicating evidence of neural dysfunction underlying schizophrenia and subsequent cognitive and behavioral deficits. We used voxel-based morphometry (VBM) to determine these changes in the three tissue structures: the gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). For both image processing and statistical analysis, we used statistical parametric mapping (SPM).

Results

Our results show that patients with schizophrenia exhibited a significant volume reduction in both GM and WM. In particular, GM volume reductions were more evident in the frontal, temporal, limbic, and parietal lobe, similarly the WM volume reductions were predominantly in the frontal, temporal, and limbic lobe. In addition, patients with schizophrenia demonstrated a significant increase in the CSF volume in the left third and lateral ventricle regions.

Conclusion

This VBM study supports existing research showing that schizophrenia is associated with alterations in brain structure, including gray and white matter, and cerebrospinal fluid volume. These findings provide insights into the neurobiology of schizophrenia and may inform the development of more effective diagnostic and therapeutic approaches.

Emerging epigenetic dynamics in gut-microglia brain axis: experimental and clinical implications for accelerated brain aging in schizophrenia

Brain aging, which involves a progressive loss of neuronal functions, has been reported to be premature in probands affected by schizophrenia (SCZ). Evidence shows that SCZ and accelerated aging are linked to changes in epigenetic clocks. Recent cross-sectional magnetic resonance imaging analyses have uncovered reduced brain reserves and connectivity in patients with SCZ compared to typically aging individuals. These data may indicate early abnormalities of neuronal function following cyto-architectural alterations in SCZ. The current mechanistic knowledge on brain aging, epigenetic changes, and their neuropsychiatric disease association remains incomplete. With this review, we explore and summarize evidence that the dynamics of gut-resident bacteria can modulate molecular brain function and contribute to age-related neurodegenerative disorders. It is known that environmental factors such as mode of birth, dietary habits, stress, pollution, and infections can modulate the microbiota system to regulate intrinsic neuronal activity and brain reserves through the vagus nerve and enteric nervous system. Microbiota-derived molecules can trigger continuous activation of the microglial sensome, groups of receptors and proteins that permit microglia to remodel the brain neurochemistry based on complex environmental activities. This remodeling causes aberrant brain plasticity as early as fetal developmental stages, and after the onset of first-episode psychosis. In the central nervous system, microglia, the resident immune surveillance cells, are involved in neurogenesis, phagocytosis of synapses and neurological dysfunction. Here, we review recent emerging experimental and clinical evidence regarding the gut-brain microglia axis involvement in SCZ pathology and etiology, the hypothesis of brain reserve and accelerated aging induced by dietary habits, stress, pollution, infections, and other factors. We also include in our review the possibilities and consequences of gut dysbiosis activities on microglial function and dysfunction, together with the effects of antipsychotics on the gut microbiome: therapeutic and adverse effects, role of fecal microbiota transplant and psychobiotics on microglial sensomes, brain reserves and SCZ-derived accelerated aging. We end the review with suggestions that may be applicable to the clinical setting. For example, we propose that psychobiotics might contribute to antipsychotic-induced therapeutic benefits or adverse effects, as well as reduce the aging process through the gut-brain microglia axis. Overall, we hope that this review will help increase the understanding of SCZ pathogenesis as related to chronobiology and the gut microbiome, as well as reveal new concepts that will serve as novel treatment targets for SCZ.

Modular architecture and resilience of structural covariance networks in first-episode antipsychotic-naive psychoses

