Different structural connectivity patterns in the subregions of the thalamus, hippocampus, and cingulate cortex between schizophrenia and psychotic bipolar disorder.

OBJECTIVE: Schizophrenia (SCZ) and psychotic bipolar disorder (PBD) are two major psychotic disorders with similar symptoms and tight associations on the psychopathological level, posing a clinical challenge for their differentiation. This study aimed to investigate and compare the structural connectivity patterns of the limbic system between SCZ and PBD, and to identify specific regional disruptions associated with psychiatric symptoms. METHODS: Using sMRI data from 146 SCZ, 160 PBD, and 145 healthy control (HC) participants, we employed a data-driven approach to segment the hippocampus, thalamus, hypothalamus, amygdala, and cingulate cortex into subregions. We then investigated the structural connectivity patterns between these subregions at the global and nodal levels. Additionally, we assessed psychotic symptoms by utilizing the subscales of the Brief Psychiatric Rating Scale (BPRS) to examine correlations between symptom severity and network metrics between groups. RESULTS: Patients with SCZ and PBD had decreased global efficiency (Eglob) (SCZ: adjusted P<0.001; PBD: adjusted P = 0.003), local efficiency (Eloc) (SCZ and PBD: adjusted P<0.001), and clustering coefficient (Cp) (SCZ and PBD: adjusted P<0.001), and increased path length (Lp) (SCZ: adjusted P<0.001; PBD: adjusted P = 0.004) compared to HC. Patients with SCZ showed more pronounced decreases in Eglob (adjusted P<0.001), Eloc (adjusted P<0.001), and Cp (adjusted P = 0.029), and increased Lp (adjusted P = 0.024) compared to patients with PBD. The most notable structural disruptions were observed in the hippocampus and thalamus, which correlated with different psychotic symptoms, respectively. CONCLUSION: This study provides evidence of distinct structural connectivity disruptions in the limbic system of patients with SCZ and PBD. These findings might contribute to our understanding of the neuropathological basis for distinguishing SCZ and PBD.

Striatum and globus pallidus structural abnormalities in schizophrenia: A retrospective study of the different stages of the disease.

BACKGROUND: The basal ganglia are important structures for the release of dopamine in the limbic circuits of the midbrain, and the striatum and globus pallidus are the major nuclei of the basal ganglia, and the dysfunction of these regions has been the basis of many models that have attempted to explain the underlying mechanisms of schizophrenia symptoms. The purpose of this study was to investigate the changes in the volume of the striatum subregion and globus pallidus in three different stages of schizophrenia, and to analyze whether these volume changes were related to antipsychotic drugs and schizophrenia symptoms. METHODS: In this study, we investigated the volume of the striatum and globus pallidus in patients with schizophrenia at three different stages. The study included 57 patients with first-episode schizophrenia (FSZ), 51 patients with early-stage schizophrenia (ESZ), 86 patients with chronic schizophrenia (CSZ), and 191 healthy controls (HC), all of whom underwent structured magnetic resonance imaging (MRI) scans. Covariance analysis was performed using SPSS 26.0 was used for covariance analysis to determine whether there were significant differences in striatal subregion and globus pallidus volume between groups, and stratified analysis was used to further eliminate the effect of age on brain volume. Finally, the correlation analysis between the region of interest and the cumulative dose of antipsychotic drugs and psychotic symptoms was performed. RESULTS: The comparison between the different stages of the illness showed significant volume differences in the left caudate nucleus (lCAU) (F = 2.665, adjusted p = 0.048), left putamen (lPUT) (F = 12.749, adjusted p < 0.001), left pallidum (lPAL) (F = 41.111, adjusted p < 0.001), and right pallidum (rPAL) (F = 14.479, adjusted p < 0.001). Post-hoc analysis with corrections showed that the volume differences in the lCAU subregion disappeared. Further stratified analysis controlling for age showed that compared with the HC, the lPAL (t = 4.347, p < 0.001) was initially significantly enlarged in the FSZ group, the lPUT (t = 4.493, p < 0.001), rPUT (t = 2.190, p = 0.031), lPAL (t = 7.894, p < 0.001), and rPAL (t = 4.983, p < 0.001) volumes were all significantly increased in the ESZ group, and the lPUT (t = 3.314, p = 0.002), lPAL (t = 6.334, p < 0.001), and rPAL (t = 3.604, p < 0.001) subregion volumes were also significantly increased in the CSZ group. Correlation analysis showed that lPUT and bilateral globus pallidus were associated with cumulative dose of antipsychotics, but were not associated with clinical symptoms in each subregion. CONCLUSION: The findings suggest that different subregions of the striatum and globus pallidus show significant volume differences at different stages of schizophrenia compared to HC. These volume differences may be strong radiographic evidence for schizophrenia. In addition, the lPAL was the only significantly different brain region observed in the FSZ group, suggesting that it may be a sensitive indicator of early brain structural changes in schizophrenia. Finally, our findings support the hypothesis that antipsychotic drugs have an effect on the volume of brain structures.

