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Special Issue: The ENIGMA Consortium: the first 10 years., Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more-convex-than-concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta-analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia., Center for Integrated Healthcare, U.S. Department of Veterans Affairs, Grant/Award Number: I01 CX000497; Commonwealth Health Research Board, Grant/Award Number: HRA_POR/2011/100; Conselho Nacional de Desenvolvimento Científico e Tecnológico, Grant/Award Numbers: 478466/2009, 480370/2009; Department of Energy, Labor and Economic Growth, Grant/Award Number: DE-FG02-99ER62764; Forskningsrådet om Hälsa, Arbetsliv och Välfärd, Grant/Award Numbers: K2009-62X-15077-06-3, K2012-61X-15077-09-3, 523-2014-3467, 2009-7053, 2013-2838; Fundação Amazônia Paraense de Amparo à Pesquisa, Grant/Award Numbers: 2009/14891-9, 2010/18672-7, 2012/23796-2, 2013/039; Instituto de Salud Carlos III, Grant/Award Numbers: FIS 00/3095, 01/3129, PI020499, PI060507, PI10/001; National Health and Medical Research Council, Grant/Award Numbers: 1009064, 496682; National Institutes of Health, Grant/Award Numbers: 1RC1MH089257, MH 60722, MH019112, MH064045, MH085096, MH098130, MO1 RR025758, P41RR14075, P50 MH071616, R01 DA053028, R01 EB020062, R01 HD050735, R01 MH056584, R01 MH084803, R01 MH116147, R01 MH117601, R01EB005846, R01EB015611, R01MH074797, R21 MH097196, R21MH097196, R37MH43375, S10 OD023696, T32 AG058507, T32 MH073526, TR000153, U01 MH097435, U24 RR021382A, U24 RR021992, U24 RR025736, U24 RR21992, U24RR021992, U54 EB020403, U54EB020403, UL1 TR000153; National Science Foundation, Grant/Award Numbers: 1636893, 1734853; Norges Forskningsråd, Grant/Award Numbers: 213837, 217776, 223273; Science Foundation Ireland, Grant/Award Numbers: 08/IN.1/B1916, 12/IP/1359; Wellcome Trust, Grant/Award Number: 072894/2/03/Z.

BackgroundSchizophrenia is associated with aberrant gamma band power, hypothesized to reflect imbalance in the excitation-inhibition (E/I) ratio and undermine neural signal efficiency. Relationships between resting-state gamma, E/I balance, and regional hemodynamics from the fMRI BOLD signal are unknown.MethodsWe recorded simultaneous EEG-fMRI at rest, with eyes open, in people with schizophrenia (n= 57) and people without a psychiatric diagnosis (n= 46) and identified gamma and aperiodic EEG parameters associated with E/I balance. Measures from all EEG channels were entered into a whole-brain, parametric modulation analysis followed by statistical correction for multiple comparisons. Sensory gating was assessed using the Sensory Gating Inventory, and psychotic symptoms were assessed using the Positive and Negative Syndrome Scale.ResultsAcross groups, gamma power modestly predicts a steeper aperiodic slope (greater inhibition), without group differences in either gamma power or aperiodic slope. In schizophrenia, gamma-BOLD coupling was reduced in bilateral auditory regions of the superior temporal gyri and inversely correlated with sensory gating deficits and symptom severity. Analysis of the spectral features of scanner sounds revealed distinct peaks in the gamma range, reflecting a rapidly repeating scanner pulse sound present throughout the resting state recording.ConclusionRegional hemodynamic support for putative inhibitory and excitatory contributions to resting EEG are aberrant in SZ. Deficient gamma coupling to auditory BOLD may reflect impaired gating of fMRI-scanner sound.

In this work, we focus on explicitly nonlinear relationships in functional networks. We introduce a technique using normalized mutual information (MI), that calculates the nonlinear correlation between different brain regions. We demonstrate our proposed approach using simulated data, then apply it to a dataset previously studied in (Damaraju et al., 2014). This resting-state fMRI data included 151 schizophrenia patients and 163 age- and gender-matched healthy controls. We first decomposed these data using group independent component analysis (ICA) and yielded 47 functionally relevant intrinsic connectivity networks. Our analysis showed a modularized nonlinear relationship among brain functional networks that was particularly noticeable in the sensory and visual cortex. Interestingly, the modularity appears both meaningful and distinct from that revealed by the linear approach. Group analysis identified significant differences in nonlinear dependencies between schizophrenia patients and healthy controls particularly in visual cortex, with controls showing more nonlinearity in most cases. Certain domains, including cognitive control, and default mode, appeared much less nonlinear, whereas links between the visual and other domains showed evidence of substantial nonlinear and modular properties. Overall, these results suggest that quantifying nonlinear dependencies of functional connectivity may provide a complementary and potentially important tool for studying brain function by exposing relevant variation that is typically ignored.Further, we propose a method that captures both linear and nonlinear effects in a ‘boosted’ approach. This method increases the sensitivity to group differences in comparison to the standard linear approach, at the cost of being unable to separate linear and nonlinear effects.

There is growing evidence that rather than using a single brain imaging modality to study its association with physiological or symptomatic features, the field is paying more attention to fusion of multimodal information. However, most current multimodal fusion approaches that incorporate functional magnetic resonance imaging (fMRI) are restricted to second-level 3D features, rather than the original 4D fMRI data. This trade-off is that the valuable temporal information is not utilized during the fusion step. Here we are motivated to propose a novel approach called "parallel group ICA+ICA" that incorporates temporal fMRI information from group independent component analysis (GICA) into a parallel independent component analysis (ICA) framework, aiming to enable direct fusion of first-level fMRI features with other modalities (e.g., structural MRI), which thus can detect linked functional network variability and structural covariations. Simulation results show that the proposed method yields accurate intermodality linkage detection regardless of whether it is strong or weak. When applied to real data, we identified one pair of significantly associated fMRI-sMRI components that show group difference between schizophrenia and controls in both modalities, and this linkage can be replicated in an independent cohort. Finally, multiple cognitive domain scores can be predicted by the features identified in the linked component pair by our proposed method. We also show these multimodal brain features can predict multiple cognitive scores in an independent cohort. Overall, results demonstrate the ability of parallel GICA+ICA to estimate joint information from 4D and 3D data without discarding much of the available information up front, and the potential for using this approach to identify imaging biomarkers to study brain disorders.

In 1999, Kwon et al. reported several electroencephalographic gamma band auditory steady-state response (ASSR) abnormalities in schizophrenia, spawning approximately 100 subsequent studies. While many studies replicated the finding of reduced 40-Hz ASSR power in schizophrenia and extended this by showing that 40-Hz phase synchrony (phase-locking factor [PLF]) was also reduced, none attempted to replicate the original phase delay finding of Kwon et al. Accordingly, we measured the 40-Hz ASSR phase-locking angle (PLA) to assess phase delay and examined its differential sensitivity to schizophrenia, relative to power and PLF measures.To obtain ASSRs, electroencephalography data were recorded from 28 patients with schizophrenia and 25 healthy control subjects listening to repeated 40-Hz 500-ms click trains. Evoked power, total power, PLF, and PLA were calculated after Morlet wavelet time-frequency decomposition of single trial data from electrode Fz.In patients with schizophrenia, 40-Hz PLA was significantly reduced (i.e., phase delayed) (p.0001) and was unrelated to reductions in their 40-Hz power or PLF. PLA discriminated patients from healthy control subjects with 85% accuracy compared with 67% for power and 65% for PLF.Consistent with the original Kwon et al. study, 40-Hz click train-driven gamma oscillations were phase delayed in schizophrenia. Importantly, this phase delay abnormality was substantially larger than the gamma power and phase synchrony abnormalities that have been the focus of prior 40-Hz ASSR studies in schizophrenia. PLA provides a unique neurobiological measure of gamma band abnormalities in schizophrenia, likely reflecting a distinct pathophysiological mechanism from those underlying PLF and power abnormalities.

The error-related negativity (ERN) and error-positivity (Pe) are commonly linked to error-detection and strategic processing. Studies have documented the influence of conflict probability on ERN amplitude. However, the influence of conflict probability on ERN/Pe in schizophrenia, where such components are reduced, is unknown. A modified flanker paradigm was used to examine how the probability of conflict modulates ERN and Pe amplitudes in patients with schizophrenia (n = 33) and healthy controls (n = 25). Increased ERN was observed in response to errors on low probability, incongruent trials. No such differences were observed in Pe. While ERN and Pe showed significantly reduced amplitudes in patients relative to controls, patients showed normal condition-dependent ERN and reaction-time modulation. This suggests that while the neural mechanisms generating the ERN and Pe are compromised in schizophrenia, those modulating task performance strategy and neurophysiological responses to errors based on conflict probability are intact.