Structural covariance network (SCN) studies on first-episode antipsychotic-naïve psychosis (FEAP) have examined less granular parcellations on one morphometric feature reporting lower network resilience among other findings. We examined SCNs of volume, cortical thickness, and surface area using the Human Connectome Project atlas-based parcellation (n = 358 regions) from 79 FEAP and 68 controls to comprehensively characterize the networks using a descriptive and perturbational network neuroscience approach. Using graph theoretical methods, we examined network integration, segregation, centrality, community structure, and hub distribution across the small-worldness threshold range and correlated them with psychopathology severity. We used simulated nodal "attacks" (removal of nodes and all their edges) to investigate network resilience, calculated DeltaCon similarity scores, and contrasted the removed nodes to characterize the impact of simulated attacks. Compared to controls, FEAP SCN showed higher betweenness centrality (BC) and lower degree in all three morphometric features and disintegrated with fewer attacks with no change in global efficiency. SCNs showed higher similarity score at the first point of disintegration with ≈ 54% top-ranked BC nodes attacked. FEAP communities consisted of fewer prefrontal, auditory and visual regions. Lower BC, and higher clustering and degree, were associated with greater positive and negative symptom severity. Negative symptoms required twice the changes in these metrics. Globally sparse but locally dense network with more nodes of higher centrality in FEAP could result in higher communication cost compared to controls. FEAP network disintegration with fewer attacks suggests lower resilience without impacting efficiency. Greater network disarray underlying negative symptom severity possibly explains the therapeutic challenge.

Automatic identification of schizophrenia based on EEG signals using dynamic functional connectivity analysis and 3D convolutional neural network

Schizophrenia (ScZ) is a devastating mental disorder of the human brain that causes a serious impact of emotional inclinations, quality of personal and social life and healthcare systems. In recent years, deep learning methods with connectivity analysis only very recently focused into fMRI data. To explore this kind of research into electroencephalogram (EEG) signal, this paper investigates the identification of ScZ EEG signals using dynamic functional connectivity analysis and deep learning methods. A time-frequency domain functional connectivity analysis through cross mutual information algorithm is proposed to extract the features in alpha band (8-12 Hz) of each subject. A 3D convolutional neural network technique was applied to classify the ScZ subjects and health control (HC) subjects. The LMSU public ScZ EEG dataset is employed to evaluate the proposed method, and a 97.74 ± 1.15% accuracy, 96.91 ± 2.76% sensitivity and 98.53 ± 1.97% specificity results were achieved in this study. In addition, we also found not only the default mode network region but also the connectivity between temporal lobe and posterior temporal lobe in both right and left side have significant difference between the ScZ and HC subjects.

Out of Line or Altered States? Neural Progenitors as a Target in a Polygenic Neurodevelopmental Disorder

The genesis of a mature complement of neurons is thought to require, at least in part, precursor cell lineages in which neural progenitors have distinct identities recognized by exclusive expression of one or a few molecular markers. Nevertheless, limited progenitor types distinguished by specific markers and lineal progression through such subclasses cannot easily yield the magnitude of neuronal diversity in most regions of the nervous system. The late Verne Caviness, to whom this edition of Developmental Neuroscience is dedicated, recognized this mismatch. In his pioneering work on the histogenesis of the cerebral cortex, he acknowledged the additional flexibility required to generate multiple classes of cortical projection and interneurons. This flexibility may be accomplished by establishing cell states in which levels rather than binary expression or repression of individual genes vary across each progenitor's shared transcriptome. Such states may reflect local, stochastic signaling via soluble factors or coincidence of cell surface ligand/receptor pairs in subsets of neighboring progenitors. This probabilistic, rather than determined, signaling could modify transcription levels via multiple pathways within an apparently uniform population of progenitors. Progenitor states, therefore, rather than lineal relationships between types may underlie the generation of neuronal diversity in most regions of the nervous system. Moreover, mechanisms that influence variation required for flexible progenitor states may be targets for pathological changes in a broad range of neurodevelopmental disorders, especially those with polygenic origins.

Brain Network Topology in Deficit and Non-Deficit Schizophrenia: Application of Graph Theory to Local and Global Indices