Diagnostic significance and potential function of miR-320d in schizophrenia.

OBJECTIVES: Schizophrenia is a chronic brain disorder and needs objective diagnostic biomarkers. MicroRNAs are highly expressed in the nervous system. The study investigated the expression and clinical values of serum miR-320d in schizophrenia patients. In addition, the underlying mechanism was preliminarily examined via bioinformatic analysis. MATERIALS AND METHODS: Serum samples were collected from 57 patients with first-episode schizophrenia and 62 healthy controls. The cognitive function of patients was assessed via Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery (MCCB) consisting of seven domains. Serum miR-320d levels were tested via qRT-PCR. The miRNA target predictions were obtained from Target Scan, and annotated through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. RESULTS: Based on the GSE167630 dataset, downregulated serum miR-320d in schizophrenia was identified, which was determined in the serum of schizophrenia patients. Serum miR-320d presented a conspicuous relationship with MCCB score in both the control group and the schizophrenia group. After adjusting for age, sex, BMI, and education, serum miR-320d was still independently related to the occurrence of schizophrenia. It can identify schizophrenia cases from healthy ones with an AUC of 0.931. The Go enrichment analysis indicated that the target genes were mainly enriched in homophilic cell adhesion and cell-cell adhesion via plasma-membrane adhesion molecules, and GTPase activity and guanosine diphosphate (GDP) binding. Rap1 signaling pathway was enriched via KEGG analysis. CONCLUSION: Serum miR-320d can be taken as a candidate marker for the diagnosis of schizophrenia. Its regulatory role in neuronal cell adhesion and Rap1 signaling pathway might be the potential underlying mechanism of miR-320d in schizophrenia.

Volumes of hippocampal subfields suggest a continuum between schizophrenia, major depressive disorder and bipolar disorder.

Objective: There is considerable debate as to whether the continuum of major psychiatric disorders exists and to what extent the boundaries extend. Converging evidence suggests that alterations in hippocampal volume are a common sign in psychiatric disorders; however, there is still no consensus on the nature and extent of hippocampal atrophy in schizophrenia (SZ), major depressive disorder (MDD) and bipolar disorder (BD). The aim of this study was to verify the continuum of SZ - BD - MDD at the level of hippocampal subfield volume and to compare the volume differences in hippocampal subfields in the continuum. Methods: A total of 412 participants (204 SZ, 98 MDD, and 110 BD) underwent 3 T MRI scans, structured clinical interviews, and clinical scales. We segmented the hippocampal subfields with FreeSurfer 7.1.1 and compared subfields volumes across the three diagnostic groups by controlling for age, gender, education, and intracranial volumes. Results: The results showed a gradual increase in hippocampal subfield volumes from SZ to MDD to BD. Significant volume differences in the total hippocampus and 13 of 26 hippocampal subfields, including CA1, CA3, CA4, GC-ML-DG, molecular layer and the whole hippocampus, bilaterally, and parasubiculum in the right hemisphere, were observed among diagnostic groups. Medication treatment had the most effect on subfields of MDD compared to SZ and BD. Subfield volumes were negatively correlated with illness duration of MDD. Positive correlations were found between subfield volumes and drug dose in SZ and MDD. There was no significant difference in laterality between diagnostic groups. Conclusion: The pattern of hippocampal volume reduction in SZ, MDD and BD suggests that there may be a continuum of the three disorders at the hippocampal level. The hippocampus represents a phenotype that is distinct from traditional diagnostic strategies. Combined with illness duration and drug intervention, it may better reflect shared pathophysiology and mechanisms across psychiatric disorders.