Identification of neurophysiological abnormalities associated with schizophrenia that predate and predict psychosis onset may improve clinical prediction in the psychosis risk syndrome (PRS) and help elucidate the pathogenesis of schizophrenia. Amplitude reduction of the P300 event-related potential component reflects attention-mediated processing deficits and is among the most replicated biological findings in schizophrenia, making it a candidate biomarker of psychosis risk. The relative extent to which deficits in P300 amplitudes elicited by auditory and visual oddball stimuli precede psychosis onset during the PRS and predict transition to psychosis, however, remains unclear. Forty-three individuals meeting PRS criteria, 19 schizophrenia patients, and 43 healthy control (HC) participants completed baseline electroencephalography recording during separate auditory and visual oddball tasks. Two subcomponents of P300 were measured: P3b, elicited by infrequent target stimuli, and P3a, elicited by infrequent nontarget novel stimuli. Auditory and visual target P3b and novel P3a amplitudes were reduced in PRS and schizophrenia participants relative to HC participants. In addition, baseline auditory and visual target P3b, but not novel P3a, amplitudes were reduced in 15 PRS participants who later converted to psychosis, relative to 18 PRS non-converters who were followed for at least 22 months. Furthermore, target P3b amplitudes predicted time to psychosis onset among PRS participants. These results suggest that P300 amplitude deficits across auditory and visual modalities emerge early in the schizophrenia illness course and precede onset of full psychosis. Moreover, target P3b may represent an important neurophysiological vulnerability marker of the imminence of risk for psychosis.

BackgroundSchizophrenia (SZ) is associated with thalamic dysconnectivity. Compared to healthy controls (HCs), individuals with SZ have hyperconnectivity with sensory regions, and hypoconnectivity with cerebellar, thalamic, and prefrontal regions. Despite replication of this pattern in chronically ill individuals, less is known about when these abnormalities emerge in the illness course and if they are present prior to illness onset.MethodsResting-state functional magnetic resonance imaging data were collected from psychosis risk syndrome (PRS) youth (n = 45), early illness SZ (ESZ) (n = 74) patients, and HCs (n = 85). Age-adjusted functional connectivity, seeded from the thalamus, was compared among the groups.ResultsSignificant effects of group were observed in left and right middle temporal regions, left and right superior temporal regions, left cerebellum, and bilateral thalamus. Compared to HCs, ESZ demonstrated hyperconnectivity to all temporal lobe regions and reduced connectivity with cerebellar, anterior cingulate, and thalamic regions. Compared to HCs, PRS demonstrated hyperconnectivity with the left and right middle temporal regions, and hypoconnectivity with the cerebellar and other thalamic regions. Compared to PRS participants, ESZ participants were hyperconnected to temporal regions, but did not differ from PRS in hypoconnectivity with cerebellar and thalamic regions. Thalamic dysconnectivity was unrelated to positive symptom severity in ESZ or PRS groups.ConclusionsPRS individuals demonstrated an intermediate level of thalamic dysconnectivity, whereas ESZ showed a pattern consistent with prior observations in chronic samples. These cross-sectional findings suggest that thalamic dysconnectivity may occur prior to illness onset and become more pronounced in early illness stages.

BackgroundSchizophrenia affects around 1% of the global population. Functional connectivity extracted from resting-state functional magnetic resonance imaging (rs-fMRI) has previously been used to study schizophrenia and has great potential to provide novel insights into the disorder. Some studies have shown abnormal functional connectivity in the default mode network of individuals with schizophrenia, and more recent studies have shown abnormal dynamic functional connectivity (dFC) in individuals with schizophrenia. However, DMN dFC and the link between abnormal DMN dFC and symptom severity have not been well characterized.MethodResting-state fMRI data from subjects with schizophrenia (SZ) and healthy controls (HC) across two datasets were analyzed independently. We captured seven maximally independent subnodes in the DMN by applying group independent component analysis and estimated dFC between subnode time courses using a sliding window approach. A clustering method separated the dFCs into five reoccurring brain states. A feature selection method modeled the difference between SZs and HCs using the state-specific FC features. Finally, we used the transition probability of a hidden Markov model to characterize the link between symptom severity and dFC in SZ subjects.ResultsWe found decreases in the connectivity of the anterior cingulate cortex (ACC) and increases in the connectivity between the precuneus (PCu) and the posterior cingulate cortex (PCC) (i.e., PCu/PCC) of SZ subjects. In SZ, the transition probability from a state with weaker PCu/PCC and stronger ACC connectivity to a state with stronger PCu/PCC and weaker ACC connectivity increased with symptom severity.ConclusionsTo our knowledge, this was the first study to investigate DMN dFC and its link to schizophrenia symptom severity. We identified reproducible neural states in a data-driven manner and demonstrated that the strength of connectivity within those states differed between SZs and HCs. Additionally, we identified a relationship between SZ symptom severity and the dynamics of DMN functional connectivity. We validated our results across two datasets. These results support the potential of dFC for use as a biomarker of schizophrenia and shed new light upon the relationship between schizophrenia and DMN dynamics.

BackgroundDeficits in the way the brain processes rewards may contribute to negative symptoms in schizophrenia. Synchronization of alpha band neural oscillations is a dominant EEG signal when people are awake, but at rest. In contrast, alpha desynchronization to salient events is thought to direct allocation of information processing resources away from the internal state, to process salient stimuli in the external environment. Here, we hypothesize that alpha event-related desynchronization (ERD) during reward processing is altered in schizophrenia, leading to less difference in alpha ERD magnitude between winning and losing outcomes.MethodsEEG was recorded while participants (patients with schizophrenia (SZ)=54; healthy controls (HC) = 54) completed a casino-style slot machine gambling task. Total power, a measure of neural oscillation magnitude was measured in the alpha frequency range (8-14 Hz), time-locked to reward delivery, extracted via principal components analysis, and then compared between groups and equiprobable win and near miss loss reward outcomes. Associations between alpha power and negative symptoms and trait rumination were examined.ResultsA significant Group X Reward Outcome interaction (p=.018) was explained by differences within the HC group, driven by significant posterior-occipital alpha desynchronization to wins, relative to near miss losses (p.1), nor did alpha power relate to negative symptoms (p>.1). However, across all participants, less alpha ERD to reward outcomes was related to more trait rumination, for both wins (p=.005) and near-miss losses (p=.002), with no group differences observed in the slopes of these relationships.ConclusionThese findings suggest that event-related modulation of alpha power is altered in schizophrenia during reward outcome processing, even when reward attainment places minimal demands on higher-order cognitive processes during slot machine play. In addition, high trait rumination is associated with less event-related desynchronization to reward feedback, suggesting that rumination covaries with less external attentional allocation to reward processing, regardless of reward outcome valence and group membership.

The hallmark of resting EEG spectra are distinct rhythms emerging from a broadband, aperiodic background. This aperiodic neural signature accounts for most of total EEG power, although its significance and relation to functional neuroanatomy remains obscure. We hypothesized that aperiodic EEG reflects a significant metabolic expenditure and therefore might be associated with the default mode network while at rest. During eyes-open, resting-state recordings of simultaneous EEG-fMRI, we find that aperiodic and periodic components of EEG power are only minimally associated with activity in the default mode network. However, a whole-brain analysis identifies increases in aperiodic power correlated with hemodynamic activity in an auditory-salience-cerebellar network, and decreases in aperiodic power are correlated with hemodynamic activity in prefrontal regions. Desynchronization in residual alpha and beta power is associated with visual and sensorimotor hemodynamic activity, respectively. These findings suggest that resting-state EEG signals acquired in an fMRI scanner reflect a balance of top-down and bottom-up stimulus processing, even in the absence of an explicit task.HIGHLIGHTSPeriodic and aperiodic EEG parameters associated with distinct resting-state networksIncreases in aperiodic power associated with an auditory-salience-cerebellar networkDecreases in aperiodic power associated with prefrontal regionsGlobal neural excitability may reflect stimulus processing or arousal attributable to the uniqueness of the resting-state MR-scanner environment

We introduce an extension of independent component analysis (ICA), called multiscale ICA (msICA), and design an approach to capture dynamic functional source interactions within and between multiple spatial scales. msICA estimates functional sources at multiple spatial scales without imposing direct constraints on the size of functional sources, overcomes the limitation of using fixed anatomical locations, and eliminates the need for model-order selection in ICA analysis. We leveraged this approach to study sex-specific and -common connectivity patterns in schizophrenia.Results show dynamic reconfiguration and interaction within and between multi-spatial scales. Sex-specific differences occur (1) within the subcortical domain, (2) between the somatomotor and cerebellum domains, and (3) between the temporal domain and several others, including the subcortical, visual, and default mode domains. Most of the sex-specific differences belong to between-spatial scale functional interactions and are associated with a dynamic state with strong functional interactions between the visual, somatomotor, and temporal domains and their anticorrelation patterns with the rest of the brain. We observed significant correlations between multi-spatial scale functional interactions and symptom scores, highlighting the importance of multiscale analyses to identify potential biomarkers for schizophrenia. As such, we recommend such analyses as an important option for future functional connectivity studies.

