Chinese version of the Perth Alexithymia Questionnaire: psychometric properties and clinical applications.

Background: The alexithymia trait is of high clinical interest. The Perth Alexithymia Questionnaire (PAQ) was recently developed to enable detailed facet-level and valence-specific assessments of alexithymia. Aims: In this paper, we introduce the first Chinese version of the PAQ and examine its psychometric properties and clinical applications. Methods: In Study 1, the PAQ was administered to 990 Chinese participants. We examined its factor structure, internal consistency, test-retest reliability, as well as convergent, concurrent and discriminant validity. In Study 2, four groups, including a major depressive disorder (MDD) group (n=50), a matched healthy control group for MDD (n=50), a subclinical depression group (n=50) and a matched healthy control group for subclinical depression (n=50), were recruited. Group comparisons were conducted to assess the clinical relevance of the PAQ. Results: In Study 1, the intended five-factor structure of the PAQ was found to fit the data well. The PAQ showed good internal consistency and test-retest reliability, as well as good convergent, concurrent and discriminant validity. In Study 2, the PAQ was able to successfully distinguish the MDD group and the subclinical depression group from their matched healthy controls. Conclusions: The Chinese version of the PAQ is a valid and reliable instrument for comprehensively assessing alexithymia in the general population and adults with clinical/subclinical depression.

Cross-cultural adaptation and clinical application of the Perth Empathy Scale.

OBJECTIVE: Alterations of empathy have been observed in patients with various mental disorders. The Perth Empathy Scale (PES) was recently developed to measure a multidimensional construct of empathy across positive and negative emotions. However, its psychometric properties and clinical applications have not been examined in the Chinese context. METHODS: The Chinese version of the PES was developed and administered to a large Chinese sample (n = 1090). Factor structure, internal consistency, test-retest reliability, and convergent, discriminant, as well as concurrent validity were examined. Moreover, 50 patients with major depressive disorder (MDD) and 50 healthy controls were recruited to explore the clinical utility of the PES. RESULTS: Confirmatory factor analyses supported a theoretically congruent three-factor structure of empathy, namely Cognitive Empathy, Negative Affective Empathy and Positive Affective Empathy. The PES showed good to excellent internal consistency reliability, good convergent and discriminant validity, acceptable concurrent validity, and moderate to high test-retest reliability. Patients with MDD had significantly lower PES scores compared to healthy controls. Linear discriminant function comprised of the three factors correctly differentiated 71% of participants, which further verified the clinical utility of the PES. CONCLUSIONS: Our findings indicated that the Chinese version of the PES is a reliable and valid instrument to measure cognitive and affective empathy across negative and positive emotions, and could therefore be used in both research and clinical practice.

Unveiling the potential of machine learning in schizophrenia diagnosis: A meta-analytic study of task-based neuroimaging data.

The emergence of machine learning (ML) techniques has opened up new avenues for identifying biomarkers associated with schizophrenia (SCZ) using task-related fMRI (t-fMRI) designs. To evaluate the effectiveness of this approach, we conducted a comprehensive meta-analysis of 31 t-fMRI studies using a bivariate model. Our findings revealed a high overall sensitivity of 0.83 and specificity of 0.82 for t-fMRI studies. Notably, neuropsychological domains modulated the classification performance, with selective attention demonstrating a significantly higher specificity than working memory (ß = 0.98, z = 2.11, P = 0.04). Studies involving older, chronic patients with SCZ reported higher sensitivity (P <0.015) and specificity (P <0.001) than those involving younger, first-episode patients or high-risk individuals for psychosis. Additionally, we found that the severity of negative symptoms was positively associated with the specificity of the classification model (ß = 7.19, z = 2.20, P = 0.03). Taken together, these results support the potential of using task-based fMRI data in combination with machine learning techniques to identify biomarkers related to symptom outcomes in SCZ, providing a promising avenue for improving diagnostic accuracy and treatment efficacy. Future attempts to deploy ML classification should consider the factors of algorithm choice, data quality and quantity, as well as issues related to generalization.

