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Background Atypical auditory processing (AAP) in psychotic psychopathology is evident in early (N1), mid-latency (P2/N2/mismatch negativity), and late (P3) neural responses. The influence of attention on AAP, and how temporal stages of AAP are associated with phenomenology of psychotic psychopathology are not well understood. Methods We used a directed attention oddball task to characterize stages of AAP in psychosis and to examine the influence of selective attention. Ninety patients with schizophrenia (SCZ), 53 patients with bipolar disorder (BP), 90 healthy controls and 72 first-degree relatives of SCZ (SREL) were studied. We used principal components analysis to decompose average-reference 64-channel subject-level ERPs. Results Altered attentional modulation was evident in SCZ at early (N1 factor) and late (P3 factor) stages of AAP, but not at mid-latency P2 factor. Irrespective of condition, N1 and P3 were reduced in SCZ, which predicted greater psychopathology and schizotypal personality traits. Diminished mid-latency mismatch detection (P2 factor) was evident in SCZ, BP, and SREL and was associated with greater positive symptoms of psychosis as well as self-reported atypical cognitive-perceptual experiences. Conclusions Attentional modulation of early N1, and later P3 neural responses was atypical in patients, but the degree of attentional modulation did not relate to symptom severity or schizotypal traits. Our findings suggest the link between mid-latency mismatch detection and atypical cognitive/perceptual experiences is not driven by attentional deficits alone and point to the promise of mid-latency mismatch detection as a candidate endophenotype and intervention target.

BACKGROUND: People with schizophrenia (SZ) have deficits in context processing (CP), which refers to an executive process that guides adaptive behaviors according to goals and stored contextual information. Similar deficits were also found in their biological relatives, suggesting that CP-related dysfunctions might be endophenotypic markers of schizophrenia that reflect central pathology of the disorder. Abnormal cortical neural oscillations might be the brain mechanisms underlying CP deficits in schizophrenia. However, the precise spatial, temporal, and frequency abnormalities associated with the illness and genetic liability of schizophrenia are largely unknown. METHODS: We analyzed high-density electroencephalography (HD-EEG) and functional MRI data collected from 22 SZ, 20 biological relatives of SZ (RSZ), and 30 healthy controls [HC]) during an optimized CP task called stimulus response reversal task (SRRT). ExGaussian reaction time (RT) distribution analysis was used to determine abnormalities in intra-individual RT variability in CP. We identified fMRI cortical regions of interest (ROIs) activated for CP, then the ROI source signals of HD-EEG were computed using individual realistic head models and a source localization algorithm employing boundary element method (BEM). Cohen’s class time-frequency (TF) measures of the ROI signals were computed to define accurate time and frequency dynamics of CP-related cortical oscillations in high and low CP (HCP and LCP) load conditions. RESULTS: RSZ were normal in all behavioral performance indices, and SZ were also normal in response accuracy and motor speed (RT-mu). However, SZ had larger response instability (RT-sigma) than HC only in HCP trials, suggesting their specific deficits in contextual motor control. We identified task-related fMRI ROIs including dorsal middle frontal gyrus (dMFG), inferior middle frontal gyrus (iMFG), inferior frontal gyrus (IFG), inferior parietal lobules (IPL), anterior cingulate cortex (ACC), motor cortex (MC), and middle occipital gyrus (mOG) in the both hemispheres. TF analyses of the ROI signals in 3 time-windows of the task trials identified CP-related neural oscillatory activities (HCP-LCP differences) in low-frequency (1–5 Hz) event-related synchrony (LF-ERS) and alpha band (8–12 Hz) event-related desynchrony (A-ERD) that varied across the groups. Unlike HC who had simultaneous LF-ERS increases in dMFG and IPL during contextual cue encoding for HCP trials, SZ and RSZ had LF-ERS increases only in IFG and iMFG respectively. During delay period (maintenance of cue information) in HCP trials, HC had increased LF-ERS in dMFG and IPL, while RSZ had increased LF-ERS in iMFG. In contrast, SZ had A-ERD increases in mOG during delays in HCP trials. The HCP-related RT-sigma increases in SZ were predicted by their CP-related LF-ERS (1–4 Hz) during maintenance (1300–1500 ms after cue onsets) in IPL (r=-.71, p=.002). Before responses to probes in HCP trials where response conflicts should be resolved, HC had LF-ERS increases in dMFG, ACC, and IPL while RSZ had such increases in iMFG, ACC, and MC. In contrast, SZ had increases in pre-response A-ERD for HCP trials in mOG and MC. DISCUSSION: Results suggested that SZ and RSZ had common deficits in LF-ERS of the dorsal prefrontal and parietal network, but they utilized resources of other cortical regions to compensate their core deficits in CP. HCP-specific response instability in SZ might be caused by their parietal dysfunction to update contextual rules and additional ACC-motor dysfunctions. In summary, CP-related deficits in the dorsal prefrontal-parietal network might be the endophenotypic markers of schizophrenia, while ACC-motor cortical deficits might be disease-specific marker unique to SZ.