Slot machines are a popular form of gambling, offering a tractable way to experimentally model reward processes. This study used a 3-reel slot paradigm to assess psychologically distinct phases of reward processing, reflecting anticipation, and early- and late-stage outcome processing. EEG measures of winning, nearly missing (a losing outcome revealed at the final, third reel), and “totally” missing (a losing outcome revealed earlier, at the second reel) were collected from healthy adults (n=54). Condition effects were evaluated in: i) event-related potential (ERP) components reflecting anticipatory attention (stimulus preceding negativity, SPN) and outcome processing (reward positivity, RewP and late-positive potential, LPP) and ii) total power and phase synchrony of theta and delta band oscillations. Behaviorally, trial initiation was fastest after a near miss outcome and slowest after a winning outcome. As expected, a significant SPN was observed for possible wins (AA) vs. total misses (AB), consistent with reward anticipation. Larger win (AAA) vs. near miss (AAB) amplitudes were observed for the RewP; LPP amplitudes were largest for wins (AAA), intermediate for near misses (AAB), and smallest for total misses (ABC), reflecting significant early (RewP) and late-stage (LPP) outcome processing effects. There was an effect of reel position on the RewP, with larger amplitude in the final reel (AAA-AAB) relative to the 2nd-reel locked difference waves (AA-AB). Across all outcomes, near misses elicited the largest and most phase-synchronized theta responses, while wins elicited larger and more phase-synchronized delta responses than total misses, with delta band measures not distinguishing between near misses and wins. . Phase locking measures contrasting win vs. near miss delta and theta synchronization, within time windows corresponding to ERP measurements, covaried with RewP, but not SPN or LPP, amplitude. Lastly, EEG measures showed differential relationships with age and self-reported consummatory pleasure. In the context of slot machine play, where reward anticipation and attainment place minimal demands on effort and skill, ERP and time-frequency methods capture distinct neurophysiological signatures of reward anticipation and outcome processing.

Long-term potentiation (LTP) is a form of experience-dependent synaptic plasticity mediated by glutamatergic transmission at N-methyl-D-aspartate receptors (NMDARs). Impaired neuroplasticity has been implicated in the pathophysiology of schizophrenia, possibly due to underlying NMDAR hypofunction. Analogous to the high frequency electrical stimulation used to induce LTP in vitro and in vivo in animal models, repeated high frequency presentation of a visual stimulus in humans in vivo has been shown to induce enduring LTP-like neuroplastic changes in electroencephalography (EEG)-based visual evoked potentials (VEPs) elicited by the stimulus. Using this LTP-like visual plasticity paradigm, we previously showed that visual high-frequency stimulation (VHFS) induced sustained changes in VEP amplitudes in healthy controls, but not in patients with schizophrenia. Here, we extend this prior work by re-analyzing the EEG data underlying the VEPs, focusing on neuroplastic changes in stimulus-evoked EEG oscillatory activity following VHFS. EEG data were recorded from 19 patients with schizophrenia and 21 healthy controls during the visual plasticity paradigm. Event-related EEG oscillations (total power, intertrial phase coherence; ITC) elicited by a standard black and white checkerboard stimulus (~0.83 Hz, several 2-min blocks) were assessed before and after exposure to VHFS with the same stimulus (~8.9 Hz, 2 min). A cluster-based permutation testing approach was applied to time-frequency data to examine LTP-like plasticity effects following VHFS. VHFS enhanced theta band total power and ITC in healthy controls but not in patients with schizophrenia. The magnitude and phase synchrony of theta oscillations in response to a visual stimulus were enhanced for at least 22 min following VHFS, a frequency domain manifestation of LTP-like visual cortical plasticity. These theta oscillation changes are deficient in patients with schizophrenia, consistent with hypothesized NMDA receptor dysfunction.

Objective: A graph theoretical approach provides a powerful framework for discovering potential biomarkers of psychotic disorders. Comparing the brain graphs of the control and patient groups can help us to discover changes in mental disorders in a more convenient way. In this paper, we propose a novel tool to identify missing links associated with blocked paths (segregation) and new links associated with additional paths (abnormal integration) in estimated patient group’s time-varying graphs. We highlight the approach in an example application to the resting-state functional magnetic resonance imaging (fMRI) data of schizophrenia (SZ) patients. Methods: We first estimated whole-brain functional connectivity dynamics using a combination of spatial independent component analysis (ICA), sliding time window, and k-means clustering of windowed correlation matrices on resting-state fMRI data. The clusters are regarded as functional connectivity states, and each of them includes time intervals exhibiting similar connectivity patterns. We then estimated a Gaussian graphical model (GGM) for each state for both groups. To evaluate this approach, we compared different paths between brain components (nodes) of SZ and control groups’ graphs within each state by using the concept of connected components in graph theory. Results: We identified missing edges associated with disconnectivity (disconnectors) and showed there are additional edges in the SZ group graph that contribute to creating new paths in brain graphs. Conclusion: The proposed approach provides a tool for extracting time-varying graphs and identifying disconnectors associated with disconnectivity (absence of paths) and also connectors associated with abnormal integration (additional paths) in patient group graphs. Significance: We detected several missing links in SZ, both within and between functional domains, in particular within the subcortical (3 links) and somatomotor (4 links) domains. Interestingly, our proposed method identified new links within the somatomotor domain which may be related to a compensatory response in patients that warrants future study.

Background Dysfunctional reward processing is implicated in multiple mental disorders. Novelty seeking (NS) assesses preference for seeking novel experiences, which is linked to sensitivity to reward environmental cues. Methods A subset of 14-year-old adolescents (IMAGEN) with the top 20% ranked high-NS scores was used to identify high-NS–associated multimodal components by supervised fusion. These features were then used to longitudinally predict five different risk scales for the same and unseen subjects (an independent dataset of subjects at 19 years of age that was not used in predictive modeling training at 14 years of age) (within IMAGEN, n ≈ 1100) and even for the corresponding symptom scores of five types of patient cohorts (non-IMAGEN), including drinking (n = 313), smoking (n = 104), attention-deficit/hyperactivity disorder (n = 320), major depressive disorder (n = 81), and schizophrenia (n = 147), as well as to classify different patient groups with diagnostic labels. Results Multimodal biomarkers, including the prefrontal cortex, striatum, amygdala, and hippocampus, associated with high NS in 14-year-old adolescents were identified. The prediction models built on these features are able to longitudinally predict five different risk scales, including alcohol drinking, smoking, hyperactivity, depression, and psychosis for the same and unseen 19-year-old adolescents and even predict the corresponding symptom scores of five types of patient cohorts. Furthermore, the identified reward-related multimodal features can classify among attention-deficit/hyperactivity disorder, major depressive disorder, and schizophrenia with an accuracy of 87.2%. Conclusions Adolescents with higher NS scores can be used to reveal brain alterations in the reward-related system, implicating potential higher risk for subsequent development of multiple disorders. The identified high-NS–associated multimodal reward-related signatures may serve as a transdiagnostic neuroimaging biomarker to predict disease risks or severity.

