Evidence from comprehensive independent validation studies for smooth pursuit dysfunction as a sensorimotor biomarker for psychosis.

Smooth pursuit eye movements are considered a well-established and quantifiable biomarker of sensorimotor function in psychosis research. Identifying psychotic syndromes on an individual level based on neurobiological markers is limited by heterogeneity and requires comprehensive external validation to avoid overestimation of prediction models. Here, we studied quantifiable sensorimotor measures derived from smooth pursuit eye movements in a large sample of psychosis probands (N = 674) and healthy controls (N = 305) using multivariate pattern analysis. Balanced accuracies of 64% for the prediction of psychosis status are in line with recent results from other large heterogenous psychiatric samples. They are confirmed by external validation in independent large samples including probands with (1) psychosis (N = 727) versus healthy controls (N = 292), (2) psychotic (N = 49) and non-psychotic bipolar disorder (N = 36), and (3) non-psychotic affective disorders (N = 119) and psychosis (N = 51) yielding accuracies of 65%, 66% and 58%, respectively, albeit slightly different psychosis syndromes. Our findings make a significant contribution to the identification of biologically defined profiles of heterogeneous psychosis syndromes on an individual level underlining the impact of sensorimotor dysfunction in psychosis.

Clinical characterization and differentiation of B-SNIP psychosis Biotypes: Algorithmic Diagnostics for Efficient Prescription of Treatments (ADEPT)-1.

Clinically defined psychosis diagnoses are neurobiologically heterogeneous. The B-SNIP consortium identified and validated more neurobiologically homogeneous psychosis Biotypes using an extensive battery of neurocognitive and psychophysiological laboratory measures. However, typically the first step in any diagnostic evaluation is the clinical interview. In this project, we evaluated if psychosis Biotypes have clinical characteristics that can support their differentiation in addition to obtaining laboratory testing. Clinical interview data from 1907 individuals with a psychosis Biotype were used to create a diagnostic algorithm. The features were 58 ratings from standard clinical scales. Extremely randomized tree algorithms were used to evaluate sensitivity, specificity, and overall classification success. Biotype classification accuracy peaked at 91 % with the use of 57 items on average. A reduced feature set of 28 items, though, also showed 81 % classification accuracy. Using this reduced item set, we found that only 10-11 items achieved a one-vs-all (Biotype-1 or not, Biotype-2 or not, Biotype-3 or not) area under the sensitivity-specificity curve of .78 to .81. The top clinical characteristics for differentiating psychosis Biotypes, in order of importance, were (i) difficulty in abstract thinking, (ii) multiple indicators of social functioning, (iii) conceptual disorganization, (iv) severity of hallucinations, (v) stereotyped thinking, (vi) suspiciousness, (vii) unusual thought content, (viii) lack of spontaneous speech, and (ix) severity of delusions. These features were remarkably different from those that differentiated DSM psychosis diagnoses. This low-burden adaptive algorithm achieved reasonable classification accuracy and will support Biotype-specific etiological and treatment investigations even in under-resourced clinical and research environments.

Double dissociation between P300 components and task switch error type in healthy but not psychosis participants.

Event-related potentials (ERPs) during oddball tasks and the behavioral performance on the Penn Conditional Exclusion Task (PCET) measure context-appropriate responding: P300 ERPs to oddball targets reflect detection of input changes and context updating in working memory, and PCET performance indexes detection, adherence, and maintenance of mental set changes. More specifically, PCET variables quantify cognitive functions including inductive reasoning (set 1 completion), mental flexibility (perseverative errors), and working memory maintenance (regressive errors). Past research showed that both P300 ERPs and PCET performance are disrupted in psychosis. This study probed the possible neural correlates of 3 PCET abnormalities that occur in participants with psychosis via the overlapping cognitive demands of the two study paradigms. In a two-tiered analysis, psychosis (n = 492) and healthy participants (n = 244) were first divided based on completion of set 1 - which measures subjects' ability to use inductive reasoning to arrive at the correct set. Results showed that participants who failed set 1 produced lower parietal P300, independent of clinical status. In the second tier of analysis, a double dissociation was found among healthy set 1 completers: frontal P300 amplitudes were negatively associated with perseverative errors, and parietal P300 was negatively associated with regressive errors. In contrast, psychosis participants showed global P300 reductions regardless of PCET performance. From this we conclude that in psychosis, overall activations evoked by the oddball task are reduced while the cognitive functions required by PCET are still somewhat supported, showing some level of independence or compensatory physiology in psychosis between neural activities underlying the two tasks.