Patients with deficit schizophrenia (SZD) suffer from primary and enduring negative symptoms. Limited pieces of evidence and neuroimaging studies indicate they differ from patients with non-deficit schizophrenia (SZND) in neurobiological aspects, but the results are far from conclusive. We applied for the first time, graph theory analyses to discriminate local and global indices of brain network topology in SZD and SZND patients compared with healthy controls (HC). High-resolution T1-weighted images were acquired for 21 SZD patients, 21 SZND patients, and 21 HC to measure cortical thickness from 68 brain regions. Graph-based metrics (i.e., centrality, segregation, and integration) were computed and compared among groups, at both global and regional networks. When compared to HC, at the regional level, SZND were characterized by temporoparietal segregation and integration differences, while SZD showed widespread alterations in all network measures. SZD also showed less segregated network topology at the global level in comparison to HC. SZD and SZND differed in terms of centrality and integration measures in nodes belonging to the left temporoparietal cortex and to the limbic system. SZD is characterized by topological features in the network architecture of brain regions involved in negative symptomatology. Such results help to better define the neurobiology of SZD (SZD: Deficit Schizophrenia; SZND: Non-Deficit Schizophrenia; SZ: Schizophrenia; HC: healthy controls; CC: clustering coefficient; L: characteristic path length; E: efficiency; D: degree; CC_node: CC of a node; CC_glob: the global CC of the network; E_loc: efficiency of the information transfer flow either within segregated subgraphs or neighborhoods nodes; E_glob: efficiency of the information transfer flow among the global network; FDA: Functional Data Analysis; and D_min: estimated minimum densities).

Brain Structural Changes in Schizophrenia Patients Compared to the Control: An MRI-based Cavalieri's Method

INTRODUCTION

Schizophrenia is a severe psychotic brain disorder. One of the potential mechanisms underlying this disease may be volumetric changes in some brain regions. The present study aimed to employ magnetic resonance imaging (MRI) to estimate and quantitatively analyze the brain of patients with schizophrenia compared to the controls.

METHODS

This case-control study was conducted on MRI scans of 20 patients with schizophrenia and 20 healthy controls in Zahedan City, Southeastern Iran. MRIs with 4 mm slice thickness and 5 mm intervals in coronal and sagittal planes were captured. Then, quantitative parameters, including volume and volume density of various brain regions, were estimated in both groups using Cavalieri's point counting method. Data analyses were performed using the Mann-Whitney U test.

RESULTS

The findings of this investigation revealed that volumes of gray matter, hippocampus, and gray/white matter in patients with schizophrenia were significantly lower than the controls (P<0.05). The volumes of lateral ventricles in patients with schizophrenia (36.60±4.32 mm3) were significantly higher than the healthy individuals (30.10±7.98 mm3). However, there were no statistically significant differences between the two groups regarding the changes in the brain's total volume, cerebral hemispheres, white matter, brain stem, cerebellum, and corpus callosum (P>0.05).

CONCLUSION

Volumetric estimations on brain MRI-based stereological technique can be helpful for elucidation of structural changes, following up the treatment trends, and evaluating the therapeutic situations in schizophrenia patients. Volumetric alternations in specific brain areas might be linked to cognitive impairments and the severity of symptoms in patients with schizophrenia. Further research is needed in this regard.

HIGHLIGHTS

Volumetric changes occur in certain regions of the brain of schizophrenia patients.Structural changes in the brain of schizophrenia patients are associated with the severity of clinical manifestations.A brain MRI-based stereological technique can clarify neuropathology and assess therapeutic efficiency in patients with schizophrenia.

PLAIN LANGUAGE SUMMARY

Schizophrenia is a severe neuropsychiatric disorder with worldwide prevalence that disrupts a person's social life. It's characterized by progressive neuroanatomical alterations in both gray and white matter in different brain regions and associated with changes in the structural and functioning of some critical brain circuits. Several factors have been suggested to be involved in the development and progression of the disease including alternations and disconnection in myelin, genetic factors, neurodegenerative process, neuroinflammation, neurodevelopmental deficiencies, the number of dopaminergic neurons and volumetric changes in different areas of the brain. It has shown that quantitative volumetric brain measurements on magnetic resonance imaging (MRI) scans in patients with neurodegenerative disease owing to selective regional atrophy are beneficial for clinicians to ascertain disease progression and to evaluate volume alternations and response to treatment. Thus, we investigated structural changes of the brain in schizophrenia patients on MR images using accurate Cavalieri's estimation and compared to healthy controls. The findings demonstrated that some structural changes occurs in various brain areas which involved in many critical roles in normal brain's functionality and connectivity. On the other hand, these changes are associated with cognitive impairments and the severity of clinical symptoms in patients with schizophrenia. It's appears that elucidation of the different pathways of various structural abnormalities related to schizophrenia is required to recognize and determine the role of discrete pathophysiological phenomena in mental illness development and progress.

