Avinash Ramyead

Aberrant Current Source-Density and Lagged Phase Synchronization of Neural Oscillations as Markers for Emerging Psychosis

BACKGROUND Converging evidence indicates that neural oscillations coordinate activity across brain areas, a process which is seemingly perturbed in schizophrenia. In particular, beta (13-30 Hz) and gamma (30-50 Hz) oscillations were repeatedly found to be disturbed in schizophrenia and linked to clinical symptoms. However, it remains unknown whether abnormalities in current source density (CSD) and lagged phase synchronization of oscillations across distributed regions of the brain already occur in patients with an at-risk mental state (ARMS) for psychosis. METHODS To further elucidate this issue, we assessed resting-state EEG data of 63 ARMS patients and 29 healthy controls (HC). Twenty-three ARMS patients later made a transition to psychosis (ARMS-T) and 40 did not (ARMS-NT). CSD and lagged phase synchronization of neural oscillations across brain areas were assessed using eLORETA and their relationships to neurocognitive deficits and clinical symptoms were analyzed using linear mixed-effects models. RESULTS ARMS-T patients showed higher gamma activity in the medial prefrontal cortex compared to HC, which was associated with abstract reasoning abilities in ARMS-T. Furthermore, in ARMS-T patients lagged phase synchronization of beta oscillations decreased more over Euclidian distance compared to ARMS-NT and HC. Finally, this steep spatial decrease of phase synchronicity was most pronounced in ARMS-T patients with high positive and negative symptoms scores. CONCLUSIONS These results indicate that patients who will later make the transition to psychosis are characterized by impairments in localized and synchronized neural oscillations providing new insights into the pathophysiological mechanisms of schizophrenic psychoses and may be used to improve the prediction of psychosis.

Sex differences in cognitive functioning in at-risk mental state for psychosis, first episode psychosis and healthy control subjects.

BACKGROUND Several sex differences in schizophrenia have been reported including differences in cognitive functioning. Studies with schizophrenia patients and healthy controls (HC) indicate that the sex advantage for women in verbal domains is also present in schizophrenia patients. However, findings have been inconsistent. No study focused on sex-related cognitive performance differences in at-risk mental state for psychosis (ARMS) individuals yet. Thus, the aim of the present study was to investigate sex differences in cognitive functioning in ARMS, first episode psychosis (FEP) and HC subjects. We expected a better verbal learning and memory performance of women in all groups. METHODS The neuropsychological data analysed in this study were collected within the prospective Früherkennung von Psychosen (FePsy) study. In total, 118 ARMS, 88 FEP individuals and 86 HC completed a cognitive test battery covering the domains of executive functions, attention, working memory, verbal learning and memory, IQ and speed of processing. RESULTS Women performed better in verbal learning and memory regardless of diagnostic group. By contrast, men as compared to women showed a shorter reaction time during the working memory task across all groups. CONCLUSION The results provide evidence that women generally perform better in verbal learning and memory, independent of diagnostic group (ARMS, FEP, HC). The finding of a shorter reaction time for men in the working memory task could indicate that men have a superior working memory performance since they responded faster during the target trials, while maintaining a comparable overall working memory performance level.

Prediction of psychosis using neural oscillations and machine learning in neuroleptic-naïve at-risk patients

Abstract Objectives: This study investigates whether abnormal neural oscillations, which have been shown to precede the onset of frank psychosis, could be used towards the individualised prediction of psychosis in clinical high-risk patients. Methods: We assessed the individualised prediction of psychosis by detecting specific patterns of beta and gamma oscillations using machine-learning algorithms. Prediction models were trained and tested on 53 neuroleptic-naïve patients with a clinical high-risk for psychosis. Of these, 18 later transitioned to psychosis. All patients were followed up for at least 3 years. For an honest estimation of the generalisation capacity, the predictive performance of the models was assessed in unseen test cases using repeated nested cross-validation. Results: Transition to psychosis could be predicted from current-source density (CSD; area under the curve [AUC] = 0.77), but not from lagged phase synchronicity data (LPS; AUC = 0.56). Combining both modalities did not improve the predictive accuracy (AUC = 0.78). The left superior temporal gyrus, the left inferior parietal lobule and the precuneus most strongly contributed to the prediction of psychosis. Conclusions: Our results suggest that CSD measurements extracted from clinical resting state EEG can help to improve the prediction of psychosis on a single-subject level.