Characterization of Resting-State Functional Connectivity Changes in Hypertension by a Modified Difference Degree Test.

Introduction: Hypertension affects over a billion people worldwide, and the application of neuroimaging may elucidate changes brought about by the disease. We have applied a graph theory approach to examine the organizational differences in resting-state functional magnetic resonance imaging (rs-fMRI) data between hypertensive and normotensive participants. To detect these groupwise differences, we performed statistical testing using a modified difference degree test (DDT). Methods: Structural and rs-fMRI data were collected from a cohort of 52 total (29 hypertensive and 23 normotensive) participants. Functional connectivity maps were obtained by partial correlation analysis of participant rs-fMRI data. We modified the DDT null generation algorithm and validated the change through different simulation schemes and then applied this modified DDT to our experimental data. Results: Through a comparative analysis, the modified DDT showed higher true positivity rates (TPR) when compared with the base DDT while also maintaining false positivity rates below the nominal value of 5% in nearly all analytically thresholded trials. Applying the modified DDT to our rs-fMRI data showed differential organization in the hypertension group in the regions throughout the brain including the default mode network. These experimental findings agree with previous studies. Conclusions: While our findings agree with previous studies, the experimental results presented require more investigation to prove their link to hypertension. Meanwhile, our modification to the DDT results in higher accuracy and an increased ability to discern groupwise differences in rs-fMRI data. We expect this to be useful in studying groupwise organizational differences in future studies.

Characterization of childhood trauma, hippocampal mediation and Cannabis use in a large dataset of psychosis and non-psychosis individuals.

BACKGROUND: Cannabis use (CA) and childhood trauma (CT) independently increase the risk of earlier psychosis onset; but their interaction in relation to psychosis risk and association with endocannabinoid-receptor rich brain regions, i.e. the hippocampus (HP), remains unclear. The objective was to determine whether lower age of psychosis onset (AgePsyOnset) is associated with CA and CT through mediation by the HP volumes, and genetic risk, as measured by schizophrenia polygene scores (SZ-PGRS). METHODS: Cross-sectional, case-control, multicenter sample from 5 metropolitan US regions. Participants (n = 1185) included 397 controls not affected by psychosis (HC); 209 participants with bipolar disorder type-1; 279 with schizoaffective disorder; and 300 with schizophrenia (DSM IV-TR). CT was assessed using the Childhood Trauma Questionnaire (CTQ); CA was assessed by self-reports and trained clinical interviewers. Assessment included neuroimaging, symptomatology, cognition and calculation of the SZ polygenic risk score (SZ-PGRS). RESULTS: In survival analysis, CT and CA exposure interact to be associated with lower AgePsyOnset. At high CT or CA, CT or CA are individually sufficient to affect AgePsyOnset. CT relation with AgePsyOnset is mediated in part by the HP in CA users before AgePsyOnset. CA before AgePsyOnset is associated with higher SZ-PGRS and correlated with younger age at CA usage. DISCUSSION: CA and CT interact to increase risk when moderate; while severe CT and/or CA abuse/dependence are each sufficient to affect AgePsyOnset, indicating a ceiling effect. Probands with/out CA before AgePsyOnset differ on biological variables, suggesting divergent pathways to psychosis. FUNDING: MH077945; MH096942; MH096913; MH077862; MH103368; MH096900; MH122759.

Using psychosis biotypes and the Framingham model for parsing psychosis biology.

The Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) has invested in the collection and use of multiple biomarkers in individuals with psychosis. We expect psychosis biology and its distinctive types to be reflected in the biomarkers, as they are the 'behaviors' of the brain. Like infectious diseases, we expect the etiologies of these biomarker-driven entities to be multiple and complex. Biomarkers have not yet been annotated with disease characteristics and need to be. As a model, we seek to adopt aspects of the Framingham Heart Study (FHS) to guide and organize these observations.

Antisaccade error rates and gap effects in psychosis syndromes from bipolar-schizophrenia network for intermediate phenotypes 2 (B-SNIP2).

