Inefficient DMN Suppression in Schizophrenia Patients with Impaired Cognitive Function but not Patients with Preserved Cognitive Function

Dynamic modular dysregulation in multilayer networks underlies cognitive and clinical deficits in first-episode schizophrenia

Schizophrenia has been identified to exhibit significant abnormalities in brain functional networks, which are likely to underpin the cognitive and functional impairments observed in patients. Graph theoretical analysis revealed the disrupted modularity in schizophrenia, however, the dynamic network abnormalities in schizophrenia remains unclear. We collected the resting-state functional magnetic resonance imaging data from 82 first-episode schizophrenia (FES) patients and 55 healthy control (HC) subjects. Dynamic functional connectivity matrices were constructed and a multilayer network model was employed to run the dynamic modularity analysis. We also performed correlation analyses to investigate the relationship between flexibility, cognitive function and clinical symptoms. Our findings indicate that FES patients exhibit higher multilayer modularity. The node flexibility of FES patients were found elevated in several brain regions, which were included in the default mode network, fronto-parietal network, salience network and visual network. The node flexibility metrics in aberrant brain regions were found to demonstrate significant correlations with cognitive function and negative symptoms in patients with FES. These findings suggest a pathological imbalance in brain network dynamics, where abnormal modular organization might contribute to the cognitive impairment and functional deficits in schizophrenia.

Relationships Between Immune-Inflammatory Features and Social Cognitive Impairments in Patients With Schizophrenia Spectrum Disorders: A Systematic Review

INTRODUCTION

Patients with schizophrenia spectrum disorders (SSD), particularly patients with schizophrenia, have social cognitive impairments characterized by difficulties in emotion recognition, the ability to attribute mental states, explaining the causes of events, and identifying and utilizing social cues. These impairments appear from early life and are associated with poor functional and social prognosis. The origin of these impairments is not fully understood. The inflammatory hypothesis is one of the pathophysiological hypotheses of schizophrenia. Inflammatory marker abnormalities are also present in the early stages of schizophrenia and are associated with neuronal degeneration. Following our main hypothesis, the aim of this work was to conduct a review to explore the relationship between social cognition and inflammatory markers in SSD.

METHODS

The review included original studies reporting measures of social cognition and plasma levels of inflammatory markers in patients with SSD using the Pubmed, PsycINFO, and Embase databases. The PRISMA methodology was followed.

RESULTS

Eleven studies were selected and analyzed. They showed significant correlations between plasma cytokine levels and theory of mind and facial emotion recognition abilities.

CONCLUSION

The correlations do not seem to be specific to social cognitive impairments, but our results support the hypothesis of a link between pro- and anti-inflammatory markers and cognition in SSD. In the future, other studies should be conducted to clarify this link from a diagnostic and therapeutic perspective: identification of inflammatory trait factors and patient subgroups and personalized anti-inflammatory therapies.

Default Mode Network, Disorganization, and Treatment-Resistant Schizophrenia

BACKGROUND AND HYPOTHESIS

Disorganized thinking is a prominent feature of schizophrenia that becomes persistent in the presence of treatment resistance. Disruption of the default mode network (DMN), which regulates self-referential thinking, is now a well-established feature of schizophrenia. However, we do not know if DMN disruption affects disorganization and contributes to treatment-resistant schizophrenia (TRS).

STUDY DESIGN

This study investigated the DMN in 48 TRS, 76 non-TRS, and 64 healthy controls (HC) using a spatiotemporal approach with resting-state functional magnetic resonance imaging. We recovered DMN as an integrated network using multivariate group independent component analysis and estimated its loading coefficient (reflecting spatial prominence) and Shannon Entropy (reflecting temporal variability). Additionally, voxel-level analyses were conducted to examine network homogeneity and entropy within the DMN. We explored the relationship between DMN measures and disorganization using regression analysis.

RESULTS

TRS had higher spatial loading on population-level DMN pattern, but lower entropy compared to HC. Non-TRS patients showed intermediate DMN alterations, not significantly differing from either TRS or HC. No voxel-level differences were noted between TRS and non-TRS, emphasizing the continuum between the two groups. DMN's loading coefficient was higher in patients with more severe disorganization.

CONCLUSIONS

TRS may represent the most severe end of a spectrum of spatiotemporal DMN dysfunction in schizophrenia. While excessive spatial contribution of the DMN (high loading coefficient) is specifically associated with disorganization, both excessive spatial contribution and exaggerated temporal stability of DMN are features of schizophrenia that become more pronounced with refractoriness to first-line treatments.

Functional connectivity changes in the prefrontal-thalamic-cerebellar circuit in adolescents with first-episode Schizophrenia

BACKGROUND

The role of functional connectivity (FC) changes in the prefrontal-thalamic-cerebellar circuit in schizophrenia has received widespread attention. Currently, domestic and international studies on this circuit have focused on adults, while the FC of this circuit in the brains of adolescent patients with schizophrenia (AOS) has been less reported.

METHODS

We recruited 124 subjects who underwent resting-state functional magnetic resonance imaging scans at baseline, using key brain regions in the prefrontal-thalamic-cerebellar circuit as seed regions, to investigate the FC in AOS versus healthy controls. The FC of this loop was compared with that of the whole brain in healthy controls.

RESULTS

Compared to healthy controls, patients with AOS had reduced FC between the medial prefrontal cortex (mPFC) and precuneus (PCu) and between the posterior cerebellar lobe and middle temporal gyrus. Reduced FC between the left mPFC and the left PCu in patients with AOS was associated with positive symptom scores on the PANSS and was positively correlated with the Symbolic Encoding Scale, the Maze Scale, and the Category Fluency Test Scale. Reduced FC between the right posterior cerebellar lobe and the right middle temporal gyrus is positively correlated with the simple visuospatial memory test in AOS patients.

CONCLUSIONS

There are FC abnormalities in the prefrontal-thalamic-cerebellar circuit, precuneus, and temporal lobe in AOS. These abnormalities appear in the early stages of schizophrenia, independent of medication, and are characteristic of the disorder.

Task-based default mode network connectivity predicts cognitive impairment and negative symptoms in first-episode schizophrenia

Individuals diagnosed with schizophrenia (SZ) demonstrate difficulty distinguishing between internally and externally generated stimuli. These aberrations in "source monitoring" have been theorized as contributing to symptoms of the disorder, including hallucinations and delusions. Altered connectivity within the default mode network (DMN) of the brain has been proposed as a mechanism through which discrimination between self-generated and externally generated events is disrupted. Source monitoring abnormalities in SZ have additionally been linked to impairments in selective attention and inhibitory processing, which are reliably observed via the N100 component of the event-related brain potential elicited during an auditory paired-stimulus paradigm. Given overlapping constructs associated with DMN connectivity and N100 in SZ, the present investigation evaluated relationships between these measures of disorder-related dysfunction and sought to clarify the nature of task-based DMN function in SZ. DMN connectivity and N100 measures were assessed using EEG recorded from SZ during their first episode of illness (N = 52) and demographically matched healthy comparison participants (N = 25). SZ demonstrated less evoked theta-band connectivity within DMN following presentation of pairs of identical auditory stimuli than HC. Greater DMN connectivity among SZ was associated with better performance on measures of sustained attention (p = .03) and working memory (p = .09), as well as lower severity of negative symptoms, though it was not predictive of N100 measures. Together, present findings provide EEG evidence of lower task-based connectivity among first-episode SZ, reflecting disruptions of DMN functions that support cognitive processes. Attentional processes captured by N100 appear to be supported by different neural mechanisms.

Towards New Methodology for Cross-Validation of Clinical Evaluation Scales and Functional MRI in Psychiatry

Objective biomarkers have been a critical challenge for the field of psychiatry, where diagnostic, prognostic, and theranostic assessments are still based on subjective narratives. Psychopathology operates with idiographic knowledge and subjective evaluations incorporated into clinical assessment inventories, but is considered to be a medical discipline and, as such, uses medical intervention methods (e.g., pharmacological, ECT; rTMS; tDCS) and, therefore, is supposed to operate with the language and methods of nomothetic networks. The idiographic assessments are provisionally "quantified" into "structured clinical scales" to in some way resemble nomothetic measures. Instead of fostering data merging and integration, this approach further encapsulates the clinical psychiatric methods, as all other biological tests (molecular, neuroimaging) are performed separately, only after the clinical assessment has provided diagnosis. Translational cross-validation of clinical assessment instruments and fMRI is an attempt to address the gap. The aim of this approach is to investigate whether there exist common and specific neural circuits, which underpin differential item responses to clinical self-rating scales during fMRI sessions in patients suffering from the two main spectra of mental disorders: schizophrenia and major depression. The current status of this research program and future implications to promote the development of psychiatry as a medical discipline are discussed.