Relationships between childhood trauma and mental health during the COVID-19 pandemic: a network analysis.

Background: Childhood trauma has been found to have an important impact on mental health. However, little is known regarding the intercorrelations between childhood trauma and mental health during the COVID-19 pandemic. This study aimed to investigate such complex interplay between childhood trauma, depression, anxiety, post-traumatic stress level during the COVID-19 pandemic, and fear of COVID-19 using network analysis. Methods: A total of 1,247 college students were recruited and were asked to complete a series of questionnaires, including the Childhood Trauma Questionnaire, Patient Health Questionnaire, Generalized Anxiety Disorder Scale, Post-traumatic Stress Checklist-Civilian version, and Fear of COVID-19 Scale. The Gaussian graphical model with the scores of the questionnaires as nodes was estimated. The partial correlations between nodes were calculated as edges. Moreover, network comparison tests were conducted to compare the network patterns between participants with high levels of childhood trauma and low levels of childhood trauma. Results: Childhood trauma was found to be connected to depression, anxiety, and post-traumatic stress level. The node of childhood trauma exhibited the strongest strength and the highest expected influence in the network. Participants with high levels of childhood trauma and participants with low levels of childhood trauma showed comparable network structure and global strength. Conclusion: Our findings revealed a complex network pattern between childhood trauma and different mental health problems, indicating that childhood trauma might be a risk factor for mental health during the COVID-19 pandemic.

Anterior cingulate glutamate levels associate with functional activation and connectivity during sensory integration in schizophrenia: a multimodal 1H-MRS and fMRI study.

BACKGROUND: Glutamatergic dysfunction has been implicated in sensory integration deficits in schizophrenia, yet how glutamatergic function contributes to behavioural impairments and neural activities of sensory integration remains unknown. METHODS: Fifty schizophrenia patients and 43 healthy controls completed behavioural assessments for sensory integration and underwent magnetic resonance spectroscopy (MRS) for measuring the anterior cingulate cortex (ACC) glutamate levels. The correlation between glutamate levels and behavioural sensory integration deficits was examined in each group. A subsample of 20 pairs of patients and controls further completed an audiovisual sensory integration functional magnetic resonance imaging (fMRI) task. Blood Oxygenation Level Dependent (BOLD) activation and task-dependent functional connectivity (FC) were assessed based on fMRI data. Full factorial analyses were performed to examine the Group-by-Glutamate Level interaction effects on fMRI measurements (group differences in correlation between glutamate levels and fMRI measurements) and the correlation between glutamate levels and fMRI measurements within each group. RESULTS: We found that schizophrenia patients exhibited impaired sensory integration which was positively correlated with ACC glutamate levels. Multimodal analyses showed significantly Group-by-Glutamate Level interaction effects on BOLD activation as well as task-dependent FC in a 'cortico-subcortical-cortical' network (including medial frontal gyrus, precuneus, ACC, middle cingulate gyrus, thalamus and caudate) with positive correlations in patients and negative in controls. CONCLUSIONS: Our findings indicate that ACC glutamate influences neural activities in a large-scale network during sensory integration, but the effects have opposite directionality between schizophrenia patients and healthy people. This implicates the crucial role of glutamatergic system in sensory integration processing in schizophrenia.

Extracellular pollutant degradation feedback regulates intracellular electron transfer process of exoelectrogens: Strategy and mechanism.