Objective: Multimodal measurements of the same phenomena provide complementary information and highlight different perspectives, albeit each with their own limitations. A focus on a single modality may lead to incorrect inferences, which is especially important when a studied phenomenon is a disease. In this paper, we introduce a method that takes advantage of multimodal data in addressing the hypotheses of disconnectivity and dysfunction within schizophrenia (SZ). Methods: We start with estimating and visualizing links within and among extracted multimodal data features using a Gaussian graphical model (GGM). We then propose a modularity-based method that can be applied to the GGM to identify links that are associated with mental illness across a multimodal data set. Through simulation and real data, we show our approach reveals important information about disease-related network disruptions that are missed with a focus on a single modality. We use functional MRI (fMRI), diffusion MRI (dMRI), and structural MRI (sMRI) to compute the fractional amplitude of low frequency fluctuations (fALFF), fractional anisotropy (FA), and gray matter (GM) concentration maps. These three modalities are analyzed using our modularity method. Results: Our results show missing links that are only captured by the cross-modal information that may play an important role in disconnectivity between the components. Conclusion: We identified multimodal (fALFF, FA and GM) disconnectivity in the default mode network area in patients with SZ, which would not have been detectable in a single modality. Significance: The proposed approach provides an important new tool for capturing information that is distributed among multiple imaging modalities.

Highlights • Schizophrenia patients have intact reward anticipation and early stage reward outcome processing. • However, for patients early in their illness course, deficits were evident during late stage reward outcome processing. • Patients with schizophrenia who have an older neural brain age have worse depressive symptoms., Background Reward processing abnormalities may underlie characteristic pleasure and motivational impairments in schizophrenia. Some neural measures of reward processing show age-related modulation, highlighting the importance of considering age effects on reward sensitivity. We compared event-related potentials (ERPs) reflecting reward anticipation (stimulus-preceding negativity, SPN) and evaluation (reward positivity, RewP; late positive potential, LPP) across individuals with schizophrenia (SZ) and healthy controls (HC), with an emphasis on examining the effects of chronological age, brain age (i.e., predicted age based on neurobiological measures), and illness phase. Methods Subjects underwent EEG while completing a slot-machine task for which rewards were not dependent on performance accuracy, speed, or response preparation. Slot-machine task EEG responses were compared between 54 SZ and 54 HC individuals, ages 19 to 65. Reward-related ERPs were analyzed with respect to chronological age, categorically-defined illness phase (early; ESZ versus chronic schizophrenia; CSZ), and were used to model brain age relative to chronological age. Results Illness phase-focused analyses indicated there were no group differences in average SPN or RewP amplitudes. However, a group × reward outcome interaction revealed that ESZ differed from HC in later outcome processing, reflected by greater LPP responses following loss versus reward (a reversal of the HC pattern). While brain age estimates did not differ among groups, depressive symptoms in SZ were associated with older brain age estimates while controlling for negative symptoms. Conclusions ESZ and CSZ did not differ from HC in reward anticipation or early outcome processing during a cognitively undemanding reward task, highlighting areas of preserved functioning. However, ESZ showed altered later reward outcome evaluation, pointing to selective reward deficits during the early illness phase of schizophrenia. Further, an association between ERP-derived brain age and depressive symptoms in SZ extends prior findings linking depression with reward-related ERP blunting. Taken together, both illness phase and age may impact reward processing among SZ, and brain aging may offer a promising, novel marker of reward dysfunction that warrants further study.

The size of the human head is determined by growth in the first years of life, while the rest of the body typically grows until early adulthood1. Such complex developmental processes are regulated by various genes and growth pathways2. Rare genetic syndromes have revealed genes that affect head size3, but the genetic drivers of variation in head size within the general population remain largely unknown. To elucidate biological pathways underlying the growth of the human head, we performed the largest genome-wide association study on human head size to date (N = 79,107). We identified 67 genetic loci, 50 of which are novel, and found that these loci are preferentially associated with head size and mostly independent from height. In subsequent neuroimaging analyses, the majority of genetic variants demonstrated widespread effects on the brain, whereas the effects of 17 variants could be localized to one or two specific brain regions. Through hypothesis-free approaches, we find a strong overlap of head size variants with both cancer pathways and cancer genes. Gene set analyses showed enrichment for different types of cancer and the p53, Wnt and ErbB signalling pathway. Genes overlapping or close to lead variants – such as TP53, PTEN and APC – were enriched for genes involved in macrocephaly syndromes (up to 37-fold) and high-fidelity cancer genes (up to 9-fold), whereas this enrichment was not seen for human height variants. This indicates that genes regulating early brain and cranial growth are associated with a propensity to neoplasia later in life, irrespective of height. Our results warrant further investigations of the link between head size and cancer, as well as its clinical implications in the general population.

BackgroundReward processing abnormalities may underlie characteristic pleasure and motivational impairments in schizophrenia. Some neural measures of reward processing show strong age-related modulation, highlighting the importance of considering age effects on reward sensitivity. We compared event-related potentials (ERPs) reflecting reward anticipation (stimulus-preceding negativity, SPN) and evaluation (reward positivity, RewP; late-positive potential, LPP) across individuals with schizophrenia (SZ) and healthy controls (HC), with an emphasis on examining effects of chronological age, brain age (i.e., predicted age based on neurobiological measures), and illness phase.MethodsSubjects underwent EEG while completing a slot-machine task for which rewards were not dependent on performance accuracy, speed, or other preparatory demands. Slot-machine task EEG responses were compared between 54 SZ and 54 HC individuals, ages 19 to 65. Reward-related ERPs were analyzed with respect to chronological age, categorically-defined illness phase (early; ESZ versus chronic schizophrenia; CSZ), and were used to model brain age relative to chronological age.ResultsIllness phase-focused analyses indicated there were no group differences in average SPN or RewP amplitudes. However, a group x reward outcome interaction revealed that ESZ differed from HC in later outcome processing, reflected by greater LPP responses following loss versus reward (a reversal of the HC pattern). While brain age estimates did not differ among groups, depressive symptoms in SZ were associated with older brain age estimates while controlling for negative symptoms.ConclusionsESZ and CSZ did not differ from HC in reward anticipation or early outcome processing during a cognitively undemanding reward task, highlighting areas of preserved functioning. However, ESZ showed altered later reward outcome evaluation, pointing to selective reward deficits during the early illness phase of schizophrenia. Further, an association between ERP-derived brain age and depressive symptoms in SZ extends prior findings linking depression with reward-related ERP blunting. Taken together, both illness phase and age may impact reward processing in SZ, and brain aging may offer a promising, novel marker of reward dysfunction that warrants further study.

Although visual processing impairments have been explored in schizophrenia (SZ), their underlying neurobiology of the visual processing impairments has not been widely studied. Also, while some research has hinted at differences in information transfer and flow in SZ, there are few investigations of the dynamics of functional connectivity within visual networks. In this study, we analyzed resting-state fMRI data of the visual sensory network (VSN) in 160 healthy control (HC) subjects and 151 SZ subjects. We estimated 9 independent components within the VSN. Then, we calculated the dynamic functional network connectivity (dFNC) using the Pearson correlation. Next, using k-means clustering, we partitioned the dFNCs into five distinct states, and then we calculated the portion of time each subject spent in each state, that we termed the occupancy rate (OCR). Using OCR, we compared HC with SZ subjects and investigated the link between OCR and visual learning in SZ subjects. Besides, we compared the VSN functional connectivity of SZ and HC subjects in each state. We found that this network is indeed highly dynamic. Each state represents a unique connectivity pattern of fluctuations in VSN FNC, and all states showed significant disruption in SZ. Overall, HC showed stronger connectivity within the VSN in states. SZ subjects spent more time in a state in which the connectivity between the middle temporal gyrus and other regions of VNS is highly negative. Besides, OCR in a state with strong positive connectivity between middle temporal gyrus and other regions correlated significantly with visual learning scores in SZ.