Disruption of visual percepts by a subsequent stimulus (ie, backward masking) has been consistently noted in schizophrenia, with some evidence that this fragility in early perception is present in people with genetic liability for the disorder. Given the potential of backward masking paradigms to mark neural processes that confer risk for schizophrenia, it is important to test the diagnostic specificity of abnormalities in visual perception. To more fully assess whether masking visual stimuli reveals a marker of genetic liability (ie, endophenotype) specific to schizophrenia, we tested 44 people with the disorder, 29 people with bipolar disorder, 56 first-degree biological relatives of people with schizophrenia, 26 first-degree biological relatives of people with bipolar disorder, and 43 nonpsychiatric control participants using a magnocellular-biased visual backward masking procedure that included target-to-mask onset asynchronies ranging from 0 to 80 ms. Relatives of people with schizophrenia who were without schizophrenia spectrum disorders exhibited impaired performance compared with nonpsychiatric control participants and relatives of people with bipolar disorder when a visual mask interrupted early perception (eg, 27 ms). A similar vulnerability of early processes was noted in people with schizophrenia, yet they also had impaired performance when masks occurred at later time points (ie, 80 ms). Performance deficits were not attributable to intellectual function, measures of attention and memory, symptomatology, or medication dosage. Bipolar patients and their relatives failed to exhibit deficits on the backward masking task. Fragility of early visual percepts appears to mark genetic liability specific to schizophrenia and may serve as an endophenotype for the disorder.

The lack of consistency of genetic associations in highly heritable mental illnesses, such as schizophrenia, remains a challenge in molecular psychiatry. Because clinical phenotypes for psychiatric disorders are often ill defined, considerable effort has been made to relate genetic polymorphisms to underlying physiological aspects of schizophrenia (so called intermediate phenotypes), that may be more reliable. Given the polygenic etiology of schizophrenia, the aim of this work was to form a measure of cumulative genetic risk and study its effect on neural activity during working memory (WM) using functional magnetic resonance imaging. Neural activity during the Sternberg Item Recognition Paradigm was measured in 79 schizophrenia patients and 99 healthy controls. Participants were genotyped, and a genetic risk score (GRS), which combined the additive effects of 41 single-nucleotide polymorphisms (SNPs) from 34 risk genes for schizophrenia, was calculated. These risk SNPs were chosen according to the continuously updated meta-analysis of genetic studies on schizophrenia available at www.schizophreniaresearchforum.org. We found a positive relationship between GRS and left dorsolateral prefrontal cortex inefficiency during WM processing. GRS was not correlated with age, performance, intelligence, or medication effects and did not differ between acquisition sites, gender, or diagnostic groups. Our study suggests that cumulative genetic risk, combining the impact of many genes with small effects, is associated with a known brain-based intermediate phenotype for schizophrenia. The GRS approach could provide an advantage over studying single genes in studies focusing on the genetic basis of polygenic conditions such as neuropsychiatric disorders.

Background: Resting state neural activity accounts for a majority of metabolic energy consumed by the brain. Although functional magnetic resonance imaging has been useful for identifying neuroanatomical networks active during resting state, the dynamic activity within these networks is more richly described through electroencephalography (EEG) which captures high frequency oscillations cycling through cortical networks and subcortical nuclei. In order to better understand how resting-state activity may explain the phenomenology of psychotic psychopathology, we mapped the dynamics of resting state networks onto dimensions of symptomatology typically noted in schizophrenia, schizoaffective, and bipolar disorder. Subthreshold symptomatology was also examined in first-degree biological relatives of patients. Methods: Participants were enrolled in a family study of schizophrenia. Families affected by bipolar disorder and healthy controls were included for comparison. Resting EEG data were acquired during eyes open and eyes closed states. Dynamics of neural connectivity were operationalized through computing phase locking values for a broad range of EEG frequencies (1–55 Hz) for recordings across the scalp. Participants also completed diagnostic interviews, symptom rating assessments, measures of schizotypal personality factors, and cognitive testing. Results: Principal component analysis (PCA) of phase-locking values yielded 4 fundamental frequencies around which neural synchronization occurred (Delta/Theta, Alpha, Beta, Gamma). Spatial PCAs revealed four resting state oscillatory networks for each of the frequency components. The oscillatory networks were highly similar across the frequency components suggesting the existence of neuroanatomical pathways shared by frequencies during resting state cycles. The four spatial networks were identified as frontal–central–parietal, frontal interhemispheric, posterior interhemispheric, and generalized long range. A diagnosis of schizophrenia was associated with increased interhemispheric frontal synchronization in delta/theta and alpha frequency components. The frontal low frequency abnormalities were associated with lifetime negative symptoms, reality distortion, and positive formal disorder. Frontal interhemispheric delta/theta synchronization was also associated with cluster A symptoms in biological family members of individuals with schizophrenia. Conclusion: Evidence suggests that different oscillatory frequencies share neuroanatomical structures in resting state networks. Psychosis is associated with increased low frequency synchronization between frontal brain regions. The low frequency abnormalities are also predictive of psychotic symptomatology and genetic liability for schizophrenia.

We evaluated whether abnormal frequency composition of the resting state electroencephalogram (EEG) in schizophrenia was associated with genetic liability for the disorder by studying first-degree biological relatives of schizophrenia patients. The study included a data-driven method for defining EEG frequency components and determined the specificity of resting state EEG frequency abnormalities by assessing schizophrenia patients, bipolar disorder patients, and relatives of both patient groups. Schizophrenia patients and their relatives, but not bipolar patients or their relatives, exhibited increased high-frequency activity (beta) providing evidence for disturbances in resting state brain activity being specific to genetic liability for schizophrenia. Schizophrenia patients exhibited augmented low-frequency EEG activity (delta, theta), while bipolar disorder patients and the 2 groups of relatives generally failed to manifest similar low-frequency EEG abnormalities. The Val(158)Met polymorphism for the catechol-O-methyl transferase (COMT) gene was most strongly associated with delta and theta activity in schizophrenia patients. Met homozygote schizophrenia patients exhibited augmented activity for the 2 low-frequency bands compared with control subjects. Excessive high-frequency EEG activity over frontal brain regions may serve as an endophenotype that reflects cortical expression of genetic vulnerability for schizophrenia. Low-frequency resting state EEG anomalies in schizophrenia may relate to disorder-specific pathophysiology in schizophrenia and the influence of the COMT gene on tonic dopamanergic function.