Association of Longitudinal Changes in Cerebral Microstructure with Cognitive Functioning in Breast Cancer Survivors after Adjuvant Chemotherapy

Background: Adjuvant chemotherapy for breast cancer might impact cognitive function and brain structure. Methods: In this study, we investigated the cerebral microstructural changes in breast cancer survivors after adjuvant chemotherapy and the correlation with cognitive function with both cross-sectional and longitudinal study designs. All participants underwent structural MRI. In total, we recruited 67 prechemotherapy patients (BB), 67 postchemotherapy patients (BA), and 77 healthy controls (BH). For the follow-up study, 28 participants in the BH and 28 in the BB groups returned for imaging and assessment (BHF, BBF). Voxel-based morphometry analysis was performed to evaluate differences in brain volume; vertex-based shape analysis was used to assess the shape alterations of subcortical regions. Moreover, multiple regression was applied to assess the association between the changes in neuropsychological assessment and brain volume. Results: The results showed brain volume reduction in the temporal and parietal gyrus in BB and BA patients. Among each group, we also found significant shape alterations in the caudate and thalamus. Volume reductions in the temporal regions and shape changes in the caudate and hippocampus were also observed in patients from time point 1 to time point 2 (postchemotherapy). An association between brain volume and cognitive performance was also found in the limbic system. Conclusions: Based on our findings, we can provide a better understanding of the cerebral structural changes in breast cancer survivors, establish a subsequent prediction model, and serve as a reference for subsequent treatment.

Early life stress, low-grade systemic inflammation and weaker suppression of the default mode network (DMN) during face processing in Schizophrenia

Childhood trauma (CT) is associated with lower cognitive and social cognitive function in schizophrenia. Recent evidence suggests that the relationship between CT and cognition is mediated by both low-grade systemic inflammation and reduced connectivity of the default mode network (DMN) during resting state. This study sought to test whether the same pattern of associations was observed for DMN connectivity during task based activity. Fifty-three individuals with schizophrenia (SZ) or schizoaffective disorder (SZA) and one hundred and seventy six healthy participants were recruited from the Immune Response and Social Cognition (iRELATE) project. A panel of pro-inflammatory markers that included IL-6, IL-8, IL-10, tumour necrosis factor-alpha (TNFa), and C-reactive protein (CRP), were measured in plasma using ELISA. DMN connectivity was measured during an fMRI social cognitive face processing task. Patients showed evidence of low grade systemic inflammation and significantly increased connectivity between the left lateral parietal (LLP) cortex-cerebellum and LLP-left angular gyrus compared to healthy participants. Across the entire sample, IL-6 predicted increased connectivity between LLP-cerebellum, LLP-precuneus, and mPFC-bilateral-precentral-gyri and left postcentral gyrus. In turn, and again in the entire sample, IL-6 (but no other inflammatory marker) mediated the relationship between childhood physical neglect and LLP-cerebellum. Physical neglect scores also significantly predicted the positive association between IL-6 and LLP-precuneus connectivity. This is to our knowledge the first study that provides evidence that higher plasma IL-6 mediates the association between higher childhood neglect and increased DMN connectivity during task based activity. Consistent with our hypothesis, exposure to trauma is associated with weaker suppression of the DMN during a face processing task, and this association was mediated via increased inflammatory response. The findings may represent part of the biological mechanism by which CT and cognitive performance are related.

Spatiotemporal dynamics of functional connectivity and association with molecular architecture in schizophrenia

Schizophrenia is a self-disorder characterized by disrupted brain dynamics and architectures of multiple molecules. This study aims to explore spatiotemporal dynamics and its association with psychiatric symptoms. Resting-state functional magnetic resonance imaging data were collected from 98 patients with schizophrenia. Brain dynamics included the temporal and spatial variations in functional connectivity density and association with symptom scores were evaluated. Moreover, the spatial association between dynamics and receptors/transporters according to prior molecular imaging in healthy subjects was examined. Patients demonstrated decreased temporal variation and increased spatial variation in perceptual and attentional systems. However, increased temporal variation and decreased spatial variation were revealed in higher order networks and subcortical networks in patients. Specifically, spatial variation in perceptual and attentional systems was associated with symptom severity. Moreover, case-control differences were associated with dopamine, serotonin and mu-opioid receptor densities, serotonin reuptake transporter density, dopamine transporter density, and dopamine synthesis capacity. Therefore, this study implicates the abnormal dynamic interactions between the perceptual system and cortical core networks; in addition, the subcortical regions play a role in the dynamic interaction among the cortical regions in schizophrenia. These convergent findings support the importance of brain dynamics and emphasize the contribution of primary information processing to the pathological mechanism underlying schizophrenia.

Temporal Stability of Dynamic Default Mode Network Connectivity Negatively Correlates with Suicidality in Major Depressive Disorder

Previous studies have demonstrated that the suicidality in patients with major depressive disorder (MDD) is related to abnormal brain functional connectivity (FC) patterns. However, little is known about its relationship with dynamic functional connectivity (dFC) based on the assumption that brain FCs fluctuate over time. Temporal stabilities of dFCs within the whole brain and nine key networks were compared between 52 MDD patients and 21 age, sex-matched healthy controls (HCs) using resting-state functional magnetic resonance imaging and temporal correlation coefficients. The alterations in MDD were further correlated with the scores of suicidality item in the Hamilton Rating Scale for Depression (HAMD). Compared with HCs, the MDD patients showed a decreased temporal stability of dFC as indicated by a significantly decreased temporal correlation coefficient at the global level, as well as within the default mode network (DMN) and subcortical network. In addition, temporal correlation coefficients of the DMN were found to be significantly negatively correlated with the HAMD suicidality item scores in MDD patients. These results suggest that MDD may be characterized by excessive temporal fluctuations of dFCs within the DMN and subcortical network, and that decreased stability of DMN connectivity may be particularly associated with the suicidality in MDD.

Interactions between the cortical midline structures and sensorimotor network track maladaptive self-beliefs in clinical high risk for psychosis

Individuals at clinical high risk for psychosis (CHR) report a maladaptive self-concept—with more negative and less positive self-beliefs—linked to clinical symptoms and functional impairment. Alterations have also been reported in brain networks associated with intrinsic (cortical midline structures, CMS) and extrinsic (sensorimotor network, SMN) self-processing. Theoretical accounts of multiple levels of self-experience in schizophrenia suggest that interactions between these networks would be relevant for self-beliefs. This study tested whether self-beliefs related to resting-state functional connectivity within and between the CMS and SMN. Participants were 56 individuals meeting CHR criteria and 59 matched healthy community participants (HC). Pearson correlations examined potential mediators and outcomes. The CHR group reported more negative and less positive self-beliefs. Greater resting-state functional connectivity between the posterior CMS (posterior cingulate cortex) and the SMN was associated with less positive self-beliefs in CHR, but more positive self-beliefs in HC. Attenuated negative symptoms and poorer social functioning were associated with CMS-SMN connectivity (trend level after FDR-correction) and self-beliefs. Reduced connectivity between the left and right PCC was associated with lower positive self-beliefs in CHR, although this effect was specific to very low levels of positive self-beliefs. Left-right PCC connectivity did not correlate with outcomes. Dynamic interactions between intrinsic and extrinsic self-processing supported positive self-beliefs in typically developing youth while undermining positive self-beliefs in CHR youth. Implications are discussed for basic self-fragmentation, narrative self-related metacognition, and global belief updating. Interventions for self-processing may be beneficial in the CHR syndrome.

Load-dependent inverted U-shaped connectivity of the default mode network in schizophrenia during a working-memory task: evidence from a replication functional MRI study

BACKGROUND

Working-memory deficit is associated with aberrant degree distribution of the brain connectome in schizophrenia. However, the brain neural mechanism underlying the degree redistribution pattern in schizophrenia is still uncertain.

METHODS

We examined the functional degree distribution of the connectome in 81 patients with schizophrenia and 77 healthy controls across different working-memory loads during an n-back task. We tested the associations between altered degree distribution and clinical symptoms, and we conducted functional connectivity analyses to investigate the neural mechanism underlying altered degree distribution. We repeated these analyses in a second independent data set of 96 participants. In the second data set, we employed machine-learning analysis to study whether the degree distribution pattern of one data set could be used to discriminate between patients with schizophrenia and controls in the other data set.

