Further Comparison between ATNoSFERES and XCSM

International audienceIn this paper we present ATNoSFERES, a new framework based on an indirect encoding Genetic Algorithm which builds finite-state automata controllers able to deal with perceptual aliazing. In the context of our ongoing line of research, we compare it with XCSM, a memory-based extension of the most studied Learning Classifier System, XCS, through two benchmark experiments. We focus in particular on internal state generalization, and add special purpose features to ATNoSFERES to fulfill that comparison. We then discuss the role played by internal state generalization in the experiments studied

Premorbid social adjustment and association with attenuated psychotic symptoms in clinical high-risk and help-seeking youth

Background Attenuated positive symptom syndrome (APSS), characterized by 'putatively prodromal' attenuated psychotic-like pathology, indicates increased risk for psychosis. Poor premorbid social adjustment predicts severity of APSS symptoms and predicts subsequent psychosis in APSS-diagnosed individuals, suggesting application for improving detection of 'true' prodromal youth who will transition to psychosis. However, these predictive associations have not been tested in controls and therefore may be independent of the APSS diagnosis, negating utility for improving prediction in APSS-diagnosed individuals. Method Association between premorbid social maladjustment and severity of positive, negative, disorganized, and general APSS symptoms was tested in 156 individuals diagnosed with APSS and 76 help-seeking (non-APSS) controls enrolled in the Enhancing the Prospective Prediction of Psychosis (PREDICT) study using prediction analysis. Results Premorbid social maladjustment was associated with social anhedonia, reduced expression of emotion, restricted ideational richness, and deficits in occupational functioning, independent of the APSS diagnosis. Associations between social maladjustment and suspiciousness, unusual thought content, avolition, dysphoric mood, and impaired tolerance to normal stress were uniquely present in participants meeting APSS criteria. Social maladjustment was associated with odd behavior/appearance and diminished experience of emotions and self only in participants who did not meet APSS criteria. Conclusions Predictive associations between poor premorbid social adjustment and attenuated psychotic-like pathology were identified, a subset of which were indicative of high risk for psychosis. This study offers a method for improving risk identification while ruling out low-risk individuals

Personal Beliefs about Experiences in those at Clinical High Risk for Psychosis

Background: Negative beliefs about illness in early psychosis have been shown to have an unfavourable impact on one's quality of life. A shift of focus in psychosis research has been on the detection of individuals considered to be at clinical high risk (CHR) of developing psychosis. Little is known about the impact that beliefs about psychotic like experiences or attenuated psychotic symptoms may have on CHR individuals. Aim: To explore these beliefs in a large sample of young people at CHR of developing psychosis using the Personal Beliefs about Experiences Questionnaire (PBEQ). Method: Beliefs about unusual experiences were assessed in 153 CHR individuals with the PBEQ. Prodromal symptoms (measured by the SIPS) and depression (measured by the CDSS) were also assessed. Results: In CHR individuals, holding more negative beliefs was associated with increased severity in depression and negative symptoms. Higher scores on suspiciousness were associated with increased negative beliefs, and higher levels of grandiosity were associated with decreased negative beliefs. Those who later transitioned to psychosis agreed significantly more with statements concerning control over experiences (i.e. my experiences frighten me, I find it difficult to cope). Conclusions: The results suggest that targeting negative beliefs and other illness related appraisals is an important objective for intervention strategies

Neurocognitive predictors of metacognition in individuals at clinical high risk for psychosis

Background:Metacognition refers to the ability to evaluate and control our cognitive processes. While studies have investigated metacognition in schizophrenia and clinical high risk for psychosis (CHR), less is known about the potential mechanisms which result in metacognitive deficits.Aims:We aimed to investigate whether neurocognitive functions including attention, working memory, verbal learning and executive functions predicted the tendency to focus on one's thoughts (cognitive self-consciousness) and beliefs in the efficacy of one's cognitive skills (cognitive confidence).Method:Participants (130 CHR individuals) were recruited as part of the multi-site PREDICT study. They were assessed using the Metacognitions Questionnaire (MCQ) as well as measures of executive function (WCST), attention (N-Back), working memory (LNS) and verbal learning (AVLT).Results:Cognitive competence was negatively correlated with N-Back while cognitive self-consciousness was positively correlated with N-Back and LNS. Linear regression analysis with N-Back, AVLT, LNS and WCST as predictors showed that neurocognition significantly predicted cognitive self-consciousness, with N-Back, LNS and WCST as significant predictors. The model accounted for 14% of the variance in cognitive self-consciousness. However, neurocognition did not result in a significant predictive model of cognitive competence.Conclusions:Neurocognition was associated with an increased focus on one's thoughts, but it was not associated with higher confidence in one's cognitive skills. Neurocognition accounted for less than one-sixth of the variance in metacognition, suggesting that interventions that target neurocognition are unlikely to improve metacognitive abilities