Electroconvulsive therapy efficacy in adolescents with mental illness: A retrospective comparison.

Background: There is limited evidence on the efficacy of electroconvulsive therapy (ECT) in adolescents with mental illness. The present study reported outcomes of adolescents with mental illness treated with ECT aimed at providing evidence for large-scale feasibility. Objectives: The primary objective of this trial was to examine the differences in demographic and clinical data between responders and non-responders. The secondary objective was to determine whether ECT produced differential readmission rates, the burden of oral medication, and social function in responders and non-responders in the long term. Methods: Patients aged 14-18 years diagnosed with schizophrenia (SCZ), major depressive disorder (MDD), or bipolar disorder (BD) who received ECT between 2015 and 2020 were included in the study. Demographic and clinical data were compared, and both short-term and long-term outcomes were assessed: response on the Clinical Global Impressions-Improvement scale and readmission at follow-up. The independent-sample t-test was used to compare the continuous variables and the X 2 test was used to compare the dichotomous variables with statistical significance at P ≤ 0.05. Results: Four hundred ten adolescents (aged 14-18 years, 53.90% female) received ECT for SCZ, MDD, and BD. The response rate for SCZ, MDD, and BD were 65.61, 78.57, and 69.95%, respectively. Both SCZ (P = 0.008) and BD (P = 0.008) groups had a significant elder age in responders than in non-responders. Besides that MDD responders had a significantly larger number of ECT sessions than non-responders (P = 0.046), the study failed to find a significant difference in other ECT parameters. A significantly higher proportion of readmission was found in BD non-responders than in responders (P = 0.029), there was no difference in the rate of readmission in other diagnostic groups. Conclusions: These data suggested that ECT is an effective treatment for adolescents with severe mental illness, and the rate of readmission was low in the long term. The present study supports that large-scale systematic studies are warranted for further investigation of the response rate of ECT for treating adolescents with mental illness.

Aberrant Functional Connectivity of the Orbitofrontal Cortex Is Associated With Excited Symptoms in First-Episode Drug-Naïve Patients With Schizophrenia.

Background: Schizophrenia (SZ) is associated with the highest disability rate among serious mental disorders. Excited symptoms are the core symptoms of SZ, which appear in the early stage, followed by other stages of the disease subsequently. These symptoms are destructive and more prone to violent attacks, posing a serious economic burden to the society. Abnormal spontaneous activity in the orbitofrontal cortex had been reported to be associated with excited symptoms in patients with SZ. However, whether the abnormality appears in first-episode drug-naïve patients with SZ has still remained elusive. Methods: A total of 56 first-episode drug-naïve patients with SZ and 27 healthy controls underwent resting-state functional magnetic resonance imaging (rs-fMRI) and positive and negative syndrome scale (PANSS). First, differences in fractional amplitude of low-frequency fluctuations (fALFF) between first-episode drug-naïve patients with SZ and healthy controls were examined to identify cerebral regions exhibiting abnormal local spontaneous activity. Based on the fALFF results, the resting-state functional connectivity analysis was performed to determine changes in cerebral regions exhibiting abnormal local spontaneous activity. Finally, the correlation between abnormal functional connectivity and exciting symptoms was analyzed. Results: Compared with the healthy controls, first-episode drug-naïve patients with SZ showed a significant decrease in intrinsic activity in the bilateral precentral gyrus, bilateral postcentral gyrus, and the left orbitofrontal cortex. In addition, first-episode drug-naïve patients with SZ had significantly reduced functional connectivity values between the left orbitofrontal cortex and several cerebral regions, which were mainly distributed in the bilateral postcentral gyrus, the right middle frontal gyrus, bilateral paracentral lobules, the left precentral gyrus, and the right median cingulate. Further analyses showed that the functional connectivity between the left orbitofrontal cortex and the left postcentral gyrus, as well as bilateral paracentral lobules, was negatively correlated with excited symptoms in first-episode drug-naïve patients with SZ. Conclusion: Our results indicated the important role of the left orbitofrontal cortex in first-episode drug-naïve patients with SZ and suggested that the abnormal spontaneous activity of the orbitofrontal cortex may be valuable to predict the occurrence of excited symptoms. These results may provide a new direction to explore the excited symptoms of SZ.