RESULTS

Patients with schizophrenia showed decreased centrality in the dorsal posterior cingulate cortex (dPCC) for the "2-back versus 0-back" contrast compared to healthy controls. The dPCC centrality pattern across all working-memory loads was an inverted U shape, with a left shift of this pattern in patients with schizophrenia. This reduced centrality was correlated with the severity of delusions and related to reduced functional connectivity between the dPCC and the dorsal precuneus. We replicated these results with the second data set, and the machine-learning analyses achieved an accuracy level of 71%.

LIMITATIONS

We used a limited n-back paradigm that precluded the examination of higher working-memory loads.

CONCLUSION

Schizophrenia is characterized by a load-dependent reduction of centrality in the dPCC, related to the severity of delusions. We suggest that restoring dPCC centrality in the presence of cognitive demands might have a therapeutic effect on persistent delusions in people with schizophrenia.

Altered large-scale brain network interactions associated with HIV infection and error processing

Altered activity within and between large-scale brain networks has been implicated across various neuropsychiatric conditions. However, patterns of network dysregulation associated with human immunodeficiency virus (HIV), and further impacted by cannabis (CB) use, remain to be delineated. We examined the impact of HIV and CB on resting-state functional connectivity (rsFC) between brain networks and associations with error awareness and error-related network responsivity. Participants (N = 106), stratified into four groups (HIV+/CB+, HIV+/CB-, HIV-/CB+, HIV-/CB-), underwent fMRI scanning while completing a resting-state scan and a modified Go/NoGo paradigm assessing brain responsivity to errors and explicit error awareness. We examined separate and interactive effects of HIV and CB on resource allocation indexes (RAIs), a measure quantifying rsFC strength between the default mode network (DMN), central executive network (CEN), and salience network (SN). We observed reduced RAIs among HIV+ (vs. HIV-) participants, which was driven by increased SN-DMN rsFC. No group differences were detected for SN-CEN rsFC. Increased SN-DMN rsFC correlated with diminished error awareness, but not with error-related network responsivity. These outcomes highlight altered network interactions among participants with HIV and suggest such rsFC dysregulation may persist during task performance, reflecting an inability to disengage irrelevant mental operations, ultimately hindering error processing.

Subcortical control of the default mode network: Role of the basal forebrain and implications for neuropsychiatric disorders

The precise interplay between large-scale functional neural systems throughout the brain is essential for performance of cognitive processes. In this review we focus on the default mode network (DMN), one such functional network that is active during periods of quiet wakefulness and believed to be involved in introspection and planning. Abnormalities in DMN functional connectivity and activation appear across many neuropsychiatric disorders, including schizophrenia. Recent evidence suggests subcortical regions including the basal forebrain are functionally and structurally important for regulation of DMN activity. Within the basal forebrain, subregions like the ventral pallidum may influence DMN activity and the nucleus basalis of Meynert can inhibit switching between brain networks. Interactions between DMN and other functional networks including the medial frontoparietal network (default), lateral frontoparietal network (control), midcingulo-insular network (salience), and dorsal frontoparietal network (attention) are also discussed in the context of neuropsychiatric disorders. Several subtypes of basal forebrain neurons have been identified including basal forebrain parvalbumin-containing or somatostatin-containing neurons which can regulate cortical gamma band oscillations and DMN-like behaviors, and basal forebrain cholinergic neurons which might gate access to sensory information during reinforcement learning. In this review, we explore this evidence, discuss the clinical implications on neuropsychiatric disorders, and compare neuroanatomy in the human vs rodent DMN. Finally, we address technological advancements which could help provide a more complete understanding of modulation of DMN function and describe newly identified BF therapeutic targets that could potentially help restore DMN-associated functional deficits in patients with a variety of neuropsychiatric disorders.

Detecting the Inverted-U in fMRI Studies of Schizophrenia: A Comparison of Three Analysis Methods

OBJECTIVE

Cognitive tasks are used to probe neuronal activity during functional magnetic resonance imaging (fMRI) to detect signs of aberrant cognitive functioning in patients diagnosed with schizophrenia (SZ). However, nonlinear (inverted-U-shaped) associations between neuronal activity and task difficulty can lead to misinterpretation of group differences between patients and healthy comparison subjects (HCs). In this paper, we evaluated a novel method for correcting these misinterpretations based on conditional performance analysis.

METHOD

Participants included 25 HCs and 27 SZs who performed a working memory (WM) task (N-back) with 5 load conditions while undergoing fMRI. Neuronal activity was regressed onto: 1) task load (i.e., parametric task levels), 2) marginal task performance (i.e., performance averaged over all load conditions), or 3) conditional task performance (i.e., performance within each load condition).

RESULTS

In most regions of interest, conditional performance analysis uniquely revealed inverted-U-shaped neuronal activity in both SZs and HCs. After accounting for conditional performance differences between groups, we observed few difference in both the pattern and level of neuronal activity between SZs and HCs within regions that are classically associated with WM functioning (e.g., posterior dorsolateral prefrontal and parietal association cortices). However, SZs did show aberrant activity within the anterior dorsolateral prefrontal cortex.

CONCLUSIONS

Interpretations of differences in neuronal activity between groups, and of associations between neuronal activity and performance, should be considered within the context of task performance. Whether conditional performance-based differences reflect compensation, dedifferentiation, or other processes is not a question that is easily resolved by examining activation and performance data alone.

HIV infection is linked with reduced error-related default mode network suppression and poorer medication management abilities

OBJECTIVE

Brain activity linked with error processing has rarely been examined among persons living with HIV (PLWH) despite importance for monitoring and modifying behaviors that could lead to adverse health outcomes (e.g., medication non-adherence, drug use, risky sexual practices). Given that cannabis (CB) use is prevalent among PLWH and impacts error processing, we assessed the influence of HIV serostatus and chronic CB use on error-related brain activity while also considering associated implications for everyday functioning and clinically-relevant disease management behaviors.

METHODS

A sample of 109 participants, stratified into four groups by HIV and CB (HIV+/CB+, n = 32; HIV+/CB-, n = 27; HIV-/CB+, n = 28; HIV-/CB-, n = 22), underwent fMRI scanning while completing a modified Go/NoGo paradigm called the Error Awareness Task (EAT). Participants also completed a battery of well-validated instruments including a subjective report of everyday cognitive failures and an objective measure of medication management abilities.

RESULTS

Across all participants, we observed expected error-related anterior insula (aI) activation which correlated with better task performance (i.e., less errors) and, among HIV- participants, fewer self-reported cognitive failures. Regarding awareness, greater insula activation as well as greater posterior cingulate cortex (PCC) deactivation were notably linked with aware (vs. unaware) errors. Regarding group effects, unlike HIV- participants, PLWH displayed a lack of error-related deactivation in two default mode network (DMN) regions (i.e., PCC, medial prefrontal cortex [mPFC]). No CB main or interaction effects were detected. Across all participants, reduced error-related PCC deactivation correlated with reduced medication management abilities and PCC deactivation mediated the effect of HIV on such abilities. More lifetime CB use was linked with reduced error-related mPFC deactivation among HIV- participants and poorer medication management across CB users.

CONCLUSIONS

These results demonstrate that insufficient error-related DMN suppression linked with HIV infection, as well as chronic CB use among HIV- participants, has real-world consequences for medication management behaviors. We speculate that insufficient DMN suppression may reflect an inability to disengage task irrelevant mental operations, ultimately hindering error monitoring and behavior modification.

