Utility of Washington Early Recognition Center self-report screening questionnaires in the assessment of patients with schizophrenia and bipolar disorder

Early identification and treatment are associated with improved outcomes in bipolar disorder (BPD) and schizophrenia (SCZ). Screening for the presence of these disorders usually involves time-intensive interviews that may not be practical in settings where mental health providers are limited. Thus, individuals at earlier stages of illness are often not identified. The Washington Early Recognition Center Affectivity and Psychosis (WERCAP) screen is a self-report questionnaire originally developed to identify clinical risk for developing bipolar or psychotic disorders. The goal of the current study was to investigate the utility of the WERCAP Screen and two complementary questionnaires, the WERC Stress Screen and the WERC Substance Screen, in identifying individuals with established SCZ or BPD. Participants consisted of 35 BPD and 34 SCZ patients, as well as 32 controls (CON), aged 18–30 years. Univariate analyses were used to test for score differences between groups. Logistic regression and receiver operating characteristic (ROC) curves were used to identify diagnostic predictors. Significant group differences were found for the psychosis section of the WERCAP (pWERCAP; p < 0.001), affective section of the WERCAP (aWERCAP; p = 0.001), and stress severity (p = 0.027). No significant group differences were found in the rates of substance use as measured by the WERC Substance Screen (p = 0.267). Only the aWERCAP and pWERCAP scores were useful predictors of diagnostic category. ROC curve analysis showed the optimal cut point on the aWERCAP to identify BPD among our participant groups was a score of >20 [area under the curve (AUC): 0.87; sensitivity: 0.91; specificity: 0.71], while that for the pWERCAP to identify SCZ was a score of >13 (AUC: 0.89; sensitivity: 0.88; specificity: 0.82). These results indicate that the WERCAP Screen may be useful in screening individuals for BPD and SCZ and that identifying stress and substance-use severity can be rapidly done using self-report questionnaires. Larger studies in undiagnosed individuals will be needed to test the WERCAP Screen’s ability to identify mania or psychosis in the community

Functional Connectivity of Cognitive Brain Networks in Schizophrenia during a Working Memory Task

Task-based connectivity studies facilitate the understanding of how the brain functions during cognition, which is commonly impaired in schizophrenia (SZ). Our aim was to investigate functional connectivity during a working memory task in SZ. We hypothesized that the task-negative (default mode) network and the cognitive control (frontoparietal) network would show dysconnectivity. Twenty-five SZ patient and 31 healthy control scans were collected using the customized 3T Siemens Skyra MRI scanner, previously used to collect data for the Human Connectome Project. Blood oxygen level dependent signal during the 0-back and 2-back conditions were extracted within a network-based parcelation scheme. Average functional connectivity was assessed within five brain networks: frontoparietal (FPN), default mode (DMN), cingulo-opercular (CON), dorsal attention (DAN), and ventral attention network; as well as between the DMN or FPN and other networks. For within-FPN connectivity, there was a significant interaction between n-back condition and group (p = 0.015), with decreased connectivity at 0-back in SZ subjects compared to controls. FPN-to-DMN connectivity also showed a significant condition × group effect (p = 0.003), with decreased connectivity at 0-back in SZ. Across groups, connectivity within the CON and DAN were increased during the 2-back condition, while DMN connectivity with either CON or DAN were decreased during the 2-back condition. Our findings support the role of the FPN, CON, and DAN in working memory and indicate that the pattern of FPN functional connectivity differs between SZ patients and control subjects during the course of a working memory task

Regional cortical thinning in young adults with schizophrenia but not psychotic or non-psychotic bipolar I disorder