Facial emotion perception abilities are related to grey matter volume in the culmen of cerebellum anterior lobe in drug-naïve patients with first-episode schizophrenia.

Impaired capability for understanding and interpreting the expressions on other people's faces manifests itself as a core feature of schizophrenia, contributing to social dysfunction. With the purpose of better understanding of the neurobiological basis of facial emotion perception deficits in schizophrenia, we investigated facial emotion perception abilities and regional structural brain abnormalities in drug-naïve patients with first-episode schizophrenia, and then examined the correlation between them. Fifty-two drug-naive patients with first-episode schizophrenia and 29 group-matched healthy controls were examined for facial emotion perception abilities assessed with the Facial Emotion Categorization and performed magnetic resonance imaging. The Facial Emotion Categorization data were inserted into a logistic function model so as to calculate shift point and slope as outcome measurements. Voxel-based morphometry was applied to investigate regional grey matter volume (GMV) alterations. The relationship between facial emotion perception and GMV was explored in patients using voxel-wise correlation analysis within brain regions that showed a significant GMV alterations in patients compared with controls. The schizophrenic patients performed differently on Facial Emotion Categorization tasks from the controls and presented a higher shift point and a steeper slope. Relative to the controls, patients showed GMV reductions in the superior temporal gyrus, middle occipital gyrus, parahippocampa gyrus, posterior cingulate, the culmen of cerebellum anterior lobe, cerebellar tonsil, and the declive of cerebellum posterior lobe. Importantly, abnormal performance on Facial Emotion Categorization was found correlated with GMV alterations in the culmen of cerebellum anterior lobe in schizophrenia. This study suggests that reduced GMV in the culmen of cerebellum anterior lobe occurs in first-episode schizophrenia, constituting a potential neuropathological basis for the impaired facial emotion perception in schizophrenia.

Andrographolide improves PCP-induced schizophrenia-like behaviors through blocking interaction between NRF2 and KEAP1.

Schizophrenia is one of the foremost psychological illness around the world, and recent evidence shows that inflammation and oxidative stress may play a critical role in the etiology of schizophrenia. Andrographolide is a diterpenoid lactone from Andrographis paniculate, which has shown anti-inflammation and anti-oxidative effects. In this study, we explored whether andrographolide can improve schizophrenia-like behaviors through its inhibition of inflammation and oxidative stress in Phencyclidine (PCP)-induced mouse model of schizophrenia. We found that abnormal behavioral including locomotor activity, forced swimming and novel object recognition were ameliorated following andrographolide administration (5 mg/kg and 10 mg/kg). Andrographolide inhibited PCP-induced production of inflammatory cytokines, decreased p-p65, p-IκBα, p-p38 and p-ERK1/2 in the prefrontal cortex. Andrographolide significantly declined the level of MDA and GSH, as well as elevated the activity of SOD, CAT and GCH-px. In addition, andrographolide increased expression of NRF-2, HO-1 and NQO-1, promoted nuclear translocation of NRF-2 through blocking the interaction between NRF-2 and KEAP1, which may be associated with directly binding to NRF-2. Furthermore, antioxidative effects and anti-schizophrenia-like behaviors of andrographolide were compromised by the application of NRF-2 inhibitor ML385. In conclusion, these results suggested that andrographolide improved oxidative stress and schizophrenia-like behaviors induced by PCP through increasing NRF-2 pathway.

Higher serum VGF protein levels discriminate bipolar depression from major depressive disorder.

