Event-related potential abnormalities in schizophrenia: A failure to gate in salient information?

Sensory gating refers to the central nervous system\u27s ability to filter sensory inputs, and can be measured by comparing the suppression of event-related brain potential (ERP) amplitudes in paired auditory stimulus procedure. Poor gating scores in schizophrenia may be caused by: abnormal responses to the first (SI), the second (S2) or both of the paired stimuli. However since S1 and S2 responses may index separate psychological phenomenon, corresponding to the ability to gate in and gate out sensory stimuli respectively, the precise mechanism affected in schizophrenia remains unclear. To examine the extent to which saliency processing abnormalities may contribute to SI response deficits, standard and rare (15% probability paired stimuli were presented to 21 participants with schizophrenia and 22 healthy control! P50 and N100 ERP amplitude as well as low, beta and gamma frequency power were measure to examine the time course and relative contributions of oscillatory activity affecting auditor processing in schizophrenia. In this study, schizophrenia patients exhibited less evoked beta power (12-20 Hz) in response to salient stimuli at SI, and lower N100 amplitude in response to all SI stimuli. No group differences were found in the low, beta 2 (20-30 Hz), or gamma frequency ranges. These findings suggest aberrant sensory processing during stages of stimulu evaluation and saliency detection in schizophrenia. (C) 2009 Elsevier B.V. All rights reserved

Neural Correlates of Attentional and Mnemonic Processing in Event-Based Prospective Memory

Prospective memory (PM), or memory for realizing delayed intentions, was examined with an event-based paradigm while simultaneously measuring neural activity with high-density EEG recordings. Specifically, the neural substrates of monitoring for an event-based cue were examined, as well as those perhaps associated with the cognitive processes supporting detection of cues and fulfillment of intentions. Participants engaged in a baseline lexical decision task (LDT), followed by a LDT with an embedded PM component. Event-based cues were constituted by color and lexicality (red words). Behavioral data provided evidence that monitoring, or preparatory attentional processes, were used to detect cues. Analysis of the event-related potentials (ERP) revealed visual attentional modulations at 140 and 220 ms post-stimulus associated with preparatory attentional processes. In addition, ERP components at 220, 350, and 400 ms post-stimulus were enhanced for intention-related items. Our results suggest preparatory attention may operate by selectively modulating processing of features related to a previously formed event-based intention, as well as provide further evidence for the proposal that dissociable component processes support the fulfillment of delayed intentions

Top-down control of visual sensory processing during an ocular motor response inhibition task

The study addressed whether top-down control of visual cortex supports volitional behavioral control in a novel antisaccade task. The hypothesis was that anticipatory modulations of visual cortex activity would differentiate trials on which subjects knew an anti- versus a pro-saccade response was required. Trials consisted of flickering checkerboards in both peripheral visual fields, followed by brightening of one checkerboard (target) while both kept flickering. Neural activation related to checkerboards before target onset (bias signal) was assessed using electroencephalography. Pretarget visual cortex responses to checkerboards were strongly modulated by task demands (significantly lower on antisaccade trials), an effect that may reduce the predisposition to saccade generation instigated by visual capture. The results illustrate how top-down sensory regulation can complement motor preparation to facilitate adaptive voluntary behavioral control

Transdiagnostic dimensions of psychosis in the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP)