BACKGROUND: Antisaccade tasks can be used to index cognitive control processes, e.g. attention, behavioral inhibition, working memory, and goal maintenance in people with brain disorders. Though diagnoses of schizophrenia (SZ), schizoaffective (SAD), and bipolar I with psychosis (BDP) are typically considered to be distinct entities, previous work shows patterns of cognitive deficits differing in degree, rather than in kind, across these syndromes. METHODS: Large samples of individuals with psychotic disorders were recruited through the Bipolar-Schizophrenia Network on Intermediate Phenotypes 2 (B-SNIP2) study. Anti- and pro-saccade task performances were evaluated in 189 people with SZ, 185 people with SAD, 96 people with BDP, and 279 healthy comparison participants. Logistic functions were fitted to each group's antisaccade speed-performance tradeoff patterns. RESULTS: Psychosis groups had higher antisaccade error rates than the healthy group, with SZ and SAD participants committing 2 times as many errors, and BDP participants committing 1.5 times as many errors. Latencies on correctly performed antisaccade trials in SZ and SAD were longer than in healthy participants, although error trial latencies were preserved. Parameters of speed-performance tradeoff functions indicated that compared to the healthy group, SZ and SAD groups had optimal performance characterized by more errors, as well as less benefit from prolonged response latencies. Prosaccade metrics did not differ between groups. CONCLUSIONS: With basic prosaccade mechanisms intact, the higher speed-performance tradeoff cost for antisaccade performance in psychosis cases indicates a deficit that is specific to the higher-order cognitive aspects of saccade generation.

Psychosis Biotypes: Replication and Validation from the B-SNIP Consortium.

Current clinical phenomenological diagnosis in psychiatry neither captures biologically homologous disease entities nor allows for individualized treatment prescriptions based on neurobiology. In this report, we studied two large samples of cases with schizophrenia, schizoaffective, and bipolar I disorder with psychosis, presentations with clinical features of hallucinations, delusions, thought disorder, affective, or negative symptoms. A biomarker approach to subtyping psychosis cases (called psychosis Biotypes) captured neurobiological homology that was missed by conventional clinical diagnoses. Two samples (called "B-SNIP1" with 711 psychosis and 274 healthy persons, and the "replication sample" with 717 psychosis and 198 healthy persons) showed that 44 individual biomarkers, drawn from general cognition (BACS), motor inhibitory (stop signal), saccadic system (pro- and anti-saccades), and auditory EEG/ERP (paired-stimuli and oddball) tasks of psychosis-relevant brain functions were replicable (r's from .96-.99) and temporally stable (r's from .76-.95). Using numerical taxonomy (k-means clustering) with nine groups of integrated biomarker characteristics (called bio-factors) yielded three Biotypes that were virtually identical between the two samples and showed highly similar case assignments to subgroups based on cross-validations (88.5%-89%). Biotypes-1 and -2 shared poor cognition. Biotype-1 was further characterized by low neural response magnitudes, while Biotype-2 was further characterized by overactive neural responses and poor sensory motor inhibition. Biotype-3 was nearly normal on all bio-factors. Construct validation of Biotype EEG/ERP neurophysiology using measures of intrinsic neural activity and auditory steady state stimulation highlighted the robustness of these outcomes. Psychosis Biotypes may yield meaningful neurobiological targets for treatments and etiological investigations.

Joint estimation and regularized aggregation of brain network in FMRI data.

BACKGROUND: In the Gaussian graphical model framework, precision matrices reveal conditional dependence structure among random variables. In functional magnetic resonance imaging (fMRI) data, estimating such precision matrices of multi-subjects and aggregating them to a group-level is an essential step for constructing a group brain network. NEW METHOD: In this article, we considered joint estimation of multiple precision matrices with regularized aggregation. Also, in the construction of a group precision matrix, we integrated robust aggregation to the estimation. In the estimation of individual precision matrices, we took a regularization approach to induce sparsity, which made brain network estimation more realistic. RESULTS: We demonstrated the effectiveness of the proposed method through simulated examples, and analyses on real fMRI data acquired during eye movement tasks assessing cognitive control. For the fMRI data, the joint estimation of multiple precision matrices (JEMP) with regularized aggregation (RA) captured more robust associations between task-relevant neural regions of interest (ROIs), compared to the analyses using JEMP alone. The JEMP with RA also was sensitive to increased neural efficiency after task practice. COMPARISON WITH EXISTING METHOD(S): The simple average of individual precision matrices may be affected by outliers and provide inconsistent outcomes between subject-level and group-level networks. In contrast, the proposed method yielded a robust group graph that could identify and ease the effect of outliers. CONCLUSIONS: The proposed method identified regions of practice-induced attenuation associated with reduced cognitive demand after repeat task exposure. Through simulated and real data, we demonstrated that this method does not require any distribution assumption, can identify outliers, and provides robust, representative group brain networks. This method can be applied to datasets that have extensive variability and/or multiple outliers, including applications to specific, and general, cognitive processes, as well as for studies that may require longitudinal data, such as pharmaceutical trials.