Patients with schizophrenia exhibit disrupted thalamocortical connections that relate to aspects of symptoms and deficits in cognition. Targeted cognitive training (TCT) of the auditory system in schizophrenia has been shown to improve cognition, but its impact on thalamocortical connectivity is not known. Here we examined thalamocortical connections that may be neuroplastic in response to TCT using a region of interest (ROI) approach. Participants were randomly assigned to either 40h of TCT (N=24) or an active control condition (CG; N=20). Participants underwent resting state fMRI and cognitive testing both before and after training. Changes in thalamocortical connectivity were measured in 15 ROIs derived from a previous study comparing a large sample of schizophrenia subjects with healthy controls. A significant group by time interaction was observed in a left superior temporal ROI which was previously found to exhibit thalamocortical hyper-connectivity in patients with schizophrenia. Changes in this ROI reflected thalamic connectivity increases in the TCT group, while the CG group showed decreases. Additionally, the relationship between connectivity change and change in global cognition showed a slope difference between groups, with increases in thalamo-temporal connectivity correlating with improvements in global cognition in TCT. No significant relationships were observed with changes in clinical symptoms or functioning. These findings demonstrate that TCT may influence intrinsic functional connections in young individuals with schizophrenia, such that improvements in cognition correspond to compensatory increases in connectivity in a temporal region previously shown to exhibit thalamic hyper-connectivity.

The human brain is asymmetrically lateralized for certain functions (such as language processing) to regions in one hemisphere relative to the other. Asymmetries are measured with a laterality index (LI). However, traditional LI measures are limited by a lack of consensus on metrics used for its calculation. To address this limitation, source-based laterality (SBL) leverages an independent component analysis for the identification of laterality-specific alterations, identifying covarying components between hemispheres across subjects. SBL is successfully implemented with simulated data with inherent differences in laterality. SBL is then compared with a voxel-wise analysis utilizing structural data from a sample of patients with schizophrenia and controls without schizophrenia. SBL group comparisons identified three distinct temporal regions and one cerebellar region with significantly altered laterality in patients with schizophrenia relative to controls. Previous work highlights reductions in laterality (ie, reduced left gray matter volume) in patients with schizophrenia compared with controls without schizophrenia. Results from this pilot SBL project are the first, to our knowledge, to identify covarying laterality differences within discrete temporal brain regions. The authors argue SBL provides a unique focus to detect covarying laterality differences in patients with schizophrenia, facilitating the discovery of laterality aspects undetected in previous work.

Although both resting and task-induced functional connectivity (FC) have been used to characterize the human brain and cognitive abilities, the potential of task-induced FCs in individualized prediction for out-of-scanner cognitive traits remains largely unexplored. A recent study Greene etal. (2018) predicted the fluid intelligence scores using FCs derived from rest and multiple task conditions, suggesting that task-induced brain state manipulation improved prediction of individual traits. Here, using a large dataset incorporating fMRI data from rest and 7 distinct task conditions, we replicated the original study by employing a different machine learning approach, and applying the method to predict two reading comprehension-related cognitive measures. Consistent with their findings, we found that task-based machine learning models often outperformed rest-based models. We also observed that combining multi-task fMRI improved prediction performance, yet, integrating the more fMRI conditions can not necessarily ensure better predictions. Compared with rest, the predictive FCs derived from language and working memory tasks were highlighted with more predictive power in predominantly default mode and frontoparietal networks. Moreover, prediction models demonstrated high stability to be generalizable across distinct cognitive states. Together, this replication study highlights the benefit of using task-based FCs to reveal brain-behavior relationships, which may confer more predictive power and promote the detection of individual differences of connectivity patterns underlying relevant cognitive traits, providing strong evidence for the validity and robustness of the original findings.

BackgroundDuring vocalization, efference copy/corollary discharge mechanisms suppress the auditory cortical response to self-generated sounds. Previously, we found attenuated vocalization-related auditory cortical suppression in psychosis and a similar trend in the psychosis risk syndrome. Here, we report data from the final sample of early illness schizophrenia patients (ESZ), individuals at clinical high risk for psychosis (CHR), and healthy controls (HC).MethodsEvent-related potentials (ERP) were recorded from ESZ (n = 84), CHR (n = 71), and HC (n = 103) participants during a vocalization paradigm. The N1 ERP component was elicited during production (Talk) and playback (Listen) of vocalization. Age effects on N1 suppression (Talk–Listen), Talk N1, and Listen N1 were compared across groups. N1 measures were adjusted for normal aging before testing for group differences.ResultsBoth ESZ and CHR groups showed reduced Talk–Listen N1 suppression relative to HC, but did not differ from each other. Listen N1 was reduced in ESZ, but not in CHR, relative to HC. Deficient Talk–Listen N1 suppression was associated with greater unusual thought content in CHR individuals. N1 suppression increased with age in HC (12–36 years), and while CHR individuals showed a similar age-related increase, no such relationship was evident in ESZ.ConclusionsPutative efference copy/corollary discharge-mediated auditory cortical suppression during vocalization is deficient in ESZ and precedes psychosis onset, particularly in CHR individuals with greater unusual thought content. Furthermore, this suppression increases from adolescence through early adulthood, likely reflecting the effects of normal brain maturation. This maturation effect is disrupted in ESZ, presumably due to countervailing illness effects.

Hallucinations characterize schizophrenia, with approximately 59% of patients reporting auditory hallucinations and 27% reporting visual hallucinations. Prior neuroimaging studies suggest that hallucinations are linked to disrupted communication across distributed (sensory, salience-monitoring and subcortical) networks. Yet, our understanding of the neurophysiological mechanisms that underlie auditory and visual hallucinations in schizophrenia remains limited. This study integrates two resting-state functional magnetic resonance imaging (fMRI) analysis methods – amplitudes of low-frequency fluctuations (ALFF) and functional network connectivity (FNC) – to explore the hypotheses that (1) abnormal FNC between salience and sensory (visual/auditory) networks underlies hallucinations in schizophrenia, and (2) disrupted hippocampal oscillations (as measured by hippocampal ALFF) beget changes in FNC linked to hallucinations. Our first hypothesis was supported by the finding that schizophrenia patients reporting hallucinations have higher FNC between the salience network and an associative auditory network relative to healthy controls. Hippocampal ALFF was negatively associated with FNC between primary auditory cortex and the salience network in healthy subjects, but was positively associated with FNC between these networks in patients reporting hallucinations. These findings provide indirect support favoring our second hypothesis. We suggest future studies integrate fMRI with electroencephalogram (EEG) and/or magnetoencephalogram (MEG) methods to directly probe the temporal relation between altered hippocampal oscillations and changes in cross-network functional communication.

N-methyl-D-aspartate glutamate receptor (NMDAR) hypofunction has been implicated in the pathophysiology of schizophrenia, including auditory processing abnormalities reflected by the mismatch negativity (MMN) event-related potential component. Evidence suggesting cognitive benefits from nicotine administration, together with the high rate of cigarette use in patients with schizophrenia, has stimulated interest in whether nicotine modulates NMDAR hypofunction. We examined the interactive effects of ketamine, an NMDAR antagonist that produces transient schizophrenia-like neurophysiological effects, and nicotine, a nicotinic acetylcholine receptor (nAChR) agonist, in 30 healthy volunteers to determine whether nicotine prevents or attenuates MMN abnormalities. Secondary analyses compared the profile of ketamine and schizophrenia effects on MMN using previously reported data from 24 schizophrenia patients (Hay et al., 2015). Healthy volunteers completed four test days, during which they received ketamine/placebo and nicotine/placebo in a double-blind, counterbalanced design. MMN to intensity, frequency, duration, and frequency+duration double deviant sounds was assessed each day. Ketamine decreased intensity, frequency, and double deviant MMN amplitudes, whereas nicotine increased intensity and double deviant MMN amplitudes. A ketamine x nicotine interaction indicated, however, that nicotine failed to attenuate the decrease in MMN associated with ketamine. Although the present dose of ketamine produced smaller decrements in MMN than those associated with schizophrenia, the profile of effects across deviant types did not differ between ketamine and schizophrenia. Results suggest that while ketamine and schizophrenia produce similar profiles of MMN effects across deviant types, nicotinic agonists may have limited potential to improve these putative NMDAR hypofunction-mediated impairments in schizophrenia.

The hallmark of resting EEG spectra are distinct rhythms emerging from a broadband, aperiodic background. This aperiodic neural signature accounts for most of total EEG power, although its significance and relation to functional neuroanatomy remains obscure. We hypothesized that aperiodic EEG reflects a significant metabolic expenditure and therefore might be associated with the default mode network while at rest. During eyes-open, resting-state recordings of simultaneous EEG-fMRI, we find that aperiodic and periodic components of EEG power are only minimally associated with activity in the default mode network. However, a whole-brain analysis identifies increases in aperiodic power correlated with hemodynamic activity in an auditory-salience-cerebellar network, and decreases in aperiodic power are correlated with hemodynamic activity in prefrontal regions. Desynchronization in residual alpha and beta power is associated with visual and sensorimotor hemodynamic activity, respectively. These findings suggest that resting-state EEG signals acquired in an fMRI scanner reflect a balance of top-down and bottom-up stimulus processing, even in the absence of an explicit task.