A preliminary choroid plexus volumetric study in individuals with psychosis

The choroid plexus (ChP) is part of the blood-cerebrospinal fluid barrier, regulating brain homeostasis and the brain's response to peripheral events. Its upregulation and enlargement are considered essential in psychosis. However, the timing of the ChP enlargement has not been established. This study introduces a novel magnetic resonance imaging-based segmentation method to examine ChP volumes in two cohorts of individuals with psychosis. The first sample consists of 41 individuals with early course psychosis (mean duration of illness = 1.78 years) and 30 healthy individuals. The second sample consists of 30 individuals with chronic psychosis (mean duration of illness = 7.96 years) and 34 healthy individuals. We utilized manual segmentation to measure ChP volumes. We applied ANCOVAs to compare normalized ChP volumes between groups and partial correlations to investigate the relationship between ChP, LV volumes, and clinical characteristics. Our segmentation demonstrated good reliability (.87). We further showed a significant ChP volume increase in early psychosis (left: p < .00010, right: p < .00010) and a significant positive correlation between higher ChP and higher LV volumes in chronic psychosis (left: r = .54, p = .0030, right: r = .68; p < .0010). Our study suggests that ChP enlargement may be a marker of acute response around disease onset. It might also play a modulatory role in the chronic enlargement of lateral ventricles, often reported in psychosis. Future longitudinal studies should investigate the dynamics of ChP enlargement as a promising marker for novel therapeutic strategies.

Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium

Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.

Prospective, randomized, multicenter clinical trial evaluating longitudinal changes in brain function and microstructure in first-episode schizophrenia patients treated with long-acting injectable paliperidone palmitate versus oral antipsychotics

Widespread anatomical alterations and abnormal functional connectivity have shown strong association with symptom severity in first-episode schizophrenia (FES) patients. Second-generation antipsychotic treatment might slow disease progression and possibly modify the cerebral plasticity in FES patients. However, whether a long-acting injectable antipsychotic (paliperidone palmitate [PP]), available in monthly and every-3-months formulations, is more effective than oral antipsychotics (OAP) in improving cerebral organization has been unclear. Therefore, in the current longitudinal study, we evaluated the differences in functional and microstructural changes of 68 FES patients in a randomized clinical trial of PP vs OAP. When compared to OAP treatment, PP treatment was more effective in decreasing abnormally high fronto-temporal and thalamo-temporal connectivity, as well as increasing fronto-sensorimotor and thalamo-insular connectivity. Consistent with previous studies, multiple white matter pathways showed larger changes in fractional anisotropy (FA) and mean diffusivity (MD) in response to PP compared with OAP treatment. These findings suggest that PP treatment might reduce regional abnormalities and improve cerebral connectivity networks compared with OAP treatment, and identified changes that may serve as reliable imaging biomarkers associated with medication treatment efficacy.

Changes in the volumes and asymmetry of subcortical structures in healthy individuals according to gender