Auditory Oddball Responses Across the Schizophrenia-Bipolar Spectrum and Their Relationship to Cognitive and Clinical Features.

OBJECTIVE: Neural activations during auditory oddball tasks may be endophenotypes for psychosis and bipolar disorder. The authors investigated oddball neural deviations that discriminate multiple diagnostic groups across the schizophrenia-bipolar spectrum (schizophrenia, schizoaffective disorder, psychotic bipolar disorder, and nonpsychotic bipolar disorder) and clarified their relationship to clinical and cognitive features. METHODS: Auditory oddball responses to standard and target tones from 64 sensor EEG recordings were compared across patients with psychosis (total N=597; schizophrenia, N=225; schizoaffective disorder, N=201; bipolar disorder with psychosis, N=171), patients with bipolar disorder without psychosis (N=66), and healthy comparison subjects (N=415) from the second iteration of the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP2) study. EEG activity was analyzed in voltage and in the time-frequency domain (low, beta, and gamma bands). Event-related potentials (ERPs) were compared with those from an independent sample collected during the first iteration of B-SNIP (B-SNIP1; healthy subjects, N=211; psychosis group, N=526) to establish the repeatability of complex oddball ERPs across multiple psychosis syndromes (r values >0.94 between B-SNIP1 and B-SNIP2). RESULTS: Twenty-six EEG features differentiated the groups; they were used in discriminant and correlational analyses. EEG variables from the N100, P300, and low-frequency ranges separated the groups along a diagnostic continuum from healthy to bipolar disorder with psychosis/bipolar disorder without psychosis to schizoaffective disorder/schizophrenia and were strongly related to general cognitive function (r=0.91). P50 responses to standard trials and early beta/gamma frequency responses separated the bipolar disorder without psychosis group from the bipolar disorder with psychosis group. P200, N200, and late beta/gamma frequency responses separated the two bipolar disorder groups from the other groups. CONCLUSIONS: Neural deviations during auditory processing are related to psychosis history and bipolar disorder. There is a powerful transdiagnostic relationship between severity of these neural deviations and general cognitive performance. These results have implications for understanding the neurobiology of clinical syndromes across the schizophrenia-bipolar spectrum that may have an impact on future biomarker research.

Neural Processing of Repeated Emotional Scenes in Schizophrenia, Schizoaffective Disorder, and Bipolar Disorder.

Impaired emotional processing and cognitive functioning are common in schizophrenia, schizoaffective disorder, and bipolar disorders, causing significant socioemotional disability. While a large body of research demonstrates abnormal cognition/emotion interactions in these disorders, previous studies investigating abnormalities in the emotional scene response using event-related potentials (ERPs) have yielded mixed findings, and few studies compare findings across psychiatric diagnoses. The current study investigates the effects of emotion and repetition on ERPs in a large, well-characterized sample of participants with schizophrenia-bipolar syndromes. Two ERP components that are modulated by emotional content and scene repetition, the early posterior negativity (EPN) and late positive potential (LPP), were recorded in healthy controls and participants with schizophrenia, schizoaffective disorder, bipolar disorder with psychosis, and bipolar disorder without psychosis. Effects of emotion and repetition were compared across groups. Results displayed significant but small effects in schizophrenia and schizoaffective disorder, with diminished EPN amplitudes to neutral and novel scenes, reduced LPP amplitudes to emotional scenes, and attenuated effects of scene repetition. Despite significant findings, small effect sizes indicate that emotional scene processing is predominantly intact in these disorders. Multivariate analyses indicate that these mild ERP abnormalities are related to cognition, psychosocial functioning, and psychosis severity. This relationship suggests that impaired cognition, rather than diagnosis or mood disturbance, may underlie disrupted neural scene processing in schizophrenia-bipolar syndromes.

Reduced white matter microstructure in bipolar disorder with and without psychosis.