A tensor-based morphometry analysis of regional differences in brain volume in relation to prenatal alcohol exposure

Reductions in brain volumes represent a neurobiological signature of fetal alcohol spectrum disorders (FASD). Less clear is how regional brain tissue reductions differ after normalizing for brain size differences linked with FASD and whether these profiles can predict the degree of prenatal exposure to alcohol. To examine associations of regional brain tissue excesses/deficits with degree of prenatal alcohol exposure and diagnosis with and without correction for overall brain volume, tensor-based morphometry (TBM) methods were applied to structural imaging data from a well-characterized, demographically homogeneous sample of children diagnosed with FASD (n = 39, 9.6–11.0 years) and controls (n = 16, 9.5–11.0 years). Degree of prenatal alcohol exposure was significantly associated with regionally pervasive brain tissue reductions in: (1) the thalamus, midbrain, and ventromedial frontal lobe, (2) the superior cerebellum and inferior occipital lobe, (3) the dorsolateral frontal cortex, and (4) the precuneus and superior parietal lobule. When overall brain size was factored out of the analysis on a subject-by-subject basis, no regions showed significant associations with alcohol exposure. FASD diagnosis was associated with a similar deformation pattern, but few of the regions survived FDR correction. In data-driven independent component analyses (ICA) regional brain tissue deformations successfully distinguished individuals based on extent of prenatal alcohol exposure and to a lesser degree, diagnosis. The greater sensitivity of the continuous measure of alcohol exposure compared with the categorical diagnosis across diverse brain regions underscores the dose dependence of these effects. The ICA results illustrate that profiles of brain tissue alterations may be a useful indicator of prenatal alcohol exposure when reliable historical data are not available and facial features are not apparent

Latent class cluster analysis of symptom ratings identifies distinct subgroups within the clinical high risk for psychosis syndrome

© 2017 The clinical-high-risk for psychosis (CHR-P) syndrome is heterogeneous in terms of clinical presentation and outcomes. Identifying more homogenous subtypes of the syndrome may help clarify its etiology and improve the prediction of psychotic illness. This study applied latent class cluster analysis (LCCA) to symptom ratings from the North American Prodrome Longitudinal Studies 1 and 2 (NAPLS 1 and 2). These analyses produced evidence for three to five subgroups within the CHR-P syndrome. Differences in negative and disorganized symptoms distinguished among the subgroups. Subgroup membership was found to predict conversion to psychosis. The authors contrast the methods employed within this study with previous attempts to identify more homogenous subgroups of CHR-P individuals and discuss how these results could be tested in future samples of CHR-P individuals

The Early Psychosis Screener (EPS): Quantitative validation against the SIPS using machine learning

Machine learning techniques were used to identify highly informative early psychosis self-report items and to validate an early psychosis screener (EPS) against the Structured Interview for Psychosis-risk Syndromes (SIPS). The Prodromal Questionnaire–Brief Version (PQ-B) and 148 additional items were administered to 229 individuals being screened with the SIPS at 7 North American Prodrome Longitudinal Study sites and at Columbia University. Fifty individuals were found to have SIPS scores of 0, 1, or 2, making them clinically low risk (CLR) controls; 144 were classified as clinically high risk (CHR) (SIPS 3–5) and 35 were found to have first episode psychosis (FEP) (SIPS 6). Spectral clustering analysis, performed on 124 of the items, yielded two cohesive item groups, the first mostly related to psychosis and mania, the second mostly related to depression, anxiety, and social and general work/school functioning. Items within each group were sorted according to their usefulness in distinguishing between CLR and CHR individuals using the Minimum Redundancy Maximum Relevance procedure. A receiver operating characteristic area under the curve (AUC) analysis indicated that maximal differentiation of CLR and CHR participants was achieved with a 26-item solution (AUC = 0.899 ± 0.001). The EPS-26 outperformed the PQ-B (AUC = 0.834 ± 0.001). For screening purposes, the self-report EPS-26 appeared to differentiate individuals who are either CLR or CHR approximately as well as the clinician-administered SIPS. The EPS-26 may prove useful as a self-report screener and may lead to a decrease in the duration of untreated psychosis. A validation of the EPS-26 against actual conversion is underway

Networks of blood proteins in the neuroimmunology of schizophrenia.