In recent years, with the development of technology, three-dimensional software has entered our lives. Volumetric measurements made with Magnetic Resonance Imaging (MRI) are essential in the morphometry of the brain and subcortical structures. In this study, we aim to share the volume and asymmetry of the hippocampus, its sub-branches, and other subcortical structures and their interaction with age/sex using volBrain, a web-based automated software.1.5 T T1-weighted volumetric MRI, of 90 healthy individuals (51 females, 39 males) of both genders were included in our study. Pallidum, hippocampus, Cornu Ammonis1 (CA1), Cornu Ammonis2-3 (CA2-CA3), and Cornu Ammonis4-Dentate Gyrus (CA4-DG) measurements in females and males had a statistically higher mean in the right region (p < 0.05). In addition, females' hippocampus, CA1, CA2-CA3, and CA4-DG averages decreased more rapidly in the right region than in the left region. Subiculum measurement had a higher mean in the left region in both males and females (p < 0.05).The mean subiculum of males decreased more rapidly in the right region than in the left region. When the total values of the subcortical region in males and females were compared according to age categories, amygdala, pallidum, putamen, hippocampus, CA2-CA3, and subiculum values did not differ to gender in individuals aged 50 and over (p > 0.05). In individuals under 50 years old, the mean of females was statistically lower than the mean of males (p < 0.05).The Stratum radiatum (SR), Stratum lacunosum (SL), and Stratum molecuare (SM) asymmetry values of males in the examined subcortical regions had a higher mean than females (p = 0.039). In other regions, there was no statistically asymmetrical difference (p > 0.05). Studies evaluating the volumetric analysis and asymmetry of hippocampus subbranches and other subcortical structures in adults are very limited. As a result, the morphometry of the hippocampus subbranches and other subcortical structures was examined in detail. It was determined that the structures differed according to age, gender and body side.

Multi-ancestry phenome-wide association of complement component 4 variation with psychiatric and brain phenotypes in youth

BACKGROUND

Increased expression of the complement component 4A (C4A) gene is associated with a greater lifetime risk of schizophrenia. In the brain, C4A is involved in synaptic pruning; yet, it remains unclear the extent to which upregulation of C4A alters brain development or is associated with the risk for psychotic symptoms in childhood. Here, we perform a multi-ancestry phenome-wide association study in 7789 children aged 9-12 years to examine the relationship between genetically regulated expression (GREx) of C4A, childhood brain structure, cognition, and psychiatric symptoms.

RESULTS

While C4A GREx is not related to childhood psychotic experiences, cognition, or global measures of brain structure, it is associated with a localized reduction in regional surface area (SA) of the entorhinal cortex. Furthermore, we show that reduced entorhinal cortex SA at 9-10 years predicts a greater number and severity of psychosis-like events at 1-year and 2-year follow-up time points. We also demonstrate that the effects of C4A on the entorhinal cortex are independent of genome-wide polygenic risk for schizophrenia.

CONCLUSIONS

Our results suggest neurodevelopmental effects of C4A on childhood medial temporal lobe structure, which may serve as a biomarker for schizophrenia risk prior to symptom onset.

Investigation of the Relationship Between Cognitive Functions and Retinal Findings From Spectral Optical Coherence Tomography in Patients With Schizophrenia and Their Healthy Siblings

OBJECTIVE

Retinal structural changes which were investigated by optical coherence tomography (OCT) have been reported in schizophrenia. Since cognitive dysfunction is a core feature of schizophrenia, the correlations between retinal findings and cognitive functions of patients and their healthy siblings may provide insight into the pathophysiological processes of the disorder. We aimed to investigate the relationship between neuropsychiatric tests and retinal changes in schizophrenia patients and their healthy siblings.

METHODS

We measured OCT parameters and cognitive performance (via Trail Making Tests, verbal fluency tests, and The Digit Span Tests) of 72 participants (36 patients with schizophrenia and 36 healthy siblings) and disease severity (with Positive and Negative Syndrome Scale, Global Assessment of Functioning, and Clinical Global Impression scales) in patients with schizophrenia and evaluated the relationship between retinal findings and clinical parameters, especially neurocognitive tests.

RESULTS

We found decreased ganglion cell layer-inner plexiform layer thickness and macular volume in the patient group. There were strong correlations between neurocognitive tests and OCT findings in both groups. On the other hand, there was not any correlation between retinal findings and disease parameters.

CONCLUSION

The cognitive symptoms of schizophrenia may be more closely related to structural changes in the retina.