Abnormal Network Properties and Fiber Connections of DMN across Major Mental Disorders: A Probability Tracing and Graph Theory Study

The default mode network (DMN) is related to brain functions and its abnormalities were associated with mental disorders' pathophysiology. To further understand the common and distinct DMN alterations across disorders, we capitalized on the probability tracing method and graph theory to analyze the role of DMN across three major mental disorders. A total of 399 participants (156 schizophrenia [SCZ], 90 bipolar disorder [BP], 58 major depression disorder [MDD], and 95 healthy controls [HC]) completed magnetic resonance imaging (MRI)-scanning, clinical, and cognitive assessment. The MRI preprocessing of diffusion-tensor-imaging was conducted in FMRIB Software Library and probabilistic fiber tracking was applied by PANDA. This study had three main findings. First, patient groups showed significantly lower cluster coefficient in whole-brain compared with HC. SCZ showed significantly longer characteristic path compared with HC. Second, patient groups showed inter-group specificity in abnormalities of DMN connections. Third, SCZ was sensitive to left_medial_superior_frontal_gyrus (L_SFGmed)-right_anterior_cingulate_gyrus (R_ACG) connection relating to positive symptoms; left_ACG-right_ACG connection was the mania's antagonistic factor in BP. This trans-diagnostic study found disorder-specific structural abnormalities in the fiber connection of R_SFGmed-L_SFGmed-R_ACG_L_ACG within DMN, where SCZ showed more disconnections compared with other disorders. And these connections are diagnosis-specifically correlated to phenotypes. The current study may provide further evidence of shared and distinct endo-phenotypes across psychopathology.

Classification and Visualization of Chemotherapy-Induced Cognitive Impairment in Volumetric Convolutional Neural Networks

Breast cancer is the most common female cancer worldwide, and breast cancer accounts for 30% of female cancers. Of all the treatment modalities, breast cancer survivors who have undergone chemotherapy might complain about cognitive impairment during and after cancer treatment. This phenomenon, chemo-brain, is used to describe the alterations in cognitive functions after receiving systemic chemotherapy. Few reports detect the chemotherapy-induced cognitive impairment (CICI) by performing functional MRI (fMRI) and a deep learning analysis. In this study, we recruited 55 postchemotherapy breast cancer survivors (C+ group) and 65 healthy controls (HC group) and extracted mean fractional amplitudes of low-frequency fluctuations (mfALFF) from resting-state fMRI as our input feature. Two state-of-the-art deep learning architectures, ResNet-50 and DenseNet-121, were transformed to 3D, embedded with squeeze and excitation (SE) blocks and then trained to differentiate cerebral alterations based on the effect of chemotherapy. An integrated gradient was applied to visualize the pattern that was recognized by our model. The average performance of SE-ResNet-50 models was an accuracy of 80%, precision of 78% and recall of 70%; on the other hand, the SE-DenseNet-121 model reached identical results with an average of 80% accuracy, 86% precision and 80% recall. The regions with the greatest contributions highlighted by the integrated gradients algorithm for differentiating chemo-brain were the frontal, temporal, parietal and occipital lobe. These regions were consistent with other studies and strongly associated with the default mode and dorsal attention networks. We constructed two volumetric state-of-the-art models and visualized the patterns that are critical for identifying chemo-brains from normal brains. We hope that these results will be helpful in clinically tracking chemo-brain in the future.

Pharmaco-Magnetic Resonance as a Tool for Monitoring the Medication-Related Effects in the Brain May Provide Potential Biomarkers for Psychotic Disorders

The neurodegenerative and neurodevelopmental hypotheses represent the basic etiological framework for the origin of schizophrenia. Additionally, the dopamine hypothesis, adopted more than two decades ago, has repeatedly asserted the position of dopamine as a pathobiochemical substrate through the action of psychostimulants and neuroleptics on the mesolimbic and mesocortical systems, giving insight into the origin of positive and negative schizophrenic symptoms. Meanwhile, cognitive impairments in schizophrenia remain incompletely understood but are thought to be present during all stages of the disease, as well as in the prodromal, interictal and residual phases. On the other hand, observations on the effects of NMDA antagonists, such as ketamine and phencyclidine, reveal that hypoglutamatergic neurotransmission causes not only positive and negative but also cognitive schizophrenic symptoms. This review aims to summarize the different hypotheses about the origin of psychoses and to identify the optimal neuroimaging method that can serve to unite them in an integral etiological framework. We systematically searched Google scholar (with no concern to the date published) to identify studies investigating the etiology of schizophrenia, with a focus on impaired central neurotransmission. The complex interaction between the dopamine and glutamate neurotransmitter systems provides the long-needed etiological concept, which combines the neurodegenerative hypothesis with the hypothesis of impaired neurodevelopment in schizophrenia. Pharmaco-magnetic resonance imaging is a neuroimaging method that can provide a translation of scientific knowledge about the neural networks and the disruptions in and between different brain regions, into clinically applicable and effective therapeutic results in the management of severe psychotic disorders.

Emotional imagination of negative situations: Functional neuroimaging in anorexia and bulimia

Aim

The present study aims to extend the knowledge of the neural correlates of emotion processing in first episode subjects affected by anorexia nervosa (AN) or bulimia nervosa (BN). We applied an emotional distress paradigm targeting negative emotions thought to be relevant for interpersonal difficulties and therapeutic resistance mechanisms.

Methods

The current study applied to 44 female participants with newly diagnosed AN or BN and 20 matched controls a neuroimaging paradigm eliciting affective responses. The measurements also included an extensive assessment comprising clinical scales, neuropsychological tests, measures of emotion processing and empathy.

Results

AN and BN did not differ from controls in terms of emotional response, emotion matching, self-reported empathy and cognitive performance. However, eating disorder and psychopathological clinical scores, as well as alexithymia levels, were increased in AN and BN. On a neural level, no significant group differences emerged, even when focusing on a region of interest selected a priori: the amygdala. Some interesting findings put in relation the hippocampal activity with the level of Body Dissatisfaction of the participants, the relative importance of the key nodes for the common network in the decoding of different emotions (BN = right amygdala, AN = anterior cingulate area), and the qualitative profile of the deactivations.

Conclusions

Our data do not support the hypothesis that participants with AN or BN display reduced emotional responsiveness. However, peculiar characteristics in emotion processing could be associated to the three different groups. Therefore, relational difficulties in eating disorders, as well as therapeutic resistance, could be not secondary to a simple difficulty in feeling and identifying basic negative emotions in AN and BN participants.

Strategies to solve the reverse inference fallacy in future MRI studies of schizophrenia: a review

Few advances in schizophrenia research have been translated into clinical practice, despite 60 years of serum biomarkers studies and 50 years of genetic studies. During the last 30 years, neuroimaging studies on schizophrenia have gradually increased, partly due to the beautiful prospect that the pathophysiology of schizophrenia could be explained entirely by the Human Connectome Project (HCP). However, the fallacy of reverse inference has been a critical problem of the HCP. For this reason, there is a dire need for new strategies or research "bridges" to further schizophrenia at the biological level. To understand the importance of research "bridges," it is vital to examine the strengths and weaknesses of the recent literature. Hence, in this review, our team has summarized the recent literature (1995-2018) about magnetic resonance imaging (MRI) of schizophrenia in terms of regional and global structural and functional alterations. We have also provided a new proposal that may supplement the HCP for studying schizophrenia. As postulated, despite the vast number of MRI studies in schizophrenia, the lack of homogeneity between the studies, along with the relatedness of schizophrenia with other neurological disorders, has hindered the study of schizophrenia. In addition, the reverse inference cannot be used to diagnose schizophrenia, further limiting the clinical impact of findings from medical imaging studies. We believe that multidisciplinary technologies may be used to develop research "bridges" to further investigate schizophrenia at the single neuron or neuron cluster levels. We have postulated about future strategies for overcoming the current limitations and establishing the research "bridges," with an emphasis on multimodality imaging, molecular imaging, neuron cluster signals, single transmitter biomarkers, and nanotechnology. These research "bridges" may help solve the reverse inference fallacy and improve our understanding of schizophrenia for future studies.

Abnormal Large-Scale Network Activation Present in Bipolar Mania and Bipolar Depression Under Resting State

Introduction: Previous studies have primarily focused on the neuropathological mechanisms of the emotional circuit present in bipolar mania and bipolar depression. Recent studies applying resting-state functional magnetic resonance imaging (fMRI) have raise the possibility of examining brain-wide networks abnormality between the two oppositional emotion states, thus this study aimed to characterize the different functional architecture represented in mania and depression by employing group-independent component analysis (gICA). Materials and Methods: Forty-one bipolar depressive patients, 20 bipolar manic patients, and 40 healthy controls (HCs) were recruited and received resting-state fMRI scans. Group-independent component analysis was applied to the brain network functional connectivity analysis. Then, we calculated the correlation between the value of between-group differences and clinical variables. Results: Group-independent component analysis identified 15 components in all subjects, and ANOVA showed that functional connectivity (FC) differed significantly in the default mode network, central executive network, and frontoparietal network across the three groups. Further post-hoc t-tests showed a gradient descent of activity-depression > HC > mania-in all three networks, with the differences between depression and HCs, as well as between depression and mania, surviving after family wise error (FWE) correction. Moreover, central executive network and frontoparietal network activities were positively correlated with Hamilton depression rating scale (HAMD) scores and negatively correlated with Young manic rating scale (YMRS) scores. Conclusions: Three brain networks heighten activity in depression, but not mania; and the discrepancy regions mainly located in prefrontal, which may imply that the differences in cognition and emotion between the two states is associated with top-down regulation in task-independent networks.