Misdiagnosis between major depressive disorder (MDD) and bipolar depression (BD) is quite common. Our previous study found significantly lower serum VGF (non-acronymic) in MDD patients. However, it is unclear whether same changes occur in BD patients. Therefore, we aimed to investigate the relationship between serum VGF levels in BD and MDD patients. General information, scores of 17-item Hamilton Depression Rating Scale (HDRS), and fasting blood samples of all participants including 30 MDD patients, 20 BD patients, and 30 healthy controls (HC) were collected. Serum VGF levels were measured by Enzyme-linked immunosorbent assay kits. Pearson correlation analysis was used to analyze correlations between serum VGF levels and clinical information. Receiver operating characteristic (ROC) curve and likelihood ratios (LRs) were used to analyze the differential potential of serum VGF. Serum VGF levels were significantly lower in MDD patients but higher in BD patients compared with HC (both PTukey < 0.01). No correlation was found between serum VGF levels and any data of subjects. The optimal cutoff for serum VGF in discriminating BD patients from MDD patients was ≥1093.85 pg/ml (AUC = 0.990, sensitivity of 95%, specificity of 100% and accuracy of 95%). LRs further confirmed the differential efficiency of serum VGF in distinguishing BD and MDD patients with +LR of infinity and -LR of 0. The results suggest that serum VGF level changed significantly in MDD and BD patients and serum VGF may be an indicator for differentiating BD patients from MDD patients.

Abnormalities of regional homogeneity and its correlation with clinical symptoms in Naïve patients with first-episode schizophrenia.

Several resting-state neuroimaging studies have indicated abnormal regional homogeneity (ReHo) in chronic schizophrenia; however, little work has been conducted to investigate naïve patients with first-episode schizophrenia (FES). Even less investigated is the association between ReHo measures and clinical symptom severity in naïve patients with FES. The current study evaluated ReHo alterations in whole brain, and assessed the correlations between ReHo measures and clinical variables in naïve patients with FES. Forty-four naïve patients with FES and 26 healthy controls (HC) underwent resting-state functional magnetic resonance imaging (rs-fMRI). Group-level analysis was utilized to analyze the ReHo differences between FES and HC in a voxel-by-voxel manner. Severity of symptoms was evaluated using a five-factor model of the Positive and Negative Syndrome Scale (PANSS). The correlation between the severity of symptoms and ReHo map was examined in patients using voxel-wise correlation analyses within brain areas that showed a significant ReHo alteration in patients compared with controls. Compared with the healthy control group, the FES group showed a significant decrease in ReHo values in the left medial frontal gyrus (MFG), right precentral gyrus, left superior temporal gyrus (STG), left left middle temporal gyrus (MTG), left thalamus, and significant increase in ReHo values in the left MFG, left inferior parietal lobule (IPL), left precuneus, and right lentiform nucleus (LN). In addition, the correlation analysis showed the PANSS total score negatively correlated with ReHo in the right precentral gyrus and positively correlated with ReHo in the left thalamus, the positive factor positively correlated with ReHo in the right thalamus, the disorganized/concrete factor positively correlated with ReHo in left posterior cingulate gyrus (PCG), the excited factor positively correlated with ReHo in the left precuneus, and the depressed factor negatively correlated with ReHo in the right postcentral gyrus and positively correlated with ReHo in the right thalamus. Our results indicate that widespread ReHo abnormalities occurred in an early stage of schizophrenic onset, suggesting a potential neural basis for the pathogenesis and symptomatology of schizophrenia.

Neural correlates of future-oriented coping: Preliminary evidence from a resting-state functional connectivity study.

Future-oriented coping is a strategy for coping with events that may happen in the future, including efforts to ensure positive outcome and protection from potential threats. Appropriate future-oriented coping is essential for well-being and influences mental health and life satisfaction. However, little is known about the neural mechanism of future-oriented coping. We examined the neural basis of this coping strategy using resting-state functional connectivity analysis. Thirty healthy volunteers underwent resting-state functional magnetic resonance imaging scanning and completed the Future-Oriented Coping Inventory. Seed-based functional connectivity analysis was used to investigate potentially correlated regions, with 11 nodes in the default mode network defined as regions of interest. Multiple regression analysis was performed to measure the correlation between coping behavior and functional connectivity. We found that proactive coping was significantly correlated with the functional connectivity strength between the parahippocampal cortex (PHC) and the claustrum/insula. These novel findings suggest that cooperation between the PHC and the claustrum/insula plays an important role in proactive coping. Moreover, cognitive components, such as future thinking (the PHC) and sensory judgment (the claustrum/insula) could be important process factors in proactive coping.

