Addressing Formal Thought Disorder in Psychosis through Novel Assessment and Targeted Intervention

Indiana University-Purdue University Indianapolis (IUPUI)Formal thought disorder (FTD) is a debilitating symptom of psychosis. It is linked to functional deficits and generally demonstrates poor response to interventions. Metacognition has emerged as a potential therapeutic target that may be effective in reducing FTD, as metacognitive deficits and FTD both arise from disruptions in associative thought processes. This study’s primary aim was to determine whether FTD could be reduced with metacognitive therapy. Pre-post changes in FTD severity were assessed using clinician-rated and automated measures in 20 individuals with psychotic disorders who received 12 sessions of evidence-based metacognitive therapy. We also examined whether reductions in FTD were larger when assessed with automated instruments versus clinician-rated measures. Aim two compared associations between FTD and three outcome variables (social functioning, role functioning, metacognition) across FTD-measurement approach. Results indicated that automated FTD, but not clinician-rated FTD, was significantly reduced post-intervention. This effect was more robust within a subsample exhibiting greater levels of FTD. Strength of associations between FTD and outcome variables did not differ across FTD measurement approach. These findings provide initial evidence that a targeted metacognitive intervention can reduce FTD. Effects were strongest for automated instruments, which may be more sensitive to detecting change; however, differences in measurement type did not extend to associations with selected outcome variables. This study provides preliminary support for future efforts to reduce FTD. Large-scale studies with longer intervention periods may further our understanding of the effectiveness of metacognitive intervention on FTD

Examining Affect in Psychometric Schizotypy Using Behavioral Experience Sampling Methodology

poster abstractIn schizophrenia, patients often experience more negative emotions in the form of anger, sadness, and anxiety when compared to the general population. One unique way of measuring affect outside of the laboratory has been to use Experience Sampling Methods (ESM) to assess how individuals perceive current emotions in their daily life. However, these methods are still subject to self-report bias. In this study, we examined affect using traditional ESM methods while also implementing the Electronically Activated Recorder (EAR), a behaviorally-based ESM measure that provides real-world assessments of speech. To examine the EAR, we evaluated affect in schizotypy and non-schizotypy groups. Research shows that schizophrenia-like experiences, like increased negative affect, run along a continuum. Schizotypy is a category on the healthier end of the schizophrenia-spectrum; it applies to individuals who are thought to have a putative genetic liability for schizophrenia. Using the Linguistic Inquiry and Word Count (LIWC), we compared affective word usage among schizotypy and non-schizotypy groups to provide a real-world, behavioral ESM measure. When traditional ESM measures were used, we found individuals with schizotypy reported less negative emotions compared to the non-schizotypy group, but results did not reach the level of significance. We also observed that non-schizotypy individuals reported slightly higher positive emotions, and the schizotypy group reported slightly higher negative emotions. A similar pattern was observed when examining EAR data. Overall, results suggested that traditional and behavioral ESM measures of affect had significant overlap. In general, those with schizotypy demonstrated slightly more negative emotion and slightly less positive emotion than the non-schizotypy group. Findings did not reach the level of significance. This study demonstrates that the EAR provides behavioral ratings of affect that are on par with traditional ESM ratings. Future work should examine the EAR at different points on the schizophrenia-spectrum

Affective Systems Induce Formal Thought Disorder in Early-Stage Psychosis

Although formal thought disorder (FTD) has been described since early conceptualizations of psychosis, its underlying mechanisms are unclear. Evidence suggests FTD may be influenced by affective and cognitive systems; however, few have examined these relationships—with none focusing on early-stage psychosis (EP). In this study, positive FTD and speech production were measured in sex- and race-matched EP (n = 19) and healthy control (n = 19) groups by assessing “reactivity”—a change in experimental compared with baseline conditions—across baseline, affective, and cognitive conditions. Relationships with functioning were also examined within each group. Three key findings emerged: (a) the EP group displayed large differences in positive FTD and speech production, (b) those with EP exhibited affective reactivity for positive FTD, and (c) positive FTD and affective reactivity were linked with poor real-world functioning in EP and these relationships did not considerably change when controlling for positive symptom (e.g., delusions, hallucinations) severity. Our findings provide preliminary evidence that affective, but not cognitive, systems play a critical role in positive FTD. Affective reactivity, in particular, may aid in predicting those with EP who go on to develop serious social impairments. Future work should focus on whether affective systems differentially influence those at separate points on the psychosis-spectrum in an effort to establish evidence-based treatments for FTD