Abstract Background Schizophrenia shares some genetic risk and clinical symptoms with bipolar disorder. Clinical heterogeneity across subjects is thought to contribute to variable structural imaging findings across studies. The current study investigates cortical thickness in young adults diagnosed with schizophrenia or bipolar I disorder with a history of hyperthymic mania. We hypothesize that cortical thickness will be most similar between SCZ and the psychotic bipolar 1 disorder subtype. Methods Patients with schizophrenia (n = 52), psychotic bipolar I disorder (PBD; n = 49) and non-psychotic bipolar I disorder (NPBD; n = 24) and healthy controls (n = 40) were scanned in a 3T Trio MRI. The thickness of 34 cortical regions was estimated with FreeSurfer, and analyzed using univariate analyses of variance. Relationships to psychotic (SAPS) and negative (SANS) symptoms were investigated using linear regression. Results Cortical thickness showed significant group effects, after covarying for sex, age, and intracranial volume (p = 0.001). SCZ subjects had thinner paracentral, inferior parietal, supramarginal and fusiform cortices compared to CON. Caudal anterior cingulate cortical thickness was increased in SCZ, PBD and NPBD. Cortical thickness in PBD and NPBD were not significantly different from controls. Significant partial correlations were observed for SAPS severity with middle temporal (r = − 0.26; p = 0.001) and fusiform (− 0.26; p = 0.001) cortical thickness. Conclusions Individuals with SCZ displayed significantly reduced cortical thickness in several cortical regions compared to both CON and bipolar. We found that SCZ participants had significant cortical thinning relative to CON and bipolar disorder most significantly in the frontal (i.e. paracentral), parietal (i.e. inferior parietal, supramarginal), and temporal (i.e. middle temporal, fusiform) cortices

Over-winter Survival of Northern Bobwhite in Relation to Landscape Composition and Structure

The conceptualization of security of bobwhite during winter has been predicated on the assumption that winter ranges differ in quality, based on habitat structure, composition, or interspersion. Although some studies have qualitatively related habitat composition to survival, no studies have quantitatively linked habitat or landscape characteristics to winter survival and the specific structural or compositional characteristics that influence quality are unknown. To quantify winter habitat quality, we modeled hazards as a function of habitat characteristics in relation to winter survival of radio-marked bobwhite (2000, n = 118 in 16 coveys; 2001, n = 49 in 7 coveys) in a managed agricultural landscape in Mississippi, as a function of landscape structure and composition at 2 spatial scales (daily and seasonal ranges). For each spatial scale we constructed a priori models that estimated year-specific winter survival as a function of unique combinations of variables that characterized landscape composition and structure and had previously been identified as relevant to bobwhite ecology. At the spatial scale of winter ranges, the a priori model containing % of landscape, mean patch size, and edge density of linear herbaceous was the best approximating model and suggested a negative effect of linear herbaceous cover on survival. In retrospective analyses, models containing variables describing quantity and structure of linear herbaceous cover and cropland indicated that as these elements increased, risk of mortality increased. At the spatial scale of daily activity, metrics describing landscape structure and composition were poor predictors of survival. During this study, the quantity, patch size, amount of edge, or interspersion of patch types within the winter range or surrounding daily activity locations did not measurably influence the hazard function, suggesting that seasonal ranges can have different composition and structure, yet produce similar survival rates for the birds that inhabit each range

Utility of Washington Early Recognition Center (WERC) Self-Report Screening Questionnaires in the Assessment of Patients with Schizophrenia and Bipolar Disorder

Early identification and treatment are associated with improved outcomes in bipolar disorder and schizophrenia. Screening for the presence of these disorders usually involves time-intensive interviews that may not be practical in settings where mental health providers are limited. Thus, individuals at earlier stages of illness are often not identified. The Washington Early Recognition Center Affectivity and Psychosis (WERCAP) Screen is a self-report questionnaire originally developed to identify clinical risk for developing bipolar or psychotic disorders. The goal of the current study was to investigate the utility of the WERCAP Screen and two complementary questionnaires, the WERC Stress Screen and the WERC Substance Screen, in identifying individuals with established schizophrenia or bipolar disorder. Participants consisted of 35 bipolar disorder (BPD) and 34 schizophrenia (SCZ) patients, as well as 32 controls (CON), aged 18-30 years. Univariate analyses were used to test for score differences between groups. Logistic regression and ROC curves were used to identify diagnostic predictors. Significant group differences were found for the psychosis section of the WERCAP (pWERCAP; p 20 (AUC: 0.87; sensitivity: 0.91; specificity: 1.0); while that for the pWERCAP to identify schizophrenia was a score of >13 (AUC: 0.89; sensitivity: 0.88; specificity: 0.88). These results indicate that the WERCAP Screen may be useful in screening individuals for bipolar disorder and schizophrenia, and that identifying stress and substance use severity can be rapidly done using self-report questionnaires. Larger studies in undiagnosed individuals will be needed to test the WERCAP Screen’s ability to identify mania or psychosis in the community