Exoelectrogens possess extraordinary degradation ability to various pollutants through extracellular electron transfer (EET). Compared with extracellular electron release process, intracellular electron transfer network is not yet fully recognized. Especially, controversy remains regarding the role of CymA, an essential electron-transfer hub of Shewanella oneidensis MR-1, in EET process. In this study, we thoroughly surveyed the intracellular transfer strategies during EET through dye decolorization. Loss of CymA severely impaired the reduction ability of S. oneidensis MR-1 to methyl orange (MO), but hardly affected the decolorization of aniline blue (AB). Complement of cymA fully restored the MO decolorization ability of ΔcymA mutant. The contribution of CymA to extracellular decolorization was subjected to MO concentrations. The defect in the decolorization ability of ΔcymA mutant was not evident at low MO concentration, but severe at high MO concentration. Further investigation revealed that EET rate determined the significance of CymA in the extracellular bioremediation by S. oneidensis MR-1. Coupled with MO concentrations increasing from 15 to 120 mg/L, the initial electron transfer rates of S. oneidensis MR-1 increased accordingly from 2.69 × 104 to 11.21 × 104 electrons CFU-1 s-1, which led to a gradual increase of the dependencyCymA. Thus, we first revealed that extracellular degradation performance could feedback regulate the intracellular electron transfer process of S. oneidensis MR-1. This work is helpful to fully understand the complex EET process of exoelectrogens and facilitates the application of exoelectrogens in bioremediation of environmental pollutants.

Altered brain structural and functional connectivity in schizotypy.

BACKGROUND: Schizotypy refers to schizophrenia-like traits below the clinical threshold in the general population. The pathological development of schizophrenia has been postulated to evolve from the initial coexistence of 'brain disconnection' and 'brain connectivity compensation' to 'brain connectivity decompensation'. METHODS: In this study, we examined the brain connectivity changes associated with schizotypy by combining brain white matter structural connectivity, static and dynamic functional connectivity analysis of diffusion tensor imaging data and resting-state functional magnetic resonance imaging data. A total of 87 participants with a high level of schizotypal traits and 122 control participants completed the experiment. Group differences in whole-brain white matter structural connectivity probability, static mean functional connectivity strength, dynamic functional connectivity variability and stability among 264 brain sub-regions of interests were investigated. RESULTS: We found that individuals with high schizotypy exhibited increased structural connectivity probability within the task control network and within the default mode network; increased variability and decreased stability of functional connectivity within the default mode network and between the auditory network and the subcortical network; and decreased static mean functional connectivity strength mainly associated with the sensorimotor network, the default mode network and the task control network. CONCLUSIONS: These findings highlight the specific changes in brain connectivity associated with schizotypy and indicate that both decompensatory and compensatory changes in structural connectivity within the default mode network and the task control network in the context of whole-brain functional disconnection may be an important neurobiological correlate in individuals with high schizotypy.

Smartphone addiction is more harmful to adolescents than Internet gaming disorder: Divergence in the impact of parenting styles.

Background: The adverse effects of smartphone addiction (SPA) and Internet gaming disorder (IGD) on adolescents' mental health have been widely recognized. However, the influence of parenting styles on these high-risk Internet use behaviors of adolescents still remain elusive. Aiming to identify preventable patterns for adolescents with SPA or IGD, this study compared the mental health status between adolescents with SPA and IGD and used path analysis to confirm actual effects of parenting styles on SPA and IGD. Methods: Participants were enrolled at a junior high school in Hunan Province and a senior high school in Shanxi Province, China [n = 3,049, female (male): 50.5% (49.5%), mean age = 15.68 ± 1.54]. All participants reported their socio-demographic characteristics and undertook standardized assessments of SPA, IGD, parenting styles, depression, anxiety, insomnia, self-control, and support utilization. Results: High levels of parental care and low levels of parental overprotection benefited adolescents' mental health with SPA and IGD. However, despite having a more positive parenting style, adolescents with only SPA showed more severe mental health problems than adolescents with only IGD. Furthermore, the results showed that the parenting style of encouraging autonomy might be a protective factor against IGD, but it might reinforce SPA indirectly by reducing abilities of support utilization and self-control in whole sample. Conclusion: Compared to IGD, SPA which included different kinds of Internet addiction behaviors, was more hazardous for adolescents' mental health. The divergent effects of an autonomy-encouraging parenting style on SPA and IGD may reflect the different impacts of self-control in different types of Internet addiction.