Resting-state hyperconnectivity within the default mode network impedes the ability to initiate cognitive performance in first-episode schizophrenia patients

Among multiple cognitive impairments present in schizophrenia, a decline in fast information processing is one of the most severe neuropsychological deficit. Reduced ability to efficiently launch a coherent cognitive activity might be a significant factor contributing to poor results in time-limited tasks obtained by schizophrenia patients. The aim of this study was to identify neurophysiological predictors of expected cognitive initiation failures in a group of first-episode schizophrenia individuals (SZ). To evaluate the effectiveness of initiation, a dynamic analysis of design fluency test was applied, assessing to what extent the productivity was focused within the first interval of the performance, what is a typical way healthy subjects execute this task. Resting-state EEG recordings were obtained from SZ patients (n = 34) and controls (n = 30) to examine functional connectivity between 84 intra-cortical current sources determined by eLORETA (exact low-resolution brain electromagnetic tomography) for six conventionally analyzed frequencies. The nonparametric randomization approach was used to identify hypo- and hyper-connections, i.e. synchronizations significantly differentiating the studied samples in terms of connectivity strength. Generally, SZ patients obtained poor outcomes in fluency test and dynamic analysis of performance confirmed the presence of initiation deficit in clinical sample, which was a single factor explaining the intergroup difference regarding the entire task. In the majority of frequencies, the arrangement of synchronizations in SZ group was dominated by hypo-connections, except for the theta band, in which the strength of synchronizations between posterior cingulate cortex, cuneus and precuneus was significantly higher for SZ group. These theta-band hyper-connections turned out to be significant predictors of cognitive initiation failure in the clinical sample. Additionally, theta hyper-connections correlated negatively with the total number of unique designs generated by patients, however, the strength of this correlation was weaker than regarding initiation index. The results of this study suggest that baseline hyperconnectivity within the posterior hub of the Default Mode Network, containing posterior cingulate gyrus and precuneus, might disturb effective cognitive outcome, not only by interfering with task-positive functional networks but also by delaying the starting phase of performance, which might be specifically deleterious for the execution of time-limited tests.

Altered Default Mode Network and Salience Network Functional Connectivity in Patients with Generalized Anxiety Disorders: An ICA-Based Resting-State fMRI Study

This study aimed to explore the role of the default mode network (DMN) and salience network (SN) in the assessment of pathophysiology of generalized anxiety disorder (GAD) through analyzing the characteristics of internal function connectivity (FC) and to investigate the relationship of FC with Hamilton anxiety (HAMA) scale scores in untreated GAD patients during a resting-state functional magnetic resonance imaging (rs-fMRI). Rs-fMRI and HAMA scale scoring were performed in 51 GAD patients (31 GAD patients with liver stagnation transforming into fire type and 20 GAD patients with stagnation of liver-Qi syndrome type) and 20 healthy controls. Spearman correlation analysis was performed to assess the association between HAMA scores and abnormal brain FC. Compared with healthy controls, the FC of the right medial prefrontal gyrus of the DMN and the right superior temporal gyrus of the SN increased significantly in the GAD patients (P < 0.001). However, the FC of the left middle frontal gyrus and bilateral medial superior frontal gyrus of the SN reduced significantly in the GAD patients with stagnation of liver-Qi syndrome type as compared with healthy controls and GAD patients with liver stagnation transforming into fire type (P < 0.001). There was no relationship between abnormal brain FC and HAMA scores. In conclusion, the FC of the DMN and SN may be abnormal in the GAD patients at the resting state. The aberrant FC of some crucial brain regions of these networks may contribute to the pathophysiology of GAD.

Morphological Profiling of Schizophrenia: Cluster Analysis of MRI-Based Cortical Thickness Data

The diagnosis of schizophrenia is thought to embrace several distinct subgroups. The manifold entities in a single clinical patient group increase the variance of biological measures, deflate the group-level estimates of causal factors, and mask the presence of treatment effects. However, reliable neurobiological boundaries to differentiate these subgroups remain elusive. Since cortical thinning is a well-established feature in schizophrenia, we investigated if individuals (patients and healthy controls) with similar patterns of regional cortical thickness form naturally occurring morphological subtypes. K-means algorithm clustering was applied to regional cortical thickness values obtained from 256 structural MRI scans (179 patients with schizophrenia and 77 healthy controls [HCs]). GAP statistics revealed three clusters with distinct regional thickness patterns. The specific patterns of cortical thinning, clinical characteristics, and cognitive function of each clustered subgroup were assessed. The three clusters based on thickness patterns comprised of a morphologically impoverished subgroup (25% patients, 1% HCs), an intermediate subgroup (47% patients, 46% HCs), and an intact subgroup (28% patients, 53% HCs). The differences of clinical features among three clusters pertained to age-of-onset, N-back performance, duration exposure to treatment, total burden of positive symptoms, and severity of delusions. Particularly, the morphologically impoverished group had deficits in N-back performance and less severe positive symptom burden. The data-driven neuroimaging approach illustrates the occurrence of morphologically separable subgroups in schizophrenia, with distinct clinical characteristics. We infer that the anatomical heterogeneity of schizophrenia arises from both pathological deviance and physiological variance. We advocate using MRI-guided stratification for clinical trials as well as case-control investigations in schizophrenia.

Abnormal default-mode network homogeneity and its correlations with neurocognitive deficits in drug-naive first-episode adolescent-onset schizophrenia

The default mode network (DMN), is one of the most popularly employed resting-state networks applied in schizophrenia (SCZ) research. However, the homogeneity of this network in adolescent-onset SCZ (AOS) remains unknown. This study aims to use network homogeneity (NH) to explore the functional connectivity in the DMN of AOS patients. Resting-state functional magnetic resonance imaging scans were used to study 48 drug-naïve, first-episode AOS patients and 31 healthy age, gender, and education matched control. An automatic NH approach was employed to analyze the imaging dataset. Our results revealed that the patients had significantly higher NH values in the left medial prefrontal cortex (MPFC), and significantly lower values in the bilateral posterior cingulate cortex/precuneus (PCC/PCu) than those in healthy controls. We performed the receiver operating characteristic curve analysis to show that NH values of the left superior MPFC might be regarded as a potential marker in helping to identify patients. In addition, negative associations were found regarding abnormal values of NH in the left PCC/PCu as well as in the Maze and Stroop color-word tests in patients. The outcomes showed abnormal NH values in the DMN of drug-naïve, first-episode AOS suggesting specific functions of the DMN in the pathophysiology of SCZ.

Task-evoked Negative BOLD Response and Functional Connectivity in the Default Mode Network are Representative of Two Overlapping but Separate Neurophysiological Processes

The topography of the default mode network (DMN) can be obtained with one of two different functional magnetic resonance imaging (fMRI) methods: either from the spontaneous but organized synchrony of the low-frequency fluctuations in resting-state fMRI (rs-fMRI), known as "functional connectivity", or from the consistent and robust deactivations in task-based fMRI (tb-fMRI), here referred to as the "negative BOLD response" (NBR). These two methods are fundamentally different, but their results are often used interchangeably to describe the brain's resting-state, baseline, or intrinsic activity. While the DMN was initially defined by consistent task-based decreases in blood flow in a set of specific brain regions using PET imaging, recently nearly all studies on the DMN employ functional connectivity in rs-fMRI. In this study, we first show the high level of spatial overlap between NBR and functional connectivity of the DMN extracted from the same tb-fMRI scan; then, we demonstrate that the NBR in putative DMN regions can be significantly altered without causing any change in their overlapping functional connectivity. Furthermore, we present evidence that in the DMN, the NBR is more closely related to task performance than the functional connectivity. We conclude that the NBR and functional connectivity of the DMN reflect two separate but overlapping neurophysiological processes, and thus should be differentiated in studies investigating brain-behavior relationships in both healthy and diseased populations. Our findings further raise the possibility that the macro-scale networks of the human brain might internally exhibit a hierarchical functional architecture.