Levels of certain circulating cytokines and related immune system molecules are consistently altered in schizophrenia and related disorders. In addition to absolute analyte levels, we sought analytes in correlation networks that could be prognostic. We analyzed baseline blood plasma samples with a Luminex platform from 72 subjects meeting criteria for a psychosis clinical high-risk syndrome; 32 subjects converted to a diagnosis of psychotic disorder within two years while 40 other subjects did not. Another comparison group included 35 unaffected subjects. Assays of 141 analytes passed early quality control. We then used an unweighted co-expression network analysis to identify highly correlated modules in each group. Overall, there was a striking loss of network complexity going from unaffected subjects to nonconverters and thence to converters (applying standard, graph-theoretic metrics). Graph differences were largely driven by proteins regulating tissue remodeling (e.g. blood-brain barrier). In more detail, certain sets of antithetical proteins were highly correlated in unaffected subjects (e.g. SERPINE1 vs MMP9), as expected in homeostasis. However, for particular protein pairs this trend was reversed in converters (e.g. SERPINE1 vs TIMP1, being synthetical inhibitors of remodeling of extracellular matrix and vasculature). Thus, some correlation signals strongly predict impending conversion to a psychotic disorder and directly suggest pharmaceutical targets

The Early Psychosis Screener (EPS): Item development and qualitative validation

A panel of experts assembled and analyzed a comprehensive item bank from which a highly sensitive and specific early psychosis screener could be developed. Twenty well-established assessments relating to the prodromal stage, early psychosis, and psychosis were identified. Using DSM-5 criteria, we identified the core concepts represented by each of the items in each of the assessments. These granular core concepts were converted into a uniform set of 490 self-report items using a Likert scale and a ‘past 30 days’ time frame. Partial redundancy was allowed to assure adequate concept coverage. A panel of experts and TeleSage staff rated these items and eliminated 189 items, resulting in 301 items. The items were subjected to five rounds of cognitive interviewing with 16 individuals at clinically high risk for psychosis and 26 community mental health center patients. After each round, the expert panel iteratively reviewed, rated, revised, added, or deleted items to maximize clarity and centrality to the concept. As a result of the interviews, 36 items were revised, 52 items were added, and 205 items were deleted. By the last round of cognitive interviewing, all of the items were clearly understood by all participants. In future work, responses to the final set of 148 items and machine learning techniques will be used to quantitatively identify the subset of items that will best predict clinical high-risk status and conversion

Psychotropic medication use in youth at high risk for psychosis: Comparison of baseline data from two research cohorts 1998-2005 and 2008-2011

Background: Antipsychotic medication use rates have generally been rising among youth with psychiatric disorders, but little is known about use rates of antipsychotics or other psychotropic medications in patients at high risk for psychosis. Method: Baseline psychotropic medication use rates were compared in two research cohorts of patients at high risk for psychosis that enrolled between 1998-2005 (n. = 391) and 2008-2011 (n. = 346). Treatment durations and antipsychotic doses were described for cohort 2. Results: Median age was 17. years in cohort 1 and 18. years in cohort 2. The rate of prescription of any psychotropic at baseline was roughly 40% for each cohort. Antipsychotic prescription rates were 24% among sites that permitted baseline antipsychotic use in cohort 1 and 18% in the cohort 2; the decline did not quite reach statistical significance (p. = 0.064). In cohort 2 the mean. ±. SD baseline chlorpromazine-equivalent dose was 121. ±. 108. mg/d, and lifetime duration of antipsychotic treatment was 3.8. ±. 5.9. months. Discussion: Although the rate of antipsychotic prescription among high-risk youth may have fallen slightly, the nearly one-in-five rate in the second cohort still constitutes a significant exposure. Mitigating factors were that doses and durations of treatment were low. As for other nonpsychotic conditions, it is incumbent on our field to develop alternative treatments for high-risk patients and to generate additional evidence for or against the efficacy of antipsychotics to help define their appropriate role if alternative treatments fail