Striatal GABA level is associated with sensory integration ability in individuals with low levels of negative schizotypy.

Recent studies suggest that altered gamma-aminobutyric acidergic (GABAergic) function may result in multisensory integration deficits in schizophrenia. However, it is unclear whether the GABA level is abnormal in individuals with high levels of schizotypal traits and how it would correlate with sensory integration ability in these individuals. This study aimed to compare the GABA level between individuals with high and low levels of negative schizotypy, and examine the relationship between GABA levels and sensory integration ability in each group. In vivo GABA+ and N-acetylaspartate (NAA) levels in the striatum were measured using proton magnetic resonance imaging in 19 participants with high levels of negative schizotypy and 21 participants with low levels of negative schizotypy. The Sensory Integration subscale of the abridged version of the Cambridge Neurological Inventory was used. We examined the group differences in GABA+/NAA levels, and the correlation between striatal GABA+/NAA levels and sensory integration ability in each group. The two groups showed comparable levels of in-vivo GABA+/NAA. In-vivo GABA+/NAA levels were negatively correlated with sensory integration score in participants with low levels of negative schizotypy, but not in participants with high levels of negative schizotypy. Our findings indicate that the increased GABA level is correlated with better sensory integration ability in individuals with low levels of negative schizotypy, implicating the role of GABAergic function in multisensory integration. Unlike schizophrenia patients, individuals with high levels of schizotypy do not exhibit any abnormality in their GABAergic system and sensory integration ability.

Altered empathy-related resting-state functional connectivity in patients with bipolar disorder.

Empathy is the ability to generate emotional responses (i.e., cognitive empathy) and to make cognitive inferences (i.e., affective empathy) to other people's emotions. Empirical evidence suggests that patients with bipolar disorder (BD) exhibit impairment in cognitive empathy, but findings on affective empathy are inconsistent. Few studies have examined the neural mechanisms of cognitive and affective empathy in patients with BD. In this study, we examined the empathy-related resting-state functional connectivity (rsFC) in BD patients. Thirty-seven patients with BD and 42 healthy controls completed the self-report Questionnaires of Cognitive and Affective Empathy (QCAE), the Yoni behavioural task, and resting-sate fMRI brain scans. Group comparison of empathic ability was conducted. The interactions between group and empathic ability on seed-based whole brain rsFC were examined. BD patients scored lower on the Online Simulation subscale of the QCAE and showed positive correlations between cognitive empathy and the rsFC of the dorsal Medial Prefrontal Cortex (dmPFC) with the lingual gyrus. The correlations between cognitive empathy and the rsFC of the temporal-parietal junction (TPJ) with the fusiform gyrus, the cerebellum and the parahippocampus were weaker in BD patients than that in healthy controls. These findings highlight the underlying neural mechanisms of empathy impairments in BD patients.

Social brain network predicts real-world social network in individuals with social anhedonia.

Social anhedonia (SA) impairs social functioning in schizophrenia. Previous evidence suggested that certain brain regions predict longitudinal change of real-world social outcomes, yet previous study designs have failed to capture the corresponding functional connectivity among the brain regions involved. This study measured the real-world social network in 22 pairs of individuals with high and low levels of SA, and followed up them for 21 months. We further explored whether resting-state social brain network characteristics could predict the longitudinal variations of real-world social network. Our results showed that social brain network characteristics could predict the change of real-world social networks in both the high SA and low SA groups. However, the results differed between the two groups, i.e., the topological characteristics of the social brain network predicted real-world social network change in the high SA group; whereas the functional connectivity within the social brain network predicted real-world social network change in the low SA group. Principal component analysis and linear regression analysis on the entire sample showed that the functional connectivity component centered at the right orbital inferior frontal gyrus could best predict social network change. Our findings support the notion that social brain network characteristics could predict social network development.