Increased and Decreased Superficial White Matter Structural Connectivity in Schizophrenia and Bipolar Disorder

Schizophrenia (SZ) and bipolar disorder (BD) are often conceptualized as "disconnection syndromes," with substantial evidence of abnormalities in deep white matter tracts, forming the substrates of long-range connectivity, seen in both disorders. However, the study of superficial white matter (SWM) U-shaped short-range tracts remained challenging until recently, although findings from postmortem studies suggest they are likely integral components of SZ and BD neuropathology. This diffusion weighted imaging (DWI) study aimed to investigate SWM microstructure in vivo in both SZ and BD for the first time. We performed whole brain tractography in 31 people with SZ, 32 people with BD and 54 controls using BrainVISA and Connectomist 2.0. Segmentation and labeling of SWM tracts were performed using a novel, comprehensive U-fiber atlas. Analysis of covariances yielded significant generalized fractional anisotropy (gFA) differences for 17 SWM bundles in frontal, parietal, and temporal cortices. Post hoc analyses showed gFA reductions in both patient groups as compared with controls in bundles connecting regions involved in language processing, mood regulation, working memory, and motor function (pars opercularis, insula, anterior cingulate, precentral gyrus). We also found increased gFA in SZ patients in areas overlapping the default mode network (inferior parietal, middle temporal, precuneus), supporting functional hyperconnectivity of this network evidenced in SZ. We thus illustrate that short U-fibers are vulnerable to the pathological processes in major psychiatric illnesses, encouraging improved understanding of their anatomy and function.

Salience-Default Mode Functional Network Connectivity Linked to Positive and Negative Symptoms of Schizophrenia

Schizophrenia is a complex, debilitating mental disorder characterized by wide-ranging symptoms including delusions, hallucinations (so-called positive symptoms), and impaired motor and speech/language production (so-called negative symptoms). Salience-monitoring theorists propose that abnormal functional communication between the salience network (SN) and default mode network (DMN) begets positive and negative symptoms of schizophrenia, yet prior studies have predominately reported links between disrupted SN/DMN functional communication and positive symptoms. It remains unclear whether disrupted SN/DMN functional communication explains (1) solely positive symptoms or (2) both positive and negative symptoms of schizophrenia. To address this question, we incorporate time-lag-shifted functional network connectivity (FNC) analyses that explored coherence of the resting-state functional magnetic resonance imaging signal of 3 networks (anterior DMN, posterior DMN, and SN) with fixed time lags introduced between network time series (1 TR = 2 s; 2 TR = 4 s). Multivariate linear regression analysis revealed that severity of disordered thought and attentional deficits were negatively associated with 2 TR-shifted FNC between anterior DMN and posterior DMN. Meanwhile, severity of flat affect and bizarre behavior were positively associated with 1 TR-shifted FNC between anterior DMN and SN. These results provide support favoring the hypothesis that lagged SN/DMN functional communication is associated with both positive and negative symptoms of schizophrenia.

Cognitive Profiles and Functional Connectivity in First-Episode Schizophrenia Spectrum Disorders - Linking Behavioral and Neuronal Data

The character of cognitive deficit in schizophrenia is not clear due to the heterogeneity in research results. In heterogeneous conditions, the cluster solution allows the classification of individuals based on profiles. Our aim was to examine the cognitive profiles of first-episode schizophrenia spectrum disorder (FES) subjects based on cluster analysis, and to correlate these profiles with clinical variables and resting state brain connectivity, as measured with magnetic resonance imaging. A total of 67 FES subjects were assessed with a neuropsychological test battery and on clinical variables. The results of the cognitive domains were cluster analyzed. In addition, functional connectivity was calculated using ROI-to-ROI analysis with four groups: Three groups were defined based on the cluster analysis of cognitive performance and a control group with a normal cognitive performance. The connectivity was compared between the patient clusters and controls. We found different cognitive profiles based on three clusters: Cluster 1: decline in the attention, working memory/flexibility, and verbal memory domains. Cluster 2: decline in the verbal memory domain and above average performance in the attention domain. Cluster 3: generalized and severe deficit in all of the cognitive domains. FES diagnoses were distributed among all of the clusters. Cluster comparisons in neural connectivity also showed differences between the groups. Cluster 1 showed both hyperconnectivity between the cerebellum and precentral gyrus, the salience network (SN) (insula cortex), and fronto-parietal network (FPN) as well as between the PreCG and SN (insula cortex) and hypoconnectivity between the default mode network (DMN) and seeds of SN [insula and supramarginal gyrus (SMG)]; Cluster 2 showed hyperconnectivity between the DMN and cerebellum, SN (insula) and precentral gyrus, and FPN and IFG; Cluster 3 showed hypoconnectivity between the DMN and SN (insula) and SN (SMG) and pallidum. The cluster solution confirms the prevalence of a cognitive decline with different patterns of cognitive performance, and different levels of severity in FES. Moreover, separate behavioral cognitive subsets can be linked to patterns of brain functional connectivity.

Anterior Cingulate Glutamate and GABA Associations on Functional Connectivity in Schizophrenia

BACKGROUND

The underlying neurobiological mechanism for abnormal functional connectivity in schizophrenia (SCZ) remains unknown. This project investigated whether glutamate and GABA, 2 metabolites that contribute to excitatory and inhibitory functions, may influence functional connectivity in SCZ.

METHODS

Resting-state functional magnetic resonance imaging and proton magnetic resonance spectroscopy were acquired from 58 SCZ patients and 61 healthy controls (HC). Seed-based connectivity maps were extracted between the anterior cingulate cortex (ACC) spectroscopic voxel and all other brain voxels. Magnetic resonance spectroscopy (MRS) spectra were processed to quantify glutamate and GABA levels. Regression analysis was performed to describe relationships between functional connectivity and glutamate and GABA levels.

RESULTS

Reduced ACC functional connectivity in SCZ was found in regions associated with several neural networks including the default mode network (DMN) compared to HC. In the HC, positive correlations were found between glutamate and both ACC-right inferior frontal gyrus functional connectivity and ACC-bilateral superior temporal gyrus functional connectivity. A negative correlation between GABA and ACC-left posterior cingulate functional connectivity was also observed in HC. These same relationships were not statistically significant in SCZ.

CONCLUSIONS

The present investigation is one of the first studies to examine links between functional connectivity and glutamate and GABA levels in SCZ. Results indicate that glutamate and GABA play an important role in the functional connectivity modulation in the healthy brain. The absence of glutamate and GABA correlations in areas where SCZ showed significantly reduced functional connectivity may suggest that this chemical-functional relationship is disrupted in SCZ.

Schizophrenia-related abnormalities in the triple network: a meta-analysis of working memory studies

Previous meta-analyses found abnormal brain activations in schizophrenia patients compared with normal controls when performing working memory tasks. Although most studies focused on dysfunction of the working memory activation network in schizophrenia patients, deactivation abnormalities of the working memory in the default mode network have also been reported in schizophrenia but have received less attention. Our goal was to discover whether deactivation abnormalities can also be consistently found in schizophrenia during working memory tasks and, further, to consider both activation and deactivation abnormalities. Fifty-two English language peer-reviewed studies were included in this meta-analysis. Compared with normal controls, the schizophrenia patients showed activation dysfunction of the bilateral dorsolateral prefrontal cortex and posterior parietal cortex as well as the anterior insula, anterior cingulate cortex, and supplementary motor area, which are core nodes of the central executive and salience network. In addition to dysfunction of the activation networks, the patients showed deactivation abnormalities in the ventral medial prefrontal cortex and posterior cingulate cortex, which are core nodes of the default mode network. These results suggest that both activation and deactivation abnormalities exist in schizophrenia patients and that these abnormalities should both be considered when investigating the pathophysiological mechanism of schizophrenia.

Resting-State Default Mode Network Related Functional Connectivity Is Associated With Sustained Attention Deficits in Schizophrenia and Obsessive-Compulsive Disorder

Background: Previous studies have indicated the resting-state default mode network (DMN) related connectivity serving as predictor of sustained attention performance in healthy people. Interestingly, sustained attention deficits as well as DMN-involved functional connectivity (FC) alterations are common in both patients with schizophrenia (SCZ) and with obsessive-compulsive disorder (OCD). Thus, the present study was designed to investigate whether the DMN related resting-state connectivity alterations in these two psychiatric disorders were neural correlates of their sustained attention impairments.