The validity of the classification of non-affective and affective psychoses as distinct entities has been disputed, but, despite calls for alternative approaches to defining psychosis syndromes, there is a dearth of empirical efforts to identify transdiagnostic phenotypes of psychosis. We aimed to investigate the validity and utility of general and specific symptom dimensions of psychosis cutting across schizophrenia, schizoaffective disorder and bipolar I disorder with psychosis. Multidimensional item-response modeling was conducted on symptom ratings of the Positive and Negative Syndrome Scale, Young Mania Rating Scale, and Montgomery-angstrom sberg Depression Rating Scale in the multicentre Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium, which included 933 patients with a diagnosis of schizophrenia (N=397), schizoaffective disorder (N=224), or bipolar I disorder with psychosis (N=312). A bifactor model with one general symptom dimension, two distinct dimensions of non-affective and affective psychosis, and five specific symptom dimensions of positive, negative, disorganized, manic and depressive symptoms provided the best model fit. There was further evidence on the utility of symptom dimensions for predicting B-SNIP psychosis biotypes with greater accuracy than categorical DSM diagnoses. General, positive, negative and disorganized symptom dimension scores were higher in African American vs. Caucasian patients. Symptom dimensions accurately classified patients into categorical DSM diagnoses. This study provides evidence on the validity and utility of transdiagnostic symptom dimensions of psychosis that transcend traditional diagnostic boundaries of psychotic disorders. Findings further show promising avenues for research at the interface of dimensional psychopathological phenotypes and basic neurobiological dimensions of psychopathology

Local gyrification index in probands with psychotic disorders and their first-degree relatives

BACKGROUND: Psychotic disorders are characterized by aberrant neural connectivity. Alterations in gyrification, the pattern and degree of cortical folding, may be related to the early development of connectivity. Past gyrification studies have relatively small sample sizes, yield mixed results for schizophrenia (SZ), and are scant for psychotic bipolar (BP) and schizoaffective (SZA) disorders and for relatives of these conditions. Here we examine gyrification in psychotic disorder patients and their first-degree relatives as a possible endophenotype. METHODS: Regional Local Gyrification Index (LGI) values, as measured by FreeSurfer software, were compared between 243 controls, 388 psychotic disorder probands, and 300 of their first-degree relatives. For patients, LGI values were examined grouped across psychotic diagnoses and then separately for SZ, SZA, and BP. Familiality (heritability) values and correlations with clinical measures were also calculated for regional LGI values. RESULTS: Probands exhibited significant hypogyria compared to controls in three brain regions and relatives with axis II cluster A disorders showed nearly significant hypogyria in these same regions. LGI values in these locations were significantly heritable and uncorrelated with any clinical measure. Observations of significant CONCLUSIONS: Psychotic disorders appear to be characterized by significant regionally localized hypogyria, particularly in cingulate cortex. This abnormality may be a structural endophenotype marking risk for psychotic illness and it may help elucidate etiological underpinnings of psychotic disorders

An opportunity for primary prevention research in psychotic disorders

An opportunity has opened for research into primary prevention of psychotic disorders, based on progress in endophenotypes, genetics, and genomics. Primary prevention requires reliable prediction of susceptibility before any symptoms are present. We studied a battery of measures where published data supports abnormalities of these measurements prior to appearance of initial psychosis symptoms. These neurobiological and behavioral measurements included cognition, eye movement tracking, Event Related Potentials, and polygenic risk scores. They generated an acceptably precise separation of healthy controls from outpatients with a psychotic disorder. Methods The Bipolar and Schizophrenia Network on Intermediate Phenotypes (B-SNIP) measured this battery in an ancestry-diverse series of consecutively recruited adult outpatients with a psychotic disorder and healthy controls. Participants include all genders, 16 to 50 years of age, 261 with psychotic disorders (Schizophrenia (SZ) 109, Bipolar with psychosis (BPP) 92, Schizoaffective disorder (SAD) 60), 110 healthy controls. Logistic Regression, and an extension of the Linear Mixed Model to include analysis of pairwise interactions between measures (Environmental kernel Relationship Matrices (ERM)) with multiple iterations, were performed to predict case-control status. Each regression analysis was validated with four-fold cross-validation. Results and conclusions Sensitivity, specificity, and Area Under the Curve of Receiver Operating Characteristic of 85%, 62%, and 86%, respectively, were obtained for both analytic methods. These prediction metrics demonstrate a promising diagnostic distinction based on premorbid risk variables. There were also statistically significant pairwise interactions between measures in the ERM model. The strong prediction metrics of both types of analytic model provide proof-of-principle for biologically-based laboratory tests as a first step toward primary prevention studies. Prospective studies of adolescents at elevated risk, vs. healthy adolescent controls, would be a next step toward development of primary prevention strategies