Social brain network correlates with real-life social network in individuals with schizophrenia and social anhedonia.

Social behaviour requires the brain to efficiently integrate multiple social processes, but it is not clear what neural substrates underlie general social behaviour. While psychosis patients and individuals with subclinical symptoms are characterized by social dysfunction, the neural mechanisms underlying social dysfunctions in schizophrenia spectrum disorders remains unclear. We first constructed a general social brain network (SBN) using resting-state functional connectivity (FC) with regions of interest based on the automatic meta-analysis results from NeuroSynth. We then examined the general SBN and its relationship with social network (SN) characteristics in 30 individuals with schizophrenia (SCZ) and 33 individuals with social anhedonia (SA). We found that patients with SCZ exhibited deficits in their SN, while SA individuals did not. SCZ patients showed decreased segregation and functional connectivity in their SBN, while SA individuals showed a reversed pattern with increased segregation and functional connectivity of their SBN. Sparse canonical correlation analysis showed that both SCZ patients and SA individuals exhibited reduced correlation between SBN and SN characteristics compared with their corresponding healthy control groups. These preliminary findings suggest that both SCZ and SA participants exhibit abnormality in segregation and functional connectivity within the general SBN and reduced correlation with SN characteristics. These findings could guide the development of non-pharmacological interventions for social dysfunction in SCZ spectrum disorders.

Neurological Soft Signs Are Associated With Altered Cerebellar-Cerebral Functional Connectivity in Schizophrenia.

Cerebellar dysfunction is associated with neurological soft signs (NSS), which is a promising endophenotype for schizophrenia spectrum disorders. However, the relationship between cerebellar-cerebral resting-state functional connectivity (rsFC) and NSS is largely unexplored. Moreover, both NSS and cerebellar-cerebral rsFC have been found to be correlated with negative symptoms of schizophrenia. Here, we investigated the correlations between NSS and cerebellar-cerebral rsFC, explored their relationship with negative symptoms in a main dataset, and validated the significant findings in a replication dataset. Both datasets comprised schizophrenia patients and healthy controls. In schizophrenia patients, we found positive correlations between NSS and rsFC of the cerebellum with the inferior frontal gyrus and the precuneus, and negative correlations between NSS and rsFC of the cerebellum with the inferior temporal gyrus. In healthy controls, NSS scores were positively correlated with rsFC of the cerebellum with the superior frontal gyrus and negatively correlated with rsFC between the cerebellum and the middle occipital gyrus. Cerebellar-prefrontal rsFC was also positively correlated with negative symptoms in schizophrenia patients. These findings were validated in the replication dataset. Our results suggest that the uncoupling of rsFC between the cerebellum and the cerebral cortex may underlie the expression of NSS in schizophrenia. NSS-related cerebellar-prefrontal rsFC may be a potential neural pathway for possible neural modulation to alleviate negative symptoms.

Visual short-term memory and attention: An investigation of familiarity and stroke count in Chinese characters.

Using Chinese characters, we investigated how stroke count and frequency of use influence attention and short-term memory (STM) encoding in Mainland Chinese speakers. To isolate specific components of attention we employed the Theory of Visual Attention (TVA), which allowed estimates of STM capacity, processing speed, and the threshold of visual perception. An analysis of TVA parameters revealed that familiarity affects both the memory capacity and processing speed of objects, whereas the threshold for visual perception remained unaffected. Interestingly, our results also indicate that modulation of attention is driven solely by familiarity with the characters, independent of the actual physical aspect of Chinese characters. We propose that mental categories and prior knowledge play a vital role in the processing of information in attention, as well as in how this information is stored and represented in visual STM. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Validation of the Questionnaire of Cognitive and Affective Empathy in patients with schizophrenia, major depressive disorder and bipolar disorder.