Methods: The study included 17 SCZ patients, 35 OCD patients and 36 healthy controls (HCs). Sustained attention to response task was adopted to assess the sustained attention. Resting-state scan was administrated and seed-based whole-brain FC analyses were performed with seeds located in classical DMN regions including bilateral medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC).

Results: Both SCZ and OCD patients had poorer sustained attention than HCs. Sustained attention deficits in OCD was negatively correlated with their impaired FC of right mPFC-left superior frontal gyrus (SFG) within DMN, and that in SCZ was significantly correlated with their altered FC of left mPFC-bilateral anterior cingulate cortex (ACC) which indicated interaction between DMN and salience network. In addition, the FC between left mPFC and right parietal lobe indicating the interaction between DMN and frontal-parietal network was correlated with sustained attention in both SCZ and OCD.

Conclusion: These findings suggest the importance of DMN-involved connectivity, both within and between networks in underlying sustained attention deficits in OCD and SCZ. Results further support the potential of resting-state FC in complementing information for cognitive deficits in psychiatric disorders.

Comparison of EEG microstates with resting state fMRI and FDG-PET measures in the default mode network via simultaneously recorded trimodal (PET/MR/EEG) data

Simultaneous trimodal positron emission tomography/magnetic resonance imaging/electroencephalography (PET/MRI/EEG) resting state (rs) brain data were acquired from 10 healthy male volunteers. The rs-functional MRI (fMRI) metrics, such as regional homogeneity (ReHo), degree centrality (DC) and fractional amplitude of low-frequency fluctuations (fALFFs), as well as 2-[18F]fluoro-2-desoxy-d-glucose (FDG)-PET standardised uptake value (SUV), were calculated and the measures were extracted from the default mode network (DMN) regions of the brain. Similarly, four microstates for each subject, showing the diverse functional states of the whole brain via topographical variations due to global field power (GFP), were estimated from artefact-corrected EEG signals. In this exploratory analysis, the GFP of microstates was nonparametrically compared to rs-fMRI metrics and FDG-PET SUV measured in the DMN of the brain. The rs-fMRI metrics (ReHO, fALFF) and FDG-PET SUV did not show any significant correlations with any of the microstates. The DC metric showed a significant positive correlation with microstate C (r_s  = 0.73, p = .01). FDG-PET SUVs indicate a trend for a negative correlation with microstates A, B and C. The positive correlation of microstate C with DC metrics suggests a functional relationship between cortical hubs in the frontal and occipital lobes. The results of this study suggest further exploration of this method in a larger sample and in patients with neuropsychiatric disorders. The aim of this exploratory pilot study is to lay the foundation for the development of such multimodal measures to be applied as biomarkers for diagnosis, disease staging, treatment response and monitoring of neuropsychiatric disorders.

Associations Among Suicidal Ideation, White Matter Integrity and Cognitive Deficit in First-Episode Schizophrenia

Objective: The study was aimed to investigate the possible associations among suicidal ideation, brain white matter (WM) integrity and cognitive deficit in first-episode schizophrenia (FES) using diffusion tensor imaging. Methods: The sample contained 18 FES patients with suicidal ideation (SI+), 45 FES patients without suicidal ideation (SI-) and 44 healthy controls. The Calgary Depression Scale for Schizophrenia was used to measure the suicidal ideation and depression symptoms. The whole brain WM integrity and three domains of cognitive function: working memory, verbal comprehension as well as processing speed were compared between the three groups. Results: Compared with SI-, SI+ showed preserved WM integrity as indicated by significantly higher factional anisotropy (FA) or lower mean diffusivity (MD) in multiple WM tracts, and higher FA coupled with lower MD in bilateral posterior corona radiata. Compared with SI-, SI+ were more depressed and had less cognitive deficit in working memory and verbal comprehension. The fiber tracts in bilateral posterior corona radiata connect to the precuneus as shown by probabilistic tractography, and their WM integrity disruptions were found to be positively associated with the cognitive deficits in the FES patients. Discussion: Preserved WM integrity may be a risk factor for suicidal ideation in FES patients. One possible explanation is that it contributes to preserved cognitive function, especially in working memory and verbal comprehension, which may be associated with greater insight and could lead to increased depression and suicidal ideation. The posterior corona radiata and the precuneus may be linked to the related biological processes.

Predicting Response to Repetitive Transcranial Magnetic Stimulation in Patients With Schizophrenia Using Structural Magnetic Resonance Imaging: A Multisite Machine Learning Analysis

BACKGROUND

The variability of responses to plasticity-inducing repetitive transcranial magnetic stimulation (rTMS) challenges its successful application in psychiatric care. No objective means currently exists to individually predict the patients' response to rTMS.

METHODS

We used machine learning to develop and validate such tools using the pre-treatment structural Magnetic Resonance Images (sMRI) of 92 patients with schizophrenia enrolled in the multisite RESIS trial (http://clinicaltrials.gov, NCT00783120): patients were randomized to either active (N = 45) or sham (N = 47) 10-Hz rTMS applied to the left dorsolateral prefrontal cortex 5 days per week for 21 days. The prediction target was nonresponse vs response defined by a ≥20% pre-post Positive and Negative Syndrome Scale (PANSS) negative score reduction.

RESULTS

Our models predicted this endpoint with a cross-validated balanced accuracy (BAC) of 85% (nonresponse/response: 79%/90%) in patients receiving active rTMS, but only with 51% (48%/55%) in the sham-treated sample. Leave-site-out cross-validation demonstrated cross-site generalizability of the active rTMS predictor despite smaller training samples (BAC: 71%). The predictive pre-treatment pattern involved gray matter density reductions in prefrontal, insular, medio-temporal, and cerebellar cortices, and increments in parietal and thalamic structures. The low BAC of 58% produced by the active rTMS predictor in sham-treated patients, as well as its poor performance in predicting positive symptom courses supported the therapeutic specificity of this brain pattern.

CONCLUSIONS

Individual responses to active rTMS in patients with predominant negative schizophrenia may be accurately predicted using structural neuromarkers. Further multisite studies are needed to externally validate the proposed treatment stratifier and develop more personalized and biologically informed rTMS interventions.

Directed functional connectivity using dynamic graphical models

There are a growing number of neuroimaging methods that model spatio-temporal patterns of brain activity to allow more meaningful characterizations of brain networks. This paper proposes dynamic graphical models (DGMs) for dynamic, directed functional connectivity. DGMs are a multivariate graphical model with time-varying coefficients that describe instantaneous directed relationships between nodes. A further benefit of DGMs is that networks may contain loops and that large networks can be estimated. We use network simulations and human resting-state fMRI (N = 500) to investigate the validity and reliability of the estimated networks. We simulate systematic lags of the hemodynamic response at different brain regions to investigate how these lags potentially bias directionality estimates. In the presence of such lag confounds (0.4-0.8 s offset between connected nodes), our method has a sensitivity of 72%-77% to detect the true direction. Stronger lag confounds have reduced sensitivity, but do not increase false positives (i.e., directionality estimates of the opposite direction). In human resting-state fMRI, the default mode network has consistent influence on the cerebellar, the limbic and the auditory/temporal networks. We also show a consistent reciprocal relationship between the visual medial and visual lateral network. Finally, we apply the method in a small mouse fMRI sample and discover a highly plausible relationship between areas in the hippocampus feeding into the cingulate cortex. We provide a computationally efficient implementation of DGM as a free software package for R.

Structural and functional alterations in the brain during working memory in medication-naïve patients at clinical high-risk for psychosis

Several previous studies suggest that clinical high risk for psychosis (CHR) is associated with prefrontal functional abnormalities and more widespread reduced grey matter in prefrontal, temporal and parietal areas. We investigated neural correlates to CHR in medication-naïve patients. 41 CHR patients and 37 healthy controls were examined with 1.5 Tesla MRI, yielding functional scans while performing an N-back task and structural T1-weighted brain images. Functional and structural data underwent automated preprocessing steps in SPM and Freesurfer, correspondingly. The groups were compared employing mass-univariate strategy within the generalized linear modelling framework. CHR demonstrated reduced suppression of the medial temporal lobe (MTL) regions during n-back task. We also found that, consistent with previous findings, CHR subjects demonstrated thinning in prefrontal, cingulate, insular and inferior temporal areas, as well as reduced hippocampal volumes. The present findings add to the growing evidence of specific structural and functional abnormalities in the brain as potential neuroimaging markers of psychosis vulnerability.