OBJECTIVES: Affective and psychotic features overlap considerably in bipolar I disorder, complicating efforts to determine its etiology and develop targeted treatments. In order to clarify whether mechanisms are similar or divergent for bipolar disorder with psychosis (BDP) and bipolar disorder with no psychosis (BDNP), neurobiological profiles for both the groups must first be established. This study examines white matter structure in the BDP and BDNP groups, in an effort to identify portions of white matter that may differ between the bipolar and healthy groups or between the bipolar subgroups themselves. METHODS: Diffusion-weighted imaging data were acquired from participants with BDP (n = 45), BDNP (n = 40), and healthy comparisons (HC) (n = 66). Fractional anisotropy (FA), radial diffusivity (RD), and spin distribution function (SDF) values indexing white matter diffusivity or spin density were calculated and compared between the groups. RESULTS: In comparisons between both the bipolar groups and HC, FA (FDR < 0.00001) and RD (FDR = 0.0037) differed minimally, in localized portions of the left cingulum and corpus callosum, while reductions in SDF (FDR = 0.0002) were more widespread. The bipolar subgroups did not differ from each other on FA, RD, or SDF metrics. CONCLUSIONS: Together, these results demonstrate a novel profile of white matter differences in bipolar disorder and suggest that this white matter pathology is associated with the affective disturbance common to those with bipolar disorder rather than the psychotic features unique to some. The white matter alterations identified in this study may provide substrates for future studies examining specific mechanisms that target affective domains of illness.

White matter microstructure across brain-based biotypes for psychosis - findings from the bipolar-schizophrenia network for intermediate phenotypes.

The B-SNIP consortium identified three brain-based Biotypes across the psychosis spectrum, independent of clinical phenomenology. To externally validate the Biotype model, we used free-water fractional volume (FW) and free-water corrected fractional anisotropy (FAT) to compare white matter differences across Biotypes and clinical diagnoses. Diffusion tensor imaging data from 167 individuals were included: 41 healthy controls, 55 schizophrenia probands, 47 schizoaffective disorder probands, and 24 probands with psychotic bipolar disorder. Compared to healthy controls, FAt reductions were observed in the body of corpus callosum (BCC) for schizoaffective disorder (d = 0.91) and schizophrenia (d = 0.64). Grouping by Biotype, Biotype 1 showed FAt reductions in the CC and fornix, with largest effect in the BCC (d = 0.87). Biotype 2 showed significant FAt reductions in the BCC (d = 0.90). Schizoaffective disorder individuals had elevated FW in the CC, fornix and anterior corona radiata (ACR), with largest effect in the BCC (d = 0.79). Biotype 2 showed elevated FW in the CC, fornix and ACR, with largest effect in the BCC (d = 0.94). While significant diagnosis comparisons were observed, overall greater discrimination from healthy controls was observed for lower FAt in Biotype 1 and elevated FW in Biotype 2. However, between-group differences were modest, with one region (cerebral peduncle) showing a between-Biotype effect. No between-group effects were observed for diagnosis groupings.

Testing Psychosis Phenotypes From Bipolar-Schizophrenia Network for Intermediate Phenotypes for Clinical Application: Biotype Characteristics and Targets.

BACKGROUND: Psychiatry aspires to the molecular understanding of its disorders and, with that knowledge, to precision medicine. Research supporting such goals in the dimension of psychosis has been compromised, in part, by using phenomenology alone to estimate disease entities. To this end, we are proponents of a deep phenotyping approach in psychosis, using computational strategies to discover the most informative phenotypic fingerprint as a promising strategy to uncover mechanisms in psychosis. METHODS: Doing this, the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) has used biomarkers to identify distinct subtypes of psychosis with replicable biomarker characteristics. While we have presented these entities as relevant, their potential utility in clinical practice has not yet been demonstrated. RESULTS: Here we carried out an analysis of clinical features that characterize biotypes. We found that biotypes have unique and defining clinical characteristics that could be used as initial screens in the clinical and research settings. Differences in these clinical features appear to be consistent with biotype biomarker profiles, indicating a link between biological features and clinical presentation. Clinical features associated with biotypes differ from those associated with DSM diagnoses, indicating that biotypes and DSM syndromes are not redundant and are likely to yield different treatment predictions. We highlight 3 predictions based on biotype that are derived from individual biomarker features and cannot be obtained from DSM psychosis syndromes. CONCLUSIONS: In the future, biotypes may prove to be useful for targeting distinct molecular, circuit, cognitive, and psychosocial therapies for improved functional outcomes.

Distinguishing patterns of impairment on inhibitory control and general cognitive ability among bipolar with and without psychosis, schizophrenia, and schizoaffective disorder.

