Background Cognitive dysfunction is a core feature of psychotic disorders; however, substantial variability exists both within and between subjects in terms of cognitive domains of dysfunction, and a clear ‘profile’ of cognitive strengths and weaknesses characteristic of any diagnosis or psychosis as a whole has not emerged. Cluster analysis provides an opportunity to group individuals using a data-driven approach rather than predetermined grouping criteria. While several studies have identified meaningful cognitive clusters in schizophrenia, no study to date has examined cognition in a cross-diagnostic sample of patients with psychotic disorders using a cluster approach. We aimed to examine cognitive variables in a sample of 167 patients with psychosis using cluster methods. Method Subjects with schizophrenia (n=41), schizo-affective disorder (n=53) or bipolar disorder with psychosis (n=73) were assessed using a battery of cognitive and clinical measures. Cognitive data were analysed using Ward’s method, followed by a K-means cluster approach. Clusters were then compared on diagnosis and measures of clinical symptoms, demographic variables and community functioning. Results A four-cluster solution was selected, including a ‘neuropsychologically normal’ cluster, a globally and significantly impaired cluster, and two clusters of mixed cognitive profiles. Clusters differed on several clinical variables; diagnoses were distributed amongst all clusters, although not evenly. Conclusions Identification of groups of patients who share similar neurocognitive profiles may help pinpoint relevant neural abnormalities underlying these traits. Such groupings may also hasten the development of individualized treatment approaches, including cognitive remediation tailored to patients’ specific cognitive profiles.

Introduction: Altered emotion dynamics may represent a transdiagnostic risk factor for mood psychopathology. The present study examined whether altered emotion dynamics were associated with bipolar and depressive psychopathology concurrently and at a three-year followup. Methods: At baseline (n = 138), participants completed diagnostic interviews, questionnaires, and seven days of experience sampling assessments. Four emotion dynamics were computed for negative affect (NA) and positive affect (PA) -within-person variance (variability), mean square of successive differences and probability of acute change (instability), and autocorrelation (inertia). At the three-year follow-up, participants (n = 108) were re-assessed via interviews and questionnaires. Results: NA variability was associated with bipolar spectrum disorders at baseline and follow-up. NA instability predicted depressive symptoms and hypomanic personality at baseline, and bipolar spectrum disorders at the follow-up. NA inertia did not predict diagnoses or symptoms at either assessment. PA inertia predicted hyperthymic temperament at baseline but not follow-up. Notably, NA variability and instability predicted the development of new bipolar spectrum disorders at the follow-up. Limitations: Consistent with the recruitment strategy and young age of the participants, only 50% had developed diagnosable psychopathology by the time of the follow-up assessment. Conclusions: The present study provided a unique demonstration that altered emotion dynamics differentially predicted bipolar and depressive psychopathology concurrently and prospectively. Emotion dynamics are important to both digital phenotyping and mobile-based interventions as emotional instability offers a measurable risk factor that is identifiable prior to illness onset.

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These results generally support a four-factor model of multidimensional impulsivity with a general overall urgency factor instead of separate positive and negative urgency facets.

The present study examined the associations of positive, negative, and disorganized schizotypy with psychotic-like experiences, affect, and social functioning in daily life using experience sampling methodology (ESM) in 2 samples (ns = 165 and 203) that employed different measures of schizotypy. Schizotypy is a useful framework for understanding schizophrenia-spectrum psychopathology, and ESM offers a powerful approach for assessing schizotypy in real-world settings. Participants were signaled 8 times daily for 7 days to complete ESM questionnaires. As hypothesized, positive schizotypy was robustly associated with psychotic-like experiences in daily life, whereas negative schizotypy was associated with negative experiences, diminished positive affect, and social disinterest in both samples. As expected, disorganized schizotypy was associated with disorganization in daily life. Furthermore, it was associated with increased negative affect and diminished positive affect. Thus, positive, negative, and disorganized schizotypy were associated with unique, hypothesized patterns of experiences in daily life, and the findings across the two samples and two schizotypy measures were strikingly consistent. Note that when disorganized schizotypy was not entered as a predictor in the 2 samples, disorganized experiences and negative affect in daily life were associated with positive schizotypy. However, when disorganized schizotypy was included as a predictor, these daily life experiences were associated with disorganized, not positive, schizotypy. This is similar to findings from interview and questionnaire studies that have simultaneously assessed positive, negative, and disorganized schizotypy. The findings support the construct validity of the multidimensional model of schizotypy and the importance of including disorganization in the conceptualization and assessment of schizotypy.

Given the substantial overlap in cognitive dysfunction between bipolar disorder (BD) and schizophrenia (SZ), we examined the utility of the MATRICS Consensus Cognitive Battery (MCCB)-developed for use in SZ-for the measurement of cognition in patients with BD with psychosis (BDP) and its association with community functioning. The MCCB, Multnomah Community Ability Scale, and measures of clinical symptoms were administered to participants with BDP (n=56), SZ (n=37), and healthy controls (HC) (n=57). Groups were compared on clinical and cognitive measures; linear regressions examined associations between MCCB and community functioning. BDP and SZ groups performed significantly worse than HC on most neurocognitive domains; BDP and HC did not differ on Social Cognition. Patients with BDP performed better than patients with SZ on most cognitive measures, although groups only differed on social cognition, working memory, verbal memory, and the composite after controlling for clinical variables. MCCB was not associated with community functioning. The MCCB is an appropriate measure of neurocognition in BDP but does not appear to capture social cognitive deficits in this population. The addition of appropriate social cognitive measures is recommended.

Objective Cognitive dysfunction is a core feature of Bipolar Disorder (BD) in both adult and geriatric patients. However, little is known about whether cognitive functioning declines at a faster rate in patients with BD and there are conflicting reports regarding the relationship between age and cognitive functioning in this population. This cross-sectional study examined the relationship between age and cognitive functioning in patients with BD. Methods Patients with BD I (n=113) and healthy adults (n=64) ages 18–87 completed measures of processing speed, attention, executive functioning, verbal fluency, and clinical symptomatology. Groupwise comparisons were used to examine differences between patients and the comparison group and adult and geriatric BD cohorts. A series of linear regressions was conducted to examine the relationship of age and cognitive functioning, and clinical variables and cognition. Results Patients performed significantly worse than the comparison group on all neuropsychological measures. Age was a significant predictor of Trails A scores with older age associated with worse performance. Conclusions Older age was associated with poorer performance on Trails A in patients with BD but not healthy adults. These results are suggestive of greater dysfunction in processing speed with older age in patients with BD compared to a healthy comparison group. As cognitive functioning is associated with community outcomes, these findings suggest a need for treatments targeting cognitive symptoms across the lifespan. Future research exploring neurobiological evidence for neurodegenerative processes in bipolar disorder will pave the way for potential therapeutic interventions.

Discrepancies regarding the link between autonomic nervous system (ANS) activity and psychopathology may be due in part to inconsistent measurement of non-psychological factors, including eating, drinking, activity, posture, and interacting with others. Rather than sources of noise, behaviors like being active and being with others may be the behavioral pathways that connect psychopathology symptoms to autonomic activity. The present study examined whether behaviors mediate the association of depression, anxiety, and hypomanic traits with ANS by using experience sampling methodology and ambulatory impedance cardiography. Participants (n = 49) completed measures of affect and one day of experience sampling and ambulatory impedance cardiography. The association of hypomanic traits with heart rate variability and heart rate was mediated by physical activity, and social activity mediated the association of depressive symptoms and respiration. These results highlight the importance of considering the pathways between psychopathology and ANS and the mediating role that everyday behaviors play.