Prediction of transition to psychosis in patients with a clinical high risk for psychosis: a systematic review of methodology and reporting.

BACKGROUND To enhance indicated prevention in patients with a clinical high risk (CHR) for psychosis, recent research efforts have been increasingly directed towards estimating the risk of developing psychosis on an individual level using multivariable clinical prediction models. The aim of this study was to systematically review the methodological quality and reporting of studies developing or validating such models. METHOD A systematic literature search was carried out (up to 14 March 2016) to find all studies that developed or validated a clinical prediction model predicting the transition to psychosis in CHR patients. Data were extracted using a comprehensive item list which was based on current methodological recommendations. RESULTS A total of 91 studies met the inclusion criteria. None of the retrieved studies performed a true external validation of an existing model. Only three studies (3.5%) had an event per variable ratio of at least 10, which is the recommended minimum to avoid overfitting. Internal validation was performed in only 14 studies (15%) and seven of these used biased internal validation strategies. Other frequently observed modeling approaches not recommended by methodologists included univariable screening of candidate predictors, stepwise variable selection, categorization of continuous variables, and poor handling and reporting of missing data. CONCLUSIONS Our systematic review revealed that poor methods and reporting are widespread in prediction of psychosis research. Since most studies relied on small sample sizes, did not perform internal or external cross-validation, and used poor model development strategies, most published models are probably overfitted and their reported predictive accuracy is likely to be overoptimistic.

Neural oscillations in antipsychotic-naïve patients with a first psychotic episode

Abstract Objectives: In chronic schizophrenic psychoses, oscillatory abnormalities predominantly occur in prefrontal cortical regions and are associated with reduced communication across cortical areas. Nevertheless, it remains unclear whether similar alterations can be observed in patients with a first episode of psychosis (FEP), a state characterised by pathological features occurring in both late prodromal patients and initial phases of frank schizophrenic psychoses. Methods: We assessed resting-state electroencephalographic data of 31 antipsychotic-naïve FEP patients and 29 healthy controls (HC). We investigated the three-dimensional (3D) current source density (CSD) distribution and lagged phase synchronisation (LPS) of oscillations across small-scale and large-scale brain networks. We additionally investigated LPS relationships with clinical symptoms using linear mixed-effects models. Results: Compared to HC, FEP patients demonstrated abnormal CSD distributions in frontal areas of the brain; while decreased oscillations were found in the low frequencies, an increase was reported in the high frequencies (P < 0.01). Patients also exhibited deviant LPS in the high frequencies, whose dynamics changed over increasing 3D cortico-cortical distances and increasing psychotic symptoms. Conclusions: These results indicate that in addition to prefrontal cortical abnormalities, altered synchronised neural oscillations are also present, suggesting possible disruptions in cortico-cortical communications. These findings provide new insights into the pathophysiological mechanisms of emerging schizophrenic psychoses.

Early detection of psychosis: helpful or stigmatizing experience? A qualitative study

Despite the large scientific debate concerning potential stigmatizing effects of identifying an individual as being in an at‐risk mental state (ARMS) for psychosis, studies investigating this topic from the subjective perspective of patients are rare. This study assesses whether ARMS individuals experience stigmatization and to what extent being informed about the ARMS is experienced as helpful or harmful.

Correlations between self-rating and observer-rating of psychopathology in at-risk mental state and first-episode psychosis patients: influence of disease stage and gender.

Research findings on the correlations between self‐rating and observer‐rating of schizophrenic psychopathology are inconsistent and have rarely considered first‐episode psychosis (FEP) and at‐risk mental state (ARMS) for psychosis patients. This study investigates these correlations in ARMS and FEP patients and how they are moderated by disease stage and gender.