Individuals with schizophrenia exhibit widespread cortical thinning associated with illness severity and deficits in cognition. However, intact cortical thickness (CTh) may serve as a protective factor. The current study sought to examine changes in CTh in response to auditory targeted cognitive training (TCT) in individuals with recent onset schizophrenia. Participants underwent MRI scanning and a cognitive assessment before and after being randomly assigned to 40 h of either TCT (N = 21) or a computer games control condition (CG; N = 22) over 16 weeks. Groups did not differ at baseline on demographic variables or measures of CTh. At the level of group averages, neither group showed significant pre-post changes in CTh in any brain region. However, changes in CTh related to individual differences in treatment outcome, as improved global cognition in the TCT group corresponded to reduced cortical thinning in frontal, temporal, parietal, and occipital lobes. These relationships were not observed in the CG group. The current findings suggest that TCT may be neuroprotective in early schizophrenia, such that individuals who improved in response to training also showed a reduction in cortical thinning that may be otherwise hastened due to age and illness.

Recent theoretical models of schizophrenia posit that dysfunction of the neural mechanisms subserving predictive coding contributes to symptoms and cognitive deficits, and this dysfunction is further posited to result from N-methyl-D-aspartate glutamate receptor (NMDAR) hypofunction. Previously, by examining auditory cortical responses to self-generated speech sounds, we demonstrated that predictive coding during vocalization is disrupted in schizophrenia. To test the hypothesized contribution of NMDAR hypofunction to this disruption, we examined the effects of the NMDAR antagonist, ketamine, on predictive coding during vocalization in healthy volunteers and compared them with the effects of schizophrenia.In two separate studies, the N1 component of the event-related potential elicited by speech sounds during vocalization (talk) and passive playback (listen) were compared to assess the degree of N1 suppression during vocalization, a putative measure of auditory predictive coding. In the crossover study, 31 healthy volunteers completed two randomly ordered test days, a saline day and a ketamine day. Event-related potentials during the talk/listen task were obtained before infusion and during infusion on both days, and N1 amplitudes were compared across days. In the case-control study, N1 amplitudes from 34 schizophrenia patients and 33 healthy control volunteers were compared.N1 suppression to self-produced vocalizations was significantly and similarly diminished by ketamine (Cohen's d = 1.14) and schizophrenia (Cohen's d = .85).Disruption of NMDARs causes dysfunction in predictive coding during vocalization in a manner similar to the dysfunction observed in schizophrenia patients, consistent with the theorized contribution of NMDAR hypofunction to predictive coding deficits in schizophrenia.

Auditory verbal hallucinations (AVH), also referred to as “hearing voices,” are vivid perceptions of speech that occur in the absence of any corresponding external stimulus but seem very real to the voice hearer. They are experienced by the majority of people with schizophrenia, less frequently in other psychiatric and neurological conditions, and are relatively rare in the general population. Because antipsychotic medications are not always successful in reducing the severity or frequency of AVH, a better understanding is needed of their neurobiological basis, which may ultimately lead to more precise treatment targets. What voices say and how the voices sound, or their phenomenology, varies widely within and across groups of people who hear them. In help-seeking populations, such as people with schizophrenia, the voices tend to be threatening and menacing, typically spoken in a non-self-voice, often commenting and sometimes commanding the voice hearers to do things they would not otherwise do. In psychotic populations, voices differ from normal inner speech by being unbidden and unintended, co-opting the voice hearer’s attention. In healthy voice-hearing populations, voices are not typically distressing nor disabling, and are sometimes comforting and reassuring. Regardless of content and valence, voices tend to activate some speech and language areas of the brain. Efforts to silence these brain areas with neurostimulation have had mixed success in reducing the frequency and salience of voices. Progress with this treatment approach would likely benefit from more precise anatomical targets and more precisely dosed neurostimulation. Neural mechanisms that may underpin the experience of voices are being actively investigated and include mechanisms enabling context-based predictions and distinctions between experiences coming from self and other. Both these mechanisms can be studied in non-human animal “models” and both can provide new anatomical targets for neurostimulation.

Negative symptoms are core contributors to vocational and social deficits in schizophrenia (SZ). Available antipsychotic medications typically fail to reduce these symptoms. The neurohormone oxytocin (OT) is a promising treatment for negative symptoms, given its role in complex social behaviors mediated by the amygdala. In sample 1, we used a double-blind, placebo-controlled, crossover design to test the effects of a single dose of intranasal OT on amygdala resting-state functional connectivity (rsFC) in SZ (n = 22) and healthy controls (HC, n = 24) using a whole-brain corrected approach: we identified regions for which OT modulated SZ amygdala rsFC, assessed whether OT-modulated circuits were abnormal in SZ relative to HC on placebo, and evaluated whether connectivity on placebo and OT-induced connectivity changes correlated with baseline negative symptoms in SZ. Given our modest sample size, we used a second SZ (n = 183) and HC (n = 178) sample to replicate any symptom correlations. In sample 1, OT increased rsFC between the amygdala and left middle temporal gyrus, superior temporal sulcus, and angular gyrus (MTG/STS/AngG) in SZ compared to HC. Further, SZ had hypo-connectivity in this circuit compared to HC on placebo. More severe negative symptoms correlated with less amygdala-to-left-MTG/STS/AngG connectivity on placebo and with greater OT-induced connectivity increases. In sample 2, we replicated the correlation between amygdala-left-MTG/STS/AngG hypo-connectivity and negative symptoms, finding a specific association with expressive negative symptoms. These data suggest intranasal OT can normalize functional connectivity in an amygdala-to-left-MTG/STS/AngG circuit that contributes to negative symptoms in SZ.

Background: Auditory steady-state response (ASSR) paradigms have consistently demonstrated gamma band abnormalities in schizophrenia at a 40-Hz driving frequency with both electroencephalography (EEG) and magnetoencephalography (MEG). Various time-frequency measures have been used to assess the 40-Hz ASSR, including evoked power, single trial total power, phase-locking factor (PLF), and phase-locking angle (PLA). While both EEG and MEG studies have shown power and PLF ASSR measures to exhibit excellent test-retest reliability in healthy adults, the reliability of these measures in patients with schizophrenia has not been determined. Methods: ASSRs were obtained by recording EEG data during presentation of repeated 20-Hz, 30-Hz and 40-Hz auditory click trains from nine schizophrenia patients (SZ) and nine healthy controls (HC) tested on two occasions. Similar ASSR data were collected from a separate group of 30 HC on two to three test occasions. A subset of these HC subjects had EEG recordings during two tasks, passively listening and actively attending to click train stimuli. Evoked power, total power, PLF, and PLA were calculated following Morlet wavelet time-frequency decomposition of EEG data and test-retest generalizability (G) coefficients were calculated for each ASSR condition, time-frequency measure, and subject group. Results: G-coefficients ranged from good to excellent (> 0.6) for most 40-Hz time-frequency measures and participant groups, whereas 20-Hz G-coefficients were much more variable. Importantly, test-retest reliability was excellent for the various 40-Hz ASSR measures in SZ, similar to reliabilities in HC. Active attention to click train stimuli modestly reduced G-coefficients in HC relative to the passive listening condition. Discussion: The excellent test-retest reliability of 40-Hz ASSR measures replicates previous EEG and MEG studies. PLA, a relatively new time-frequency measure, was shown for the first time to have excellent reliability, comparable to power and PLF measures. Excellent reliability of 40 Hz ASSR measures in SZ supports their use in clinical trials and longitudinal observational studies. Keywords: Auditory steady-state response (ASSR), Gamma, Electroencephalography (EEG), Schizophrenia, Reliability, Generalizability, Oscillations, Power, Phase angle

Schizophrenia is a complex, debilitating mental disorder characterized by wide-ranging symptoms including delusions, hallucinations (so-called positive symptoms), and impaired motor and speech/language production (so-called negative symptoms). Salience-monitoring theorists propose that abnormal functional communication between the salience network (SN) and default mode network (DMN) begets positive and negative symptoms of schizophrenia, yet prior studies have predominately reported links between disrupted SN/DMN functional communication and positive symptoms. It remains unclear whether disrupted SN/DMN functional communication explains (1) solely positive symptoms or (2) both positive and negative symptoms of schizophrenia. To address this question, we incorporate time-lag-shifted functional network connectivity (FNC) analyses that explored coherence of the resting-state functional magnetic resonance imaging signal of 3 networks (anterior DMN, posterior DMN, and SN) with fixed time lags introduced between network time series (1 TR = 2 s; 2 TR = 4 s). Multivariate linear regression analysis revealed that severity of disordered thought and attentional deficits were negatively associated with 2 TR-shifted FNC between anterior DMN and posterior DMN. Meanwhile, severity of flat affect and bizarre behavior were positively associated with 1 TR-shifted FNC between anterior DMN and SN. These results provide support favoring the hypothesis that lagged SN/DMN functional communication is associated with both positive and negative symptoms of schizophrenia.