Classification of Alzheimer's Disease Based on Eight-Layer Convolutional Neural Network with Leaky Rectified Linear Unit and Max Pooling.

Alzheimer's disease (AD) is a progressive brain disease. The goal of this study is to provide a new computer-vision based technique to detect it in an efficient way. The brain-imaging data of 98 AD patients and 98 healthy controls was collected using data augmentation method. Then, convolutional neural network (CNN) was used, CNN is the most successful tool in deep learning. An 8-layer CNN was created with optimal structure obtained by experiences. Three activation functions (AFs): sigmoid, rectified linear unit (ReLU), and leaky ReLU. The three pooling-functions were also tested: average pooling, max pooling, and stochastic pooling. The numerical experiments demonstrated that leaky ReLU and max pooling gave the greatest result in terms of performance. It achieved a sensitivity of 97.96%, a specificity of 97.35%, and an accuracy of 97.65%, respectively. In addition, the proposed approach was compared with eight state-of-the-art approaches. The method increased the classification accuracy by approximately 5% compared to state-of-the-art methods.

An Association Study on the Cognitive Function and the Cerebral Grey Matter Volume of Patients with First-Episode Schizophrenia.

BACKGROUND: The impairment of cognitive function is one of the core symptoms in schizophrenia, and the degree of recovery is closely related to whether patients are able to rejoin society successfully. OBJECTIVE: This study was to clarify the correlation between cognitive function and cerebral grey matter volume in schizophrenia. METHODS: The neuro-cognitive functions of thirty-seven patients with first-episode schizophrenia (the patient group) and thirty healthy controls (the control group) was evaluated with the Clock Drawing Test, Trail Marking Test, Digit Span Test, Auditory Verbal Learning Test, Wisconsin Card Sorting Test, Verbal Fluency Test, Semantic Similarity Test and Stroop Color-Word Test. The facial emotion cognitive task was employed to assess the facial emotion cognitive functions of thirty-two patients with first-episode schizophrenia (the patient group) and 29 healthy controls (the control group). The psychotic symptoms of patients with first-episode schizophrenia were evaluated using the Positive and Negative Syndrome Scale (PANSS). The brain imaging data of the patient group and control group were collected using the magnetic resonance imagine (MRI). RESULTS: The difference between the patient group and the control group in the results of Clock Drawing Test, Trail Marking Test, Digit Span Test, Auditory Verbal Learning Test, Wisconsin Card Sorting Test, Verbal Fluency Test, Semantic Similarity Test and Stroop Color-Word Test's reaction time were significant. These two groups' Slopes in the facial emotion cognitive task were also significantly different from each other. According to the comparison of cerebral grey matter volume between the patient group and the control group, it was found that the grey matter volume of the patient group increased in the left superior frontal gyrus, and decreased in the left occipital gyrus, lingual gyrus and upper cerebellum. Based on the analyses of neuro-cognitive data and brain imaging data of the patient group, the scores of the number of correct responses in Stroop Color-Word Test's Card C were negatively correlated with grey matter volumes of the left upper frontal gyrus, right upper frontal gyrus and middle frontal gyrus. The analyses on the facial emotion cognitive task and brain imaging data of the patient group showed that the slope data were positively correlated with grey matter volumes of the right superior temporal gyrus, middle temporal gyrus, left middle temporal gyrus, inferior temporal gyrus and fusiform gyrus. CONCLUSION: There are general impairments in the neuro-cognitive functions and facial emotion cognitive functions of patients with first-episode schizophrenia, and the results suggest that brain areas with abnormal grey matter volumes are likely to be the brain structure and functional basis of the cognitive impairments.

Multivariate Approach for Alzheimer's Disease Detection Using Stationary Wavelet Entropy and Predator-Prey Particle Swarm Optimization.