INTRODUCTION: Alteration of empathy is common in patients with psychiatric disorders. Reliable and valid assessment tools for measuring empathy of clinical samples is needed. The Questionnaire of Cognitive and Affective Empathy (QCAE) is a newly-developed instrument to capture cognitive and affective components of empathy. This study aimed to validate the QCAE and compared self-reported empathy between clinical groups with varied psychiatric diagnoses and healthy sample. METHODS: The present study performed factor analysis for the QCAE on clinical samples in the Chinese setting (n = 534), including patients with schizophrenia (n = 158), bipolar disorder (n = 213) and major depressive disorder (n = 163). Internal consistency, internal correlation and convergent validity was examined in the subsample (n = 361). Group comparison among patients with schizophrenia, bipolar disorder, major depressive disorder and healthy controls (n = 107) was conducted to assess the discriminant validity. RESULTS: Our results indicated acceptable factor model, good reliability and validity of the QCAE. Impaired cognitive empathy was found in clinical samples, especially in patients with schizophrenia, while higher affective empathy was found in patients with bipolar disorder and major depressive disorder. CONCLUSION: The QCAE is a useful tool in assessing empathy in patients with varied psychiatric diagnoses.

Grey matter volume and structural covariance associated with schizotypy.

In this study, we applied brain grey matter volume and structural covariance methods on T1 weighted images to delineate potential structural brain changes in individuals with high schizotypy, who were defined as healthy individuals scoring in the top tenth percentile of the Schizotypal Personality Questionnaire (SPQ). Eighty-seven college students with high schizotypy and 122 controls were recruited in China. Differences in grey matter volume and volume covariance between the two groups, and correlations of grey matter volume with SPQ scores in the high schizotypy group were examined. We found that individuals with high schizotypy had decreased grey matter volume at the left medial superior frontal gyrus (medsFG) extending towards the superior frontal gyrus, decreased structural covariance within the right medsFG, between the right superior frontal gyrus (sFG), the right superior temporal gyrus and the right anterior insula; and increased structural covariance between the caudate and the right inferior temporal gyrus. Correlation analysis revealed that grey matter volume of the left middle temporal pole and the right sFG correlated positively with the SPQ total scores, volume of the bilateral cerebellum 9 sub-region correlated negatively with the SPQ cognitive-perceptual sub-scale scores, volume of the bilateral striatum correlated positively with the SPQ interpersonal sub-scale scores, and volume of the bilateral superior temporal pole correlated positively with the SPQ disorganization sub-scale scores in the high schizotypy group. These results highlight important grey matter structural changes in the medsFG in individuals with high schizotypy.

Altered default mode network functional connectivity in individuals with co-occurrence of schizotypy and obsessive-compulsive traits.

In this study, we examined differences in resting-state functional connectivity between sub-regions of the Default Mode Network (DMN) and whole brain voxels in 22 individuals with high schizo-obsessive traits (SOT), 30 with high schizotypal traits (SCT) alone, 20 with high obsessive-compulsive traits (OCT) alone and 30 with low trait scores (LT). We found that the SOT group showed the most reduced functional connectivity within the DMN compared with the other groups. The SOT group also showed increased connectivity between the DMN and the Salience Network, and between the DMN and the Auditory Network compared with the LT group. The SCT group exhibited increased connectivity between the DMN and the Salience Network, and between the DMN and the Executive Control Network (ECN) compared with the LT group. The OCT group exhibited decreased connectivity within the DMN, between the DMN and the Salience Network, and between the DMN and the ECN compared with the LT group. These findings highlight different changes in DMN-related functional connectivity associated with high SOT, SCT and OCT traits and may provide insight into the dysfunctional brain networks in the early stage of schizophrenia spectrum disorders.

Altered grey matter volume and white matter integrity in individuals with high schizo-obsessive traits, high schizotypal traits and obsessive-compulsive symptoms.