A Unified attentional bottleneck in the human brain

Human information processing is characterized by bottlenecks that constrain throughput. These bottlenecks limit both what we can perceive and what we can act on in multitask settings. Although perceptual and response limitations are often attributed to independent information processing bottlenecks, it has recently been suggested that a common attentional limitation may be responsible for both. To date, however, evidence supporting the existence of such a “unified” bottleneck has been mixed. Here, we tested the unified bottleneck hypothesis using time-resolved fMRI. Experiment 1 isolated brain regions involved in the response selection bottleneck that limits speeded dual-task performance. These same brain regions were not only engaged by a perceptual encoding task in Experiment 2, their activity also tracked delays to a speeded decision-making task caused by concurrent perceptual encoding (Experiment 3). We conclude that a unified attentional bottleneck, including the inferior frontal junction, superior medial frontal cortex, and bilateral insula, temporally limits operations as diverse as perceptual encoding and decision-making

Fronto-parietal and cingulo-opercular network integrity and cognition in health and schizophrenia

Growing evidence suggests that coordinated activity within specific functional brain networks supports cognitive ability, and that abnormalities in brain connectivity may underlie cognitive deficits observed in neuropsychiatric diseases, such as schizophrenia. Two functional networks, the fronto-parietal network (FPN) and cingulo-opercular network (CON), are hypothesized to support top-down control of executive functioning, and have therefore emerged as potential drivers of cognitive impairment in disease-states. Graph theoretic analyses of functional connectivity data can characterize network topology, allowing the relationships between cognitive ability and network integrity to be examined. In the current study we applied graph analysis to pseudo-resting state data in 54 healthy subjects and 46 schizophrenia patients, and measured overall cognitive ability as the shared variance in performance from tasks of episodic memory, verbal memory, processing speed, goal maintenance, and visual integration. We found that, across all participants, cognitive ability was significantly positively associated with the local and global efficiency of the whole brain, FPN, and CON, but not with the efficiency of a comparison network, the auditory network. Additionally, the participation coefficient of the right anterior insula, a major hub within the CON, significantly predicted cognition, and this relationship was independent of CON global efficiency. Surprisingly, we did not observe strong evidence for group differences in any of our network metrics. These data suggest that functionally efficient task control networks support better cognitive ability in both health and schizophrenia, and that the right anterior insula may be a particularly important hub for successful cognitive performance across both health and disease

Evidence for Accelerated Decline of Functional Brain Network Efficiency in Schizophrenia

Previous work suggests that individuals with schizophrenia display accelerated aging of white matter integrity, however, it is still unknown whether functional brain networks also decline at an elevated rate in schizophrenia. Given the known degradation of functional connectivity and the normal decline in cognitive functioning throughout healthy aging, we aimed to test the hypothesis that efficiency of large-scale functional brain networks supporting overall cognition, as well as integrity of hub nodes within those networks, show evidence of accelerated aging in schizophrenia. Using pseudo-resting state data in 54 healthy controls and 46 schizophrenia patients, in which task-dependent signal from 3 tasks was regressed out to approximate resting-state data, we observed a significant diagnosis by age interaction in the prediction of both global and local efficiency of the cingulo-opercular network, and of the local efficiency of the fronto-parietal network, but no interaction when predicting both default mode network and whole brain efficiency. We also observed a significant diagnosis by age interaction for the node degree of the right anterior insula, left dorsolateral prefrontal cortex, and dorsal anterior cingulate cortex. All interactions were driven by stronger negative associations between age and network metrics in the schizophrenia group than the healthy controls. These data provide evidence that is consistent with accelerated aging of large-scale functional brain networks in schizophrenia that support higher-order cognitive ability