BACKGROUND: The number of patients with Alzheimer's disease is increasing rapidly every year. Scholars often use computer vision and machine learning methods to develop an automatic diagnosis system. OBJECTIVE: In this study, we developed a novel machine learning system that can make diagnoses automatically from brain magnetic resonance images. METHODS: First, the brain imaging was processed, including skull stripping and spatial normalization. Second, one axial slice was selected from the volumetric image, and stationary wavelet entropy (SWE) was done to extract the texture features. Third, a single-hidden-layer neural network was used as the classifier. Finally, a predator-prey particle swarm optimization was proposed to train the weights and biases of the classifier. RESULTS: Our method used 4-level decomposition and yielded 13 SWE features. The classification yielded an overall accuracy of 92.73±1.03%, a sensitivity of 92.69±1.29%, and a specificity of 92.78±1.51%. The area under the curve is 0.95±0.02. Additionally, this method only cost 0.88 s to identify a subject in online stage, after its volumetric image is preprocessed. CONCLUSION: In terms of classification performance, our method performs better than 10 state-of-the-art approaches and the performance of human observers. Therefore, this proposed method is effective in the detection of Alzheimer's disease.

Alcoholism Detection by Data Augmentation and Convolutional Neural Network with Stochastic Pooling.

Alcohol use disorder (AUD) is an important brain disease. It alters the brain structure. Recently, scholars tend to use computer vision based techniques to detect AUD. We collected 235 subjects, 114 alcoholic and 121 non-alcoholic. Among the 235 image, 100 images were used as training set, and data augmentation method was used. The rest 135 images were used as test set. Further, we chose the latest powerful technique-convolutional neural network (CNN) based on convolutional layer, rectified linear unit layer, pooling layer, fully connected layer, and softmax layer. We also compared three different pooling techniques: max pooling, average pooling, and stochastic pooling. The results showed that our method achieved a sensitivity of 96.88%, a specificity of 97.18%, and an accuracy of 97.04%. Our method was better than three state-of-the-art approaches. Besides, stochastic pooling performed better than other max pooling and average pooling. We validated CNN with five convolution layers and two fully connected layers performed the best. The GPU yielded a 149× acceleration in training and a 166× acceleration in test, compared to CPU.

Combined serum levels of multiple proteins in tPA-BDNF pathway may aid the diagnosis of five mental disorders.

Mental disorders are severe, disabling conditions with unknown etiology and are commonly misdiagnosed when clinical symptomology criteria are solely used. Our previous work indicated that combination of serum levels of multiple proteins in tissue plasminogen activator (tPA)-brain-derived neurotrophic factor (BDNF) pathway improved accuracy of diagnosis of major depressive disorder (MDD). Here, we measured serum levels of tPA, plasminogen activator inhibitor-1 (PAI-1), BDNF, precursor-BDNF (proBDNF), tropomyosin-related kinase B (TrkB) and neurotrophin receptor p75 (p75NTR) in patients with paranoid schizophrenia (SZ, n = 34), MDD (n = 30), bipolar mania (BM, n = 30), bipolar depression (BD, n = 22), panic disorder (PD, n = 30), and healthy controls (HCs, n = 30) by Enzyme-linked immunosorbent assay kits. We used receiver operating characteristic (ROC) curve to analyze diagnostic potential of these proteins. We found, compared with HCs, that serum tPA and proBDNF were lower in SZ, BM and BD; TrkB was lower in SZ and BD; and p75NTR was declined in SZ and BM. ROC analysis showed that combined serum level of tPA, PAI-1, BDNF, proBDNF, TrkB and p75NTR was better than any single protein in accuracy of diagnosis and differentiation, suggesting that the combination of multiple serum proteins levels in tPA-BDNF pathway may have a potential for a diagnostic panel in mental disorders.

Reduced white matter integrity and facial emotion perception in never-medicated patients with first-episode schizophrenia: A diffusion tensor imaging study.