Altered brain structures have been found in patients with schizo-obsessive disorder, schizophrenia and obsessive-compulsive disorder in previous studies. However, it is unclear whether similar brain changes are also found in individuals with high schizo-obsessive traits (SOT), high schizotypal traits (SCT) and obsessive-compulsive symptoms (OCS). We examined grey matter volume (GMV) and white matter integrity (WMI, including fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity) in 26 individuals with high SOT, 30 individuals with high SCT, 25 individuals with OCS and 30 individuals with low trait scores (LT) in this study. Correlation analysis between GMV, WMI, Schizotypal Personality Questionnaire (SPQ) scores and Obsessive-Compulsive Inventory-Revised (OCI-R) scores in the subclinical groups was also carried out. We found that the SOT group exhibited increased GMV at the right superior occipital gyrus and the left postcentral gyrus compared with the LT group. The SCT group exhibited increased GMV at the right precentral gyrus and the bilateral cuneus compared with the LT group, and decreased fractional anisotropy at the anterior corona radiata compared with the other three groups. The OCS group exhibited increased GMV at the left superior temporal gyrus and decreased GMV at the left pre-supplementary motor area compared with the LT group. These findings highlight specific brain changes in individuals with high SOT, high SCT and OCS, and may thus provide new insights into the neurobiological changes that occur in sub-clinical populations of these disorders.

Generalizability of machine learning for classification of schizophrenia based on resting-state functional MRI data.

Machine learning has increasingly been applied to classification of schizophrenia in neuroimaging research. However, direct replication studies and studies seeking to investigate generalizability are scarce. To address these issues, we assessed within-site and between-site generalizability of a machine learning classification framework which achieved excellent performance in a previous study using two independent resting-state functional magnetic resonance imaging data sets collected from different sites and scanners. We established within-site generalizability of the classification framework in the main data set using cross-validation. Then, we trained a model in the main data set and investigated between-site generalization in the validated data set using external validation. Finally, recognizing the poor between-site generalization performance, we updated the unsupervised algorithm to investigate if transfer learning using additional unlabeled data were able to improve between-site classification performance. Cross-validation showed that the published classification procedure achieved an accuracy of 0.73 using majority voting across all selected components. External validation found a classification accuracy of 0.55 (not significant) and 0.70 (significant) using the direct and transfer learning procedures, respectively. The failure of direct generalization from one site to another demonstrates the limitation of within-site cross-validation and points toward the need to incorporate efforts to facilitate application of machine learning across multiple data sets. The improvement in performance with transfer learning highlights the importance of taking into account the properties of data when constructing predictive models across samples and sites. Our findings suggest that machine learning classification result based on a single study should be interpreted cautiously.

Identifying Schizo-Obsessive Comorbidity by Tract-Based Spatial Statistics and Probabilistic Tractography.

A phenomenon in schizophrenia patients that deserves attention is the high comorbidity rate with obsessive-compulsive disorder (OCD). Little is known about the neurobiological basis of schizo-obsessive comorbidity (SOC). We aimed to investigate whether specific changes in white matter exist in patients with SOC and the relationship between such abnormalities and clinical parameters. Twenty-eight patients with SOC, 28 schizophrenia patients, 30 OCD patients, and 30 demographically matched healthy controls were recruited. Using Tract-based Spatial Statistics and Probabilistic Tractography, we examined the pattern of white matter abnormalities in these participants. We also used ANOVA and Support Vector Classification of various white matter indices and structural connection probability to further examine white matter changes among the 4 groups. We found that patients with SOC had decreased fractional anisotropy (FA) and increased radial diffusivity in the right sagittal stratum and the left crescent of the fornix/stria terminalis compared with healthy controls. We also found changed connection probability in the Default Mode Network, the Subcortical Network, the Attention Network, the Task Control Network, the Visual Network, the Somatosensory Network, and the cerebellum in the SOC group compared with the other 3 groups. The classification results further revealed that FA features could differentiate the SOC group from the other 3 groups with an accuracy of .78. These findings highlight the specific white matter abnormalities found in patients with SOC.