Reductions in synaptic marker SV2A in early-course Schizophrenia

Excess synaptic pruning during neurodevelopment has emerged as one of the leading hypotheses on the causal mechanism for schizophrenia. It proposes that excess synaptic elimination occurs during development before the formal onset of illness. Accordingly, synaptic deficits may be observable at all stages of illnesses, including in the early phases. The availability of [¹¹C]UCB-J, the first-in-human in vivo synaptic marker, represents an opportunity for testing this hypothesis with a relatively high level of precision. The first two published [¹¹C]UCB-J schizophrenia studies have documented significant, widespread reductions in binding in chronic patients. The present study tested the hypothesis that reductions are present in early-course patients. 18 subjects completed [¹¹C]UCB-J PET scans, (nine with schizophrenia, average duration of illness of 3.36 years, and nine demographically-matched healthy individuals). We compared binding levels, quantified as non-displaceable specific binding (BP_ND), in a set of a priori-specified brain regions of interest (ROIs). Eight ROIs (left and right hippocampus, right superior temporal and Heschl's gyrus, left and right putamen, and right caudal and rostral middle frontal gyrus) showed large reductions meeting Bonferroni corrected significant levels, p < 0.0036. Exploratory, atlas-wide analyses confirmed widespread reductions in schizophrenia. We also observed significant positive correlations between binding levels and cognitive performance and a negative correlation with the severity of delusions. These results largely replicate findings from chronic patients, indicating that extensive [¹¹C]UCB-J binding deficits are reliable and reproducible. Moreover, these results add to the growing evidence that excess synaptic pruning is a major disease mechanism for schizophrenia.

Morphological Abnormalities in Early-Onset Schizophrenia Revealed by Structural Magnetic Resonance Imaging

Schizophrenia is a pathological condition characterized by delusions, hallucinations, and a lack of motivation. In this study, we performed a morphological analysis of regional biomarkers in early-onset schizophrenia, including cortical thicknesses, surface areas, surface curvature, and volumes extracted from T1-weighted structural magnetic resonance imaging (MRI) and compared these findings with a large cohort of neurotypical controls. Results demonstrate statistically significant abnormal presentation of the curvature of select brain regions in early-onset schizophrenia with large effect sizes, inclusive of the pars orbitalis, pars triangularis, posterior cingulate cortex, frontal pole, orbital gyrus, lateral orbitofrontal gyrus, inferior occipital gyrus, as well as in medial occipito-temporal, lingual, and insular sulci. We also observed reduced regional volumes, surface areas, and variability of cortical thicknesses in early-onset schizophrenia relative to neurotypical controls in the lingual, transverse temporal, cuneus, and parahippocampal cortices that did not reach our stringent standard for statistical significance and should be confirmed in future studies with higher statistical power. These results imply that abnormal neurodevelopment associated with early-onset schizophrenia can be characterized with structural MRI and may reflect abnormal and possibly accelerated pruning of the cortex in schizophrenia.

Functional connectivity and gray matter deficits within the auditory attention circuit in first-episode psychosis

Background

Selective attention deficits in first episode of psychosis (FEP) can be indexed by impaired attentional modulation of auditory M100. It is unknown if the pathophysiology underlying this deficit is restricted to auditory cortex or involves a distributed attention network. We examined the auditory attention network in FEP.

Methods

MEG was recorded from 27 FEP and 31 matched healthy controls (HC) while alternately ignoring or attending tones. A whole-brain analysis of MEG source activity during auditory M100 identified non-auditory areas with increased activity. Time-frequency activity and phase-amplitude coupling were examined in auditory cortex to identify the attentional executive carrier frequency. Attention networks were defined by phase-locking at the carrier frequency. Spectral and gray matter deficits in the identified circuits were examined in FEP.

Results

Attention-related activity was identified in prefrontal and parietal regions, markedly in precuneus. Theta power and phase coupling to gamma amplitude increased with attention in left primary auditory cortex. Two unilateral attention networks were identified with precuneus seeds in HC. Network synchrony was impaired in FEP. Gray matter thickness was reduced within the left hemisphere network in FEP but did not correlate with synchrony.

Conclusion

Several extra-auditory attention areas with attention-related activity were identified. Theta was the carrier frequency for attentional modulation in auditory cortex. Left and right hemisphere attention networks were identified, with bilateral functional deficits and left hemisphere structural deficits, though FEP showed intact auditory cortex theta phase-gamma amplitude coupling. These novel findings indicate attention-related circuitopathy early in psychosis potentially amenable to future non-invasive interventions.