Background The N400 event-related potential (ERP) is triggered by meaningful stimuli that are incongruous, or unmatched, with their semantic context. Functional magnetic resonance imaging (fMRI) studies have identified brain regions activated by semantic incongruity, but their precise links to the N400 ERP are unclear. In schizophrenia (SZ), N400 amplitude reduction is thought to reflect overly broad associations in semantic networks, but the abnormalities in brain networks underlying deficient N400 remain unknown. We utilized joint independent component analysis (JICA) to link temporal patterns in ERPs to neuroanatomical patterns from fMRI and investigate relationships between N400 amplitude and neuroanatomical activation in SZ patients and healthy controls (HC). Methods SZ patients (n = 24) and HC participants (n = 25) performed a picture-word matching task, in which words were either matched (APPLE→apple) by preceding pictures, or were unmatched by semantically related (in-category; IC, APPLE→lemon) or unrelated (out of category; OC, APPLE→cow) pictures, in separate ERP and fMRI sessions. A JICA “data fusion” analysis was conducted to identify the fMRI brain regions specifically associated with the ERP N400 component. SZ and HC loading weights were compared and correlations with clinical symptoms were assessed. Results JICA identified an ERP-fMRI “fused” component that captured the N400, with loading weights that were reduced in SZ. The JICA map for the IC condition showed peaks of activation in the cingulate, precuneus, bilateral temporal poles and cerebellum, whereas the JICA map from the OC condition was linked primarily to visual cortical activation and the left temporal pole. Among SZ patients, fMRI activity from the IC condition was inversely correlated with unusual thought content. Conclusions The neural networks associated with the N400 ERP response to semantic violations depends on conceptual relatedness. These findings are consistent with a distributed network underlying neural responses to semantic incongruity including unimodal visual areas as well as integrative, transmodal areas. Unusual thoughts in SZ may reflect impaired processing in transmodal hub regions such as the precuneus, leading to overly broad semantic associations., Highlights • Hemodynamic activity linked to N400 responses is distributed across the brain. • N400 linked networks depend on conceptual relatedness. • Magnitude of the N400 ERP-fMRI fused component is reduced in schizophrenia. • N400 linked network activity inversely correlates with unusual thought content.

BACKGROUND: Targeted cognitive training (TCT) for schizophrenia is hypothesized to improve global cognitive functioning by driving plasticity in distributed frontal and temporal systems. While previous work has demonstrated that TCT evokes functional changes in prefrontal and temporal cortex, less is known about whether treatment response coincides with structural changes in these brain areas. In the current study, we examined whether changes in cognition in response to TCT (compared to a computer games control condition) correspond to changes in cortical thickness (CTh) in frontal and temporal cortices among patients with recent onset schizophrenia (SZ). Additionally, we determined whether baseline CTh predicted treatment response. METHODS: SZ patients were randomized to 40 hours of TCT of the auditory system (N=21) or computer games (CG; N=22). Before and after training, participants underwent MRI and cognitive testing. Freesurfer’s longitudinal pipeline was used to calculate CTh at baseline and follow up. Patients averaged 4.5 months to complete training. Using regions from the Desikan-Killiany Atlas, we created regions of interest (ROIs) from left and right frontal and temporal cortices and calculated CTh change scores. Next, we examined slope differences to determine whether the relationship between change in CTh and change in cognition differed between TCT and CG. Last, we determined whether baseline CTh in any sub-regions of the ROIs was predictive of treatment response in the TCT group. RESULTS: The relationship between change in CTh and global cognition differed between groups in the left frontal cortex (t=2.42; p=.02), characterized by a correlation in TCT (r=.50 p=.02), but no relationship in CG (r=-.18; p=.42). The same pattern was observed in the right frontal cortex (t=3.29 p=.002; TCT: r=.59; p=.004; CG: r=-.29 p=.18). We observed a similar pattern in the temporal cortex, with a significant slope difference in the left hemisphere (t=2.38 p=.02), characterized by a correlation in TCT (r=.58 p=.006) but not CG (r=-.13 p=.55). The same trend was observed in the right temporal cortex (t=1.93 p=.06), with a strong TCT correlation (r=.72 p=.0002), and no relationship in CG (r=.11 p=.61). We observed no significant group x time interactions on change in CTh. We conducted post-hoc analyses on sub-region ROIs that may be driving these relationships and identified numerous frontal and temporal regions showing a significant slope difference, including superior and middle frontal gyrus, as well as temporal pole, inferior, and middle temporal regions (all p’s

There is growing evidence that rather than using a single brain imaging modality to study its association with physiological or symptomatic features, the field is paying more attention to fusion of multimodal information. However, most current multimodal fusion approaches that incorporate functional magnetic resonance imaging (fMRI) are restricted to second-level 3D features, rather than the original 4D fMRI data. This trade-off is that the valuable temporal information is not utilized during the fusion step. Here we are motivated to propose a novel approach called “parallel group ICA+ICA” that incorporates temporal fMRI information from GICA into a parallel ICA framework, aiming to enable direct fusion of first-level fMRI features with other modalities (e.g.structural MRI), which thus can detect linked functional network variability and structural covariations. Simulation results show that the proposed method yields accurate inter-modality linkage detection regardless of whether it is strong or weak. When applied to real data, we identified one pair of significantly associated fMRI-sMRI components that show group difference between schizophrenia and controls in both modalities. Finally, multiple cognitive domain scores can be predicted by the features identified in the linked component pair by our proposed method. We also show these multimodal brain features can predict multiple cognitive scores in an independent cohort. Overall, results demonstrate the ability of parallel GICA+ICA to estimate joint information from 4D and 3D data without discarding much of the available information up front, and the potential for using this approach to identify imaging biomarkers to study brain disorders.

BackgroundAcross the animal kingdom, responses in auditory cortex are dampened during vocalizing compared to passive listening, reflecting the action of the corollary discharge mechanism. In humans, it is seen as suppression of the EEG-based N1 event-related potential, with less N1-suppression seen in people with schizophrenia and those at clinical high risk (CHR) for psychosis. Because N1 is an admixture of theta (4-7Hz) power and phase synchrony, we asked which is responsible for N1 effects and if they outperform the sensitivity of N1 to corollary discharge and schizophrenia.MethodsTheta phase and power values were extracted from EEG data acquired from CHR youth (n=71), early illness schizophrenia patients (ESZ; n=84), and healthy controls (HC; n=103) as they said /ah/ (Talk) and then listened to the sounds played back (Listen). A principal components analysis extracted theta inter-trial coherence (ITC; phase consistency) and event related spectral power, peaking in the N1 latency range.ResultsTheta ITC-suppression (Cohen d=1.46) was greater than N1-suppression in HC (Cohen d=.63). Both were both reduced in ESZ, but only N1-suppression was reduced in CHR. When deprived of the variance shared with theta-ITC suppression, N1-suppression was no longer sensitive to HC vs. ESZ or HC vs. CHR group differences. Deficits in theta ITC-suppression were correlated with delusions (p=.007) in ESZ. Suppression of theta power was not affected by Group.ConclusionsTheta ITC-suppression may provide a simpler assay of the corollary discharge mechanism than N1-suppression. Deficits in circuits that generate low frequency oscillations may be an important component of schizophrenia.