Joint Coupling of Awake EEG Frequency Activity and MRI Gray Matter Volumes in the Psychosis Dimension: A BSNIP Study

Background: Many studies have examined either electroencephalogram (EEG) frequency activity or gray matter volumes (GMV) in various psychoses [including schizophrenia (SZ), schizoaffective (SZA), and psychotic bipolar disorder (PBP)]. Prior work demonstrated similar EEG and gray matter abnormalities in both SZ and PBP. Integrating EEG and GMV and jointly analyzing the combined data fully elucidates the linkage between the two and may provide better biomarker- or endophenotype-specificity for a particular illness. Joint exploratory investigations of EEG and GMV are scarce in the literature and the relationship between the two in psychosis is even less explored. We investigated a joint multivariate model to test whether the linear relationship or linkage between awake EEG (AEEG) frequency activity and GMV is abnormal across the psychosis dimension and if such effects are also present in first-degree relatives. Methods: We assessed 607 subjects comprising 264 probands [105 SZ, 72 SZA, and 87 PBP], 233 of their first degree relatives [82 SZ relatives (SZR), 71 SZA relatives (SZAR), and 80 PBP relatives (PBPR)], and 110 healthy comparison subjects (HC). All subjects underwent structural MRI (sMRI) and EEG scans. Frequency activity and voxel-based morphometric GMV were derived from EEG and sMRI data, respectively. Seven AEEG frequency and gray matter components were extracted using Joint independent component analysis (jICA). The loading coefficients (LC) were examined for group differences using analysis of covariance. Further, the LCs were correlated with psychopathology scores to identify relationship with clinical symptoms. Results: Joint ICA revealed a single component differentiating SZ from HC (p < 0.006), comprising increased posterior alpha activity associated with decreased volume in inferior parietal lobe, supramarginal, parahippocampal gyrus, middle frontal, inferior temporal gyri, and increased volume of uncus and culmen. No components were aberrant in either PBP or SZA or any relative group. No significant association was identified with clinical symptom measures. Conclusion: Our data suggest that a joint EEG and GMV model yielded a biomarker specific to SZ, not abnormal in PBP or SZA. Alpha activity was related to both increased and decreased volume in different cortical structures. Additionally, the joint model failed to identify endophenotypes across psychotic disorders

Large-Scale Fusion of Gray Matter and Resting-State Functional MRI Reveals Common and Distinct Biological Markers across the Psychosis Spectrum in the B-SNIP Cohort

To investigate whether aberrant interactions between brain structure and function present similarly or differently across probands with psychotic illnesses [schizophrenia (SZ), schizoaffective disorder (SAD), and bipolar I disorder with psychosis (BP)] and whether these deficits are shared with their first-degree non-psychotic relatives. A total of 1199 subjects were assessed, including 220 SZ, 147 SAD, 180 psychotic BP, 150 first-degree relatives of SZ, 126 SAD relatives, 134 BP relatives, and 242 healthy controls (1). All subjects underwent structural MRI (sMRI) and resting-state functional MRI (rs-fMRI) scanning. Joint-independent component analysis (jICA) was used to fuse sMRI gray matter and rs-fMRI amplitude of low-frequency fluctuations data to identify the relationship between the two modalities. jICA revealed two significantly fused components. The association between functional brain alteration in a prefrontal–striatal–thalamic–cerebellar network and structural abnormalities in the default mode network was found to be common across psychotic diagnoses and correlated with cognitive function, social function, and schizo-bipolar scale scores. The fused alteration in the temporal lobe was unique to SZ and SAD. The above effects were not seen in any relative group (including those with cluster-A personality). Using a multivariate-fused approach involving two widely used imaging markers, we demonstrate both shared and distinct biological traits across the psychosis spectrum. Furthermore, our results suggest that the above traits are psychosis biomarkers rather than endophenotypes