Additional Support for the Cognitive Model of Schizophrenia: Evidence of Elevated Defeatist Beliefs in Schizotypy

Objectives The cognitive model of poor functioning in schizophrenia posits that defeatist performance beliefs—overgeneralized negative beliefs about one's ability to perform tasks—develop prior to the onset of psychosis and contribute to the development and maintenance of negative symptoms and poor functioning. Although several studies with schizophrenia samples have provided support for the model, there is a paucity of research investigating these beliefs in individuals with schizotypy—those exhibiting traits reflecting a putative genetic liability for schizophrenia. This study had two aims: to examine whether defeatist performance beliefs (1) are elevated in schizotypy compared to controls and (2) are associated with decreased quality of life and working memory and increased negative but not positive schizotypy traits in the schizotypy group. Methods Schizotypy (n = 48) and control (n = 53) groups completed measures of schizotypy traits, defeatist performance beliefs, quality of life, and working memory. Results Analyses revealed that the schizotypy group reported significantly more defeatist performance beliefs than the control group. Within the schizotypy group, increased defeatist performance beliefs were significantly associated with greater negative schizotypy traits and lower quality of life. No significant associations were observed between defeatist performance beliefs and positive schizotypy traits and working memory. Conclusions Results generally support the theoretical validity of the cognitive model of poor functioning in schizophrenia and suggest that elevated defeatist performance beliefs may contribute to the manifestation of subclinical negative symptom traits and reduced quality of life among those with a latent vulnerability for schizophrenia

Category fluency in psychometric schizotypy: How altering emotional valence and cognitive load affects performance

Introduction. In clinical high-risk populations, category fluency deficits are associated with conversion to psychosis. However, their utility as clinical risk markers is unclear in psychometric schizotypy, a group experiencing schizophrenia-like traits that is at putative high risk for psychosis. Methods. We examined whether introducing affective or cognitive load, two important stress vulnerability markers, altered category fluency performance in schizotypy (n = 42) and non-schizotypy (n = 38) groups. To investigate this question, we developed an experimental paradigm where all participants were administered category fluency tests across baseline, pleasant valence, unpleasant valence, and cognitive load conditions. Results. Compared to the non-schizotypy group, those with schizotypy performed significantly worse in pleasant and unpleasant valence conditions, but not cognitive load or baseline fluency tests. Conclusions. This study demonstrated the role of affect – but not cognitive load – on category fluency in psychometric schizotypy, as group differences only emerged once affective load was introduced. One explanation for this finding is that semantic memory may be unimpaired under normal conditions in psychometric schizotypy, but may be compromised once affective load is presented. Future studies should examine whether fluency deficits – particularly when affect is induced – predict future conversion to psychosis in psychometric schizotypy cohorts

Semantic coherence in psychometric schizotypy: An investigation using Latent Semantic Analysis

Technological advancements have led to the development of automated methods for assessing semantic coherence in psychiatric populations. Latent Semantic Analysis (LSA) is an automated method that has been used to quantify semantic coherence in schizophrenia-spectrum disorders. The current study examined whether: 1) Semantic coherence reductions extended to psychometrically-defined schizotypy and 2) Greater cognitive load further reduces semantic coherence. LSA was applied to responses generated during category fluency tasks in baseline and cognitive load conditions. Significant differences between schizotypy and non-schizotypy groups were not observed. Findings suggest that semantic coherence may be relatively preserved at this point on the schizophrenia-spectrum

The link between formal thought disorder and social functioning in schizophrenia: A meta-analysis

Background. Formal thought disorder (FTD) and social functioning impairments are core symptoms of schizophrenia. Although both have been observed for over a century, the strength of the relationship between FTD and social functioning remains unclear. Furthermore, a variety of methodological approaches have been used to assess these constructs—which may contribute to inconsistency in reported associations. This meta-analysis aimed to: (a) systematically test the relationship between FTD and social functioning and (b) determine if the methodology used to assess FTD and/or social functioning moderates this relationship. Methods. Following Preferred Reporting Items for Systematic reviews and Meta-analyses (PRISMA) guidelines, a targeted literature search was conducted on studies examining the relationship between FTD and social functioning. Correlations were extracted and used to calculate weighted mean effect sizes using a random effects model. Results. A total of 1,478 participants across 13 unique studies were included in this meta-analysis. A small-medium inverse association (r = −0.23, p < 0.001) was observed between FTD and social functioning. Although heterogeneity analyses produced a significant Q-statistic (Q = 52.77, p = <0.001), the relationship between FTD and social functioning was not moderated by methodology, study quality, demographic variables, or clinical factors. Conclusions. Findings illustrate a negative association between FTD and social functioning. Despite differences in the methodological approach used and type of information assessed, measurement type and clinical factors did not moderate the relationship between FTD and social functioning. Future studies should explore whether other variables, such as cognitive processes (e.g., social cognition), may account for variability in associations between these constructs