BACKGROUND: Deficits in inhibitory control on a Stop Signal Task (SST) were previously observed to be of similar magnitude across schizophrenia, schizoaffective, and bipolar disorder with psychosis, despite variation in general cognitive ability. Understanding different patterns of performance on the SST may elucidate different pathways to the impaired inhibitory control each group displayed. Comparing nonpsychotic bipolar disorder to the psychosis groups on SST may also expand our understanding of the shared neurobiology of this illness spectrum. METHODS: We tested schizophrenia (n = 220), schizoaffective (n = 216), bipolar disorder with (n = 192) and without psychosis (n = 67), and 280 healthy comparison participants with a SST and the Brief Assessment of Cognition in Schizophrenia (BACS), a measure of general cognitive ability. RESULTS: All patient groups had a similar degree of impaired inhibitory control over prepotent responses. However, bipolar groups differed from schizophrenia and schizoaffective groups in showing speeded responses and inhibition errors that were not accounted for by general cognitive ability. Schizophrenia and schizoaffective groups had a broader set of deficits on inhibition and greater general cognitive deficit, which fully accounted for the inhibition deficits. No differences were found between the clinically well-matched bipolar with and without psychosis groups, including for inhibitory control or general cognitive ability. CONCLUSIONS: We conclude that 1) while impaired inhibitory control on a SST is of similar magnitude across the schizo-bipolar spectrum, including nonpsychotic bipolar, different mechanisms may underlie the impairments, and 2) history of psychosis in bipolar disorder does not differentially impact inhibitory behavioral control or general cognitive abilities.

Electrophysiological correlates of emotional scene processing in bipolar disorder.

Emotional dysfunction is a core feature of bipolar I disorder (BD). Behavioral data suggest that emotional processing may differ based on history of psychosis, but physiological studies frequently disregard this differentiating feature. Face processing studies indicate that emotion-related components of event-related potentials (ERPs) are abnormal in BD, but fMRI data using emotional scenes are mixed. The current study used ERPs to examine emotional scene perception in BD with and without a history of psychosis (BDP, BDNP). 386 participants from the PARDIP consortium (HC = 181, BDP = 130, BDNP = 75) viewed neutral, pleasant, and unpleasant scenes from the International Affective Picture System (IAPS) during continuous EEG recording. The early posterior negativity (EPN) and late positive potential (LPP) were examined for group and stimulus effects. Analyses were conducted for groups on and off medications to examine associations between medication status, psychosis, and ERP response. Group differences were found between HC and BD in emotional modulation of the EPN and between HC and BDP in the LPP to pleasant images. There was a significant interaction between psychosis history and anticonvulsant status in the EPN, but no other medication associations were found. The relationship between neural/self-reported emotional responses and clinical symptoms were examined with canonical correlations, but no significant associations were found. Results from this large well characterized sample indicate mild deviations in neural reactivity related to medication, mood, and psychosis history. However, processing of emotional scenes appears mostly intact in individuals with BD regardless of symptom severity.

Smooth pursuit eye movement deficits as a biomarker for psychotic features in bipolar disorder-Findings from the PARDIP study.

OBJECTIVES: Smooth pursuit eye movement deficits are an established psychosis biomarker across schizophrenia, schizoaffective and psychotic bipolar disorder (BPwP). Whether smooth pursuit deficits are also seen in bipolar disorder without psychosis (BPwoP) is unclear. Here we present data from the Psychosis and Affective Research Domains and Intermediate Phenotypes (PARDIP) study comparing bipolar patients with and without psychotic features. METHODS: Probands with BPwP (N = 49) and BPwoP (N = 36), and healthy controls (HC, N = 71) performed eye tracking tasks designed to evaluate specific sensorimotor components relevant for pursuit initiation and pursuit maintenance. RESULTS: While BPwoP did not differ from either BPwP or HC on initial eye acceleration, they performed significantly better than BPwP on early (P < .01) and predictive (P = .02) pursuit maintenance measures, both without differing from HC. BPwP were impaired compared to HC on initial eye acceleration, and on early and predictive pursuit maintenance (all P < .01). In contrast to the three pursuit measures, BPwP and BPwoP were both impaired on general neurocognitive assessments in relation to HC (both P < .001), without a significant difference between the two bipolar patient groups. CONCLUSIONS: Our findings support the model that impairments of sensorimotor and cognitive processing as required for early and later predictive smooth pursuit maintenance are relatively specific to those bipolar patients with a history of psychosis. This suggests that the neural circuitry for developing feed-forward predictive models for accurate pursuit maintenance is associated with the occurrence of psychotic features in bipolar patients. In contrast, generalized neuropsychological impairments did not differentiate the two bipolar patient groups.