Polymorphism in schizophrenia risk gene MIR137 is associated with the posterior cingulate Cortex's activation and functional and structural connectivity in healthy controls

MIR137 gene has been repeatedly reported as a schizophrenia risk gene in genome-wide association studies (GWAS). A polymorphism (rs1625579) at the MIR137 gene has been associated with both neural activation and behavioral performance during a working memory task. This study examined MIR137's associations with task-related (N-back working memory) fMRI, resting state fMRI, and diffusion tensor images (DTI) data in 177 healthy adults. We found less deactivation of the PCC in risk allele homozygotes (TT) as compared to the GT heterozygotes (cluster size = 630 voxels, cluster level P_FWE < 0.001) during the N-back task, which replicated previous findings. Using the identified cluster within the PCC as the seed, we further found decreased functional connectivity between the PCC and the anterior cingulate cortex and its adjacent medial prefrontal cortex (ACC/MPFC) in risk allele homozygotes during both resting state (cluster size = 427 voxels, cluster level P_FWE = 0.001) and the N-back task (cluster size = 73 voxels, cluster level P_FWE = 0.05). Finally, an analysis of our DTI data showed decreased white matter integrity of the posterior cingulum in risk allele homozygotes (cluster size = 214 voxels, cluster level P_FWE = 0.03). Taken together, rs1625579 seems to play an important role in both functional and structural connectivity between the PCC and the ACC/MPFC, which may serve as the brain mechanisms for the link between rs1625579 and schizophrenia.

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This study replicated the association between the risk allele of rs1625579 and altered activations at the PCC.

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This study found decreased functional connectivity between the PCC and the ACC/MPFC in the risk allele homozygotes.

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This study found decreased FA value in the posterior cingulum in the risk allele homozygotes.

Gray matter morphological anomalies in the cerebellar vermis in first-episode schizophrenia patients with cognitive deficits

BACKGROUND

Cognitive deficits are a core feature of early schizophrenia. However, the pathological foundations underlying cognitive deficits are still unknown. The present study examined the association between gray matter density and cognitive deficits in first-episode schizophrenia.

METHOD

Structural magnetic resonance imaging of the brain was performed in 34 first-episode schizophrenia patients and 21 healthy controls. Patients were divided into two subgroups according to working memory task performance. The three groups were well matched for age, gender, and education, and the two patient groups were also further matched for diagnosis, duration of illness, and antipsychotic treatment. Voxel-based morphometric analysis was performed to estimate changes in gray matter density in first-episode schizophrenia patients with cognitive deficits. The relationships between gray matter density and clinical outcomes were explored.

RESULTS

Patients with cognitive deficits were found to have reduced gray matter density in the vermis and tonsil of cerebellum compared with patients without cognitive deficits and healthy controls, decreased gray matter density in left supplementary motor area, bilateral precentral gyrus compared with patients without cognitive deficits. Classifier results showed GMD in cerebellar vermis tonsil cluster could differentiate SZ-CD from controls, left supplementary motor area cluster could differentiate SZ-CD from SZ-NCD. Gray matter density values of the cerebellar vermis cluster in patients groups were positively correlated with cognitive severity.

CONCLUSIONS

Decreased gray matter density in the vermis and tonsil of cerebellum may underlie early psychosis and serve as a candidate biomarker for schizophrenia with cognitive deficits.

Altered Brain Functional Connectivity in Betel Quid-Dependent Chewers

BACKGROUND

Betel quid (BQ) is a common psychoactive substance worldwide with particularly high usage in many Asian countries. This study aimed to explore the effect of BQ use on functional connectivity by comparing global functional brain networks and their subset between BQ chewers and healthy controls (HCs).

METHODS

Resting-state functional magnetic resonance imaging (fMRI) was obtained from 24 betel quid-dependent (BQD) male chewers and 27 healthy male individuals on a 3.0T scanner. We used independent component analysis (ICA) to determine components that represent the brain's functional networks and their spatial aspects of functional connectivity. Two sample t-tests were used to identify the functional connectivity differences in each network between these two groups.

RESULTS

Seventeen networks were identified by ICA. Nine of them showed connectivity differences between BQD and HCs (two sample t-tests, p < 0.001 uncorrected). We found increased functional connectivity in the orbitofrontal, bilateral frontoparietal, frontotemporal, occipital/parietal, frontotemporal/cerebellum, and temporal/limbic networks, and decreased connectivity in the parietal and medial frontal/anterior cingulate networks in the BQD compared to the HCs. The betel quid dependence scale scores were positively related to the increased functional connectivity in the orbitofrontal (r = 0.39, p = 0.03) while negatively related to the decreased functional connectivity in medial frontal/anterior cingulate networks (r = -0.35, p = 0.02).

DISCUSSION

Our findings provide further evidence that BQ chewing may lead to brain functional connectivity changes, which may play a key role in the psychological and physiological effects of BQ.

Alterations of Brain Functional Architecture Associated with Psychopathic Traits in Male Adolescents with Conduct Disorder

Psychopathic traits of conduct disorder (CD) have a core callous-unemotional (CU) component and an impulsive-antisocial component. Previous task-driven fMRI studies have suggested that psychopathic traits are associated with dysfunction of several brain areas involved in different cognitive functions (e.g., empathy, reward, and response inhibition etc.), but the relationship between psychopathic traits and intrinsic brain functional architecture has not yet been explored in CD. Using a holistic brain-wide functional connectivity analysis, this study delineated the alterations in brain functional networks in patients with conduct disorder. Compared with matched healthy controls, we found decreased anti-synchronization between the fronto-parietal network (FPN) and default mode network (DMN), and increased intra-network synchronization within the frontothalamic-basal ganglia, right frontoparietal, and temporal/limbic/visual networks in CD patients. Correlation analysis showed that the weakened FPN-DMN interaction was associated with CU traits, while the heightened intra-network functional connectivity was related to impulsivity traits in CD patients. Our findings suggest that decoupling of cognitive control (FPN) with social understanding of others (DMN) is associated with the CU traits, and hyper-functions of the reward and motor inhibition systems elevate impulsiveness in CD.

Patterns of Default Mode Network Deactivation in Obsessive Compulsive Disorder

The objective of the present study was to research the patterns of Default Mode Network (DMN) deactivation in Obsessive Compulsive Disorder (OCD) in the transition between a resting and a non-rest emotional condition. Twenty-seven participants, 15 diagnosed with OCD and 12 healthy controls (HC), underwent a functional neuroimaging paradigm in which DMN brain activation in a resting condition was contrasted with activity during a non-rest condition consisting in the presentation of emotionally pleasant and unpleasant images. Results showed that HC, when compared with OCD, had a significant deactivation in two anterior nodes of the DMN (medial frontal and superior frontal) in the non-rest pleasant stimuli condition. Additional analysis for the whole brain, contrasting the resting condition with all the non-rest conditions grouped together, showed that, compared with OCD, HC had a significantly deactivation of a widespread brain network (superior frontal, insula, middle and superior temporal, putamen, lingual, cuneus, and cerebellum). Concluding, the present study found that OCD patients had difficulties with the deactivation of DMN even when the non-rest condition includes the presentation of emotional provoking stimuli, particularly evident for images with pleasant content.

Resting-State Functional Connectivity in the Human Connectome Project: Current Status and Relevance to Understanding Psychopathology

A key tenet of modern psychiatry is that psychiatric disorders arise from abnormalities in brain circuits that support human behavior. Our ability to examine hypotheses around circuit-level abnormalities in psychiatric disorders has been made possible by advances in human neuroimaging technologies. These advances have provided the basis for recent efforts to develop a more complex understanding of the function of brain circuits in health and of their relationship to behavior-providing, in turn, a foundation for our understanding of how disruptions in such circuits contribute to the development of psychiatric disorders. This review focuses on the use of resting-state functional connectivity MRI to assess brain circuits, on the advances generated by the Human Connectome Project, and on how these advances potentially contribute to understanding neural circuit dysfunction in psychopathology. The review gives particular attention to the methods developed by the Human Connectome Project that may be especially relevant to studies of psychopathology; it outlines some of the key findings about what constitutes a brain region; and it highlights new information about the nature and stability of brain circuits. Some of the Human Connectome Project's new findings particularly relevant to psychopathology-about neural circuits and their relationships to behavior-are also presented. The review ends by discussing the extension of Human Connectome Project methods across the lifespan and into manifest illness. Potential treatment implications are also considered.