BACKGROUND: Facial emotion perception is impaired in schizophrenia. Although the pathology of schizophrenia is thought to involve abnormality in white matter (WM), few studies have examined the correlation between facial emotion perception and WM abnormalities in never-medicated patients with first-episode schizophrenia. The present study tested associations between facial emotion perception and WM integrity in order to investigate the neural basis of impaired facial emotion perception in schizophrenia. METHODS: Sixty-three schizophrenic patients and thirty control subjects underwent facial emotion categorization (FEC). The FEC data was inserted into a logistic function model with subsequent analysis by independent-samples T test and the shift point and slope as outcome measurements. Severity of symptoms was measured using a five-factor model of the Positive and Negative Syndrome Scale (PANSS). Voxelwise group comparison of WM fractional anisotropy (FA) was operated using tract-based spatial statistics (TBSS). The correlation between impaired facial emotion perception and FA reduction was examined in patients using simple regression analysis within brain areas that showed a significant FA reduction in patients compared with controls. The same correlation analysis was also performed for control subjects in the whole brain. RESULTS: The patients with schizophrenia reported a higher shift point and a steeper slope than control subjects in FEC. The patients showed a significant FA reduction in left deep WM in the parietal, temporal and occipital lobes, a small portion of the corpus callosum (CC), and the corona radiata. In voxelwise correlation analysis, we found that facial emotion perception significantly correlated with reduced FA in various WM regions, including left forceps major (FM), inferior longitudinal fasciculus (ILF), inferior fronto-occipital fasciculus (IFOF), Left splenium of CC, and left ILF. The correlation analyses in healthy controls revealed no significant correlation of FA with FEC task. CONCLUSIONS: These results showed disrupted WM integrity in these regions constitutes a potential neural basis for the facial emotion perception impairments in schizophrenia.

Structural and Functional Connectivity of Default Mode Network underlying the Cognitive Impairment in Late-onset Depression.

To identify the association between the functional and structural changes of default mode network (DMN) underlying the cognitive impairment in Late-onset depression (LOD), 32 LOD patients and 39 normal controls were recruited and underwent resting-state fMRI, DTI scans, and cognitive assessments. Seed-based correlation analysis was conducted to explore the functional connectivity (FC) of the DMN. Deterministic tractography between FC-impaired regions was performed to examine the structural connectivity (SC). Partial correlation analyses were employed to evaluate the cognitive association of those altered FC and SC. Compared with controls, LOD patients showed decreased FC between DMN and the cingulo-opercular network (CON), as well as the thalamus. Decreased FA and increased RD of these fiber tracts connecting DMN with CON were found in LOD patient. The DMN-CON FC and the FA, RD of the fiber tracts were both significantly correlated with the cognitive performance. Therefore, the cognitive impairment in LOD might be associated with the decreased FC between the DMN and the CON, which probably resulted from the demyelination of the white matter.

Disrupted Interhemispheric Synchrony in Default Mode Network Underlying the Impairment of Cognitive Flexibility in Late-Onset Depression.

The intuitive association between cognitive impairment and aberrant functional activity in the brain network has prompted interest in exploring the role of functional connectivity in late-onset depression (LOD). The relationship of altered voxel-mirrored homotopic connectivity (VMHC) and cognitive dysfunction in LOD is not yet well understood. This study was designed to examine the implicit relationship between the disruption of interhemispheric functional coordination and cognitive impairment in LOD. LOD patients (N = 31) and matched healthy controls (HCs; N = 37) underwent neuropsychological tests and functional magnetic resonance imaging (fMRI) in this study. The intergroup difference of interhemispheric coordination was determined by calculating VMHC value in the whole brain. The neuro-behavioral relevancy approach was applied to explore the association between disrupted VMHC and cognitive measures. Receiver operating characteristic (ROC) curve analysis was used to determine the capability of disrupted regional VMHC to distinguish LOD. Compared to the HC group, significantly attenuated VMHC in the superior frontal gyrus (SFG), superior temporal gyrus (STG), posterior cerebellar lobe (CePL) and post- and precentral gyri were observed in the bilateral brain of LOD patients. The interhemispheric asynchrony in bilateral CePLs was positively correlated with the performance of trail making test B (TMT-B) in LOD patients (r = 0.367, P = 0.040). ROC analysis revealed that regions with abnormal VMHC could efficiently distinguish LOD from HCs (Area Under Curve [AUC] = 0.90, P < 0.001). Altered linkage patterns of intrinsic homotopic connectivity and impaired cognitive flexibility was first investigated in LOD, and it would provide a novel clue for revealing the neural substrates underlying cognitive impairment in LOD.