Conceptual Disorganization Weakens Links in Cognitive Pathways: Disentangling Neurocognition, Social Cognition, and Metacognition in Schizophrenia

Disentangling links between neurocognition, social cognition, and metacognition offers the potential to improve interventions for these cognitive processes. Disorganized symptoms have shown promise for explaining the limiting relationship that neurocognition holds with both social cognition and metacognition. In this study, primary aims included: 1) testing whether conceptual disorganization, a specific disorganized symptom, moderated relationships between cognitive processes, and 2) examining the level of conceptual disorganization necessary for links between cognitive processes to break down. To accomplish these aims, comprehensive assessments of conceptual disorganization, neurocognition, social cognition, and metacognition were administered to 67 people with schizophrenia-spectrum disorders. We found that conceptual disorganization significantly moderated the relationship between neurocognition and metacognition, with links between cognitive processes weakening when conceptual disorganization is present even at minimal levels of severity. There was no evidence that conceptual disorganization—or any other specific disorganized symptom—drove the limiting relationship of neurocognition on social cognition. Based on our findings, conceptual disorganization appears to be a critical piece of the puzzle when disentangling the relationship between neurocognition and metacognition. Roles of specific disorganized symptoms in the neurocognition – social cognition relationship were less clear. Findings from this study suggest that disorganized symptoms are an important treatment consideration when aiming to improve cognitive impairments

Euclid Preparation. XXVIII. Forecasts for ten different higher-order weak lensing statistics

Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale structure. The aim of the Higher-Order Weak Lensing Statistics (HOWLS) project is to assess, compare, and combine the constraining power of ten different HOS on a common set of $Euclid$-like mocks, derived from N-body simulations. In this first paper of the HOWLS series, we computed the nontomographic ($\Omega_{\rm m}$, $\sigma_8$) Fisher information for the one-point probability distribution function, peak counts, Minkowski functionals, Betti numbers, persistent homology Betti numbers and heatmap, and scattering transform coefficients, and we compare them to the shear and convergence two-point correlation functions in the absence of any systematic bias. We also include forecasts for three implementations of higher-order moments, but these cannot be robustly interpreted as the Gaussian likelihood assumption breaks down for these statistics. Taken individually, we find that each HOS outperforms the two-point statistics by a factor of around two in the precision of the forecasts with some variations across statistics and cosmological parameters. When combining all the HOS, this increases to a $4.5$ times improvement, highlighting the immense potential of HOS for cosmic shear cosmological analyses with $Euclid$. The data used in this analysis are publicly released with the paper.Comment: 33 pages, 24 figures, main results in Fig. 19 & Table 5, version published in A&

Euclid Preparation TBD. Characterization of convolutional neural networks for the identification of galaxy-galaxy strong lensing events

Forthcoming imaging surveys will potentially increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of tens of millions of galaxies will have to be inspected to identify potential candidates. In this context, deep learning techniques are particularly suitable for the finding patterns in large data sets, and convolutional neural networks (CNNs) in particular can efficiently process large volumes of images. We assess and compare the performance of three network architectures in the classification of strong lensing systems on the basis of their morphological characteristics. We train and test our models on different subsamples of a data set of forty thousand mock images, having characteristics similar to those expected in the wide survey planned with the ESA mission \Euclid, gradually including larger fractions of faint lenses. We also evaluate the importance of adding information about the colour difference between the lens and source galaxies by repeating the same training on single-band and multi-band images. Our models find samples of clear lenses with $\gtrsim 90\%$ precision and completeness, without significant differences in the performance of the three architectures. Nevertheless, when including lenses with fainter arcs in the training set, the three models' performance deteriorates with accuracy values of $\sim 0.87$ to $\sim 0.75$ depending on the model. Our analysis confirms the potential of the application of CNNs to the identification of galaxy-scale strong lenses. We suggest that specific training with separate classes of lenses might be needed for detecting the faint lenses since the addition of the colour information does not yield a significant improvement in the current analysis, with the accuracy ranging from $\sim 0.89$ to $\sim 0.78$ for the different models