Auditory paired-stimuli responses across the psychosis and bipolar spectrum and their relationship to clinical features.

Background: EEG responses during auditory paired-stimuli paradigms are putative biomarkers of psychosis syndromes. The initial iteration of the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP1) showed unique and common patterns of abnormalities across schizophrenia (SZ), schizoaffective disorder (SAD), and bipolar disorder with psychosis (BDP). This study replicates those findings in new and large samples of psychosis cases and extends them to an important comparison group, bipolar disorder without psychosis (BDNP). Methods: Paired stimuli responses from 64-sensor EEG recording were compared across psychosis (n = 597; SZ = 225, SAD = 201, BDP = 171), BDNP (n = 66), and healthy (n = 415) subjects from the second iteration of B-SNIP. EEG activity was analyzed in voltage and in the time-frequency domain. Principal component analysis (PCA) over sensors (sPCA) was used to efficiently capture EEG voltage responses to the paired stimuli. Evoked power was calculated via a Morlet wavelet procedure. A frequency PCA divided evoked power data into three frequency bands: Low (4-17 Hz), Beta (18-32 Hz), and Gamma (33-55 Hz). Each time-course (ERP Voltage, Low, Beta, and Gamma) were then segmented into 20 ms bins and analyzed for group differences. To efficiently summarize the multiple EEG components that best captured group differences we used multivariate discriminant and correlational analyses. This approach yields a reduced set of measures that may be useful in subsequent biomarker investigations. Results: Group ANOVAs identified 17 time-ranges that showed significant group differences (p < .05 after FDR correction), constructively replicating B-SNIP1 findings. Multivariate linear discriminant analysis parsimoniously selected variables that best accounted for group differences: The P50 response to S1 and S2 uniquely separated BDNP from healthy and psychosis subjects (BDNP > all other groups); the S1 N100 response separated groups along an axis of psychopathology severity (HC > BDNP > BDP > SAD > SZ); the S1 P200 response indexed psychosis psychopathology (HC/BDNP > SAD/SZ/BDP); and the preparatory period to the S2 stimulus separated SZ from other groups (SZ > SAD/BDP>HC/BDNP).Canonical correlation identified an association between the neural responses during the S1 N100, S1 N200 and S2 preparatory period and PANSS positive symptoms and social functioning. The neural responses during the S1 P50 and S1 N100 were associated with PANSS Negative/General, MADRS and Young Mania symptoms. Conclusions: This study constructively replicated prior B-SNIP1 research on auditory deviations observed during the paired stimuli task in SZ, SAD and BDP. Inclusion of a group of BDNP allows for the identification of biomarkers more closely related to affective versus nonaffective clinical phenotypes and neural distinctions between BDP and BDNP. Findings have implications for nosology and future translational work given that some biomarkers are shared across all psychosis and some are unique to affective syndromes.

Early and late auditory information processing show opposing deviations in aniridia.

Aniridia is a congenital disorder, predominantly caused by heterozygous mutations of the PAX6 gene. While ocular defects have been extensively characterized in this population, brain-related anatomical and functional abnormalities are emerging as a prominent feature of the disorder. Individuals with aniridia frequently exhibit auditory processing deficits despite normal audiograms. While previous studies have reported hypoplasia of the anterior commissure and corpus callosum in some of these individuals, the neurophysiological basis of these impairments remains unexplored. This study provides direct assessment of neural activity related to auditory processing in aniridia. Participants were presented with tones designed to elicit an auditory steady-state response (ASSR) at 22 Hz, 40 Hz, and 84 Hz, and infrequent broadband target tones to maintain attention during electroencephalography (EEG) recording. Persons with aniridia showed increased early cortical responses (P50 AEP) in response to all tones, and increased high-frequency oscillatory entrainment (84 Hz ASSR). In contrast, this group showed a decreased cortical integration response (P300 AEP to target tones) and reduced neural entrainment to cortical beta-band stimuli (22 Hz ASSR). Collectively, our results suggest that subcortical and early cortical auditory processing is augmented in aniridia, while functional cortical integration of auditory information is deficient in this population.