The motor system in its manifold articulations is receiving increasing clinical and research attention. This is because motor impairments constitute a central, expressive component of the mental state examination and a key transdiagnostic feature indexing disease severity. Furthermore, within the schizophrenia spectrum, the integration of neurophysiological, developmental, and phenomenological perspectives suggests that motor impairment is not simply a generic, extrinsic proxy of an altered neurodevelopment, but might be more intimately related to psychotic risk. Therefore, an increased understanding, conceptualization, and knowledge of such motor system and its anomalies could empower contemporary risk prediction and diagnostic procedures. This is a pre-copyedited, author-produced version of an article accepted for publication in Schizophrenia Bulletin following peer review. Locked until 11.07.2019 due to copyright restrictions. The version of record is available online at: https://doi.org/10.1093/schbul/sby100

Multimodal, imaging-genomics techniques offer a platform for understanding genetic influences on brain abnormalities in psychiatric disorders. Such approaches utilize the information available from both imaging and genomics data and identify their association. Particularly for complex disorders such as schizophrenia, the relationship between imaging and genomic features may be better understood by incorporating additional information provided by advanced multimodal modeling. In this study, we propose a novel framework to combine features corresponding to functional magnetic resonance imaging (functional) and single nucleotide polymorphism (SNP) data from 61 schizophrenia (SZ) patients and 87 healthy controls (HC). In particular, the features for the functional and genetic modalities include dynamic (i.e., time-varying) functional network connectivity (dFNC) features and the SNP data, respectively. The dFNC features are estimated from component time-courses, obtained using group independent component analysis (ICA), by computing sliding-window functional network connectivity, and then estimating subject specific states from this dFNC data using a k-means clustering approach. For each subject, both the functional (dFNC states) and SNP data are selected as features for a parallel ICA (pICA) based imaging-genomic framework. This analysis identified a significant association between a SNP component (defined by large clusters of functionally related SNPs statistically correlated with phenotype components) and time-varying or dFNC component (defined by clusters of related connectivity links among distant brain regions distributed across discrete dynamic states, and statistically correlated with genomic components) in schizophrenia. Importantly, the polygenetic risk score (PRS) for SZ (computed as a linearly weighted sum of the genotype profiles with weights derived from the odds ratios of the psychiatric genomics consortium (PGC)) was negatively correlated with the significant dFNC component, which were mostly present within a state that exhibited a lower occupancy rate in individuals with SZ compared with HC, hence identifying a potential dFNC imaging biomarker for schizophrenia. Taken together, the current findings provide preliminary evidence for a link between dFNC measures and genetic risk, suggesting the application of dFNC patterns as biomarkers in imaging genetic association study.

Brain functional networks identified from fMRI data can provide potential biomarkers for brain disorders. Group independent component analysis (GICA) is popular for extracting brain functional networks from multiple subjects. In GICA, different strategies exist for reconstructing subject-specific networks from the group-level networks. However, it is unknown whether these strategies have different sensitivities to group differences and abilities in distinguishing patients. Among GICA, spatio-temporal regression (STR) and spatially constrained ICA approaches such as group information guided ICA (GIG-ICA) can be used to propagate components (indicating networks) to a new subject that is not included in the original subjects. In this study, based on the same a priori network maps, we reconstructed subject-specific networks using these two methods separately from resting-state fMRI data of 151 schizophrenia patients (SZs) and 163 healthy controls (HCs). We investigated group differences in the estimated functional networks and the functional network connectivity (FNC) obtained by each method. The networks were also used as features in a cross-validated support vector machine (SVM) for classifying SZs and HCs. We selected features using different strategies to provide a comprehensive comparison between the two methods. GIG-ICA generally showed greater sensitivity in statistical analysis and better classification performance (accuracy 76.45 ± 8.9%, sensitivity 0.74 ± 0.11, specificity 0.79 ± 0.11) than STR (accuracy 67.45 ± 8.13%, sensitivity 0.65 ± 0.11, specificity 0.71 ± 0.11). Importantly, results were also consistent when applied to an independent dataset including 82 HCs and 82 SZs. Our work suggests that the functional networks estimated by GIG-ICA are more sensitive to group differences, and GIG-ICA is promising for identifying image-derived biomarkers of brain disease., Highlights • We investigate which group ICA method is more sensitive to group differences in networks and FNC. • We evaluate which group ICA method can result in better classification performance. • We compare the spatio-temporal regression (STR) and GIG-ICA using different feature selection and model building strategies and independent samples. • We use different feature selection and model building strategies and classification using independent samples. • Using fMRI data including schizophrenia patients, GIG-ICA shows better performance than the traditional STR method.

Introduction During vocalization, efference copy/corollary discharge mechanisms suppress the auditory cortical response to self-generated sounds as reflected in the N1 component of the auditory event-related potential (ERP). N1 suppression during talking is reduced in patients with schizophrenia. We hypothesized that these deficits would recover with auditory training that targets the speech processing system. Methods Forty-nine individuals early in the course of a schizophrenia-spectrum illness (ESZ) were randomly assigned to 40 h of Targeted Auditory Training (TAT; n = 23) or Computer Games (CG; n = 26). The N1 ERP component was elicited during production (Talk) and playback (Listen) of vocalization. Effects of Treatment on Global Cognition, N1 suppression (Talk-Listen), N1 during Talking and Listening were assessed. Simple effects of the passage of time were also assessed in the HC after 28 weeks. Results There was a Treatment × Time interaction revealing that N1 suppression was improved with TAT, but not with CG. TAT, but not CG, also improved Global Cognition. However, TAT and CG groups differed in their pre-treatment N1 suppression, and greater N1-suppression abnormalities were strongly associated with greater improvement in N1 suppression. Conclusions In this sample of ESZ individuals, targeted auditory training appeared to improve the function of the efference copy/corollary discharge mechanism which tended to deteriorate with computer games. It remains to be determined if baseline N1 suppression abnormalities are necessary for TAT treatment to have a positive effect on efference copy/corollary discharge function or if improvements observed in this study represent a regression to the mean N1 suppression in ESZ. Trial registration ClinicalTrials.gov NCT00694889 . Registered 1 August 2007.

In recent years, there has been increasing interest in the potential for alterations to the brain's resting-state networks (RSNs) to explain various kinds of psychopathology. RSNs provide an intriguing new explanatory framework for hallucinations, which can occur in different modalities and population groups, but which remain poorly understood. This collaboration from the International Consortium on Hallucination Research (ICHR) reports on the evidence linking resting-state alterations to auditory hallucinations (AH) and provides a critical appraisal of the methodological approaches used in this area. In the report, we describe findings from resting connectivity fMRI in AH (in schizophrenia and nonclinical individuals) and compare them with findings from neurophysiological research, structural MRI, and research on visual hallucinations (VH). In AH, various studies show resting connectivity differences in left-hemisphere auditory and language regions, as well as atypical interaction of the default mode network and RSNs linked to cognitive control and salience. As the latter are also evident in studies of VH, this points to a domain-general mechanism for hallucinations alongside modality-specific changes to RSNs in different sensory regions. However, we also observed high methodological heterogeneity in the current literature, affecting the ability to make clear comparisons between studies. To address this, we provide some methodological recommendations and options for future research on the resting state and hallucinations.

In this paper, I explain why I adopted a Research Domain Criteria (RDoC) approach to study the neurobiology of auditory verbal hallucinations (AVH), or voices. I explain that the RDoC construct of "agency" fits well with AVH phenomenology. To the extent that voices sound nonself, voice hearers lack a sense of agency over the voices. Using a vocalization paradigm like those used with nonhuman primates to study mechanisms subserving the sense of agency, we find that the auditory N1 ERP is suppressed during vocalization, that EEG synchrony preceding speech onset is related to N1 suppression, and that both are reduced in patients with schizophrenia. Reduced cortical suppression is also seen across multiple psychotic disorders and in clinically high-risk youth, but it is not related to AVH. The motor activity preceding talking and connectivity between frontal and temporal lobes during talking have both proved sensitive to AVH, suggesting neural activity and connectivity associated with intentions to act may be a better way to study agency and predictions based on agency.

Perceptional abnormalities in schizophrenia are associated with hallucinations and delusions, but also with negative symptoms and poor functional outcome. Perception can be studied using EEG-derived event related potentials (ERPs). Because of their excellent temporal resolution, ERPs have been used to ask when perception is affected by schizophrenia. Because of its excellent spatial resolution, functional magnetic resonance imaging (fMRI) has been used to ask where in the brain these effects are seen. We acquired EEG and fMRI data simultaneously to explore when and where auditory perception is affected by schizophrenia. Thirty schizophrenia (SZ) patients and 23 healthy comparison subjects (HC) listened to 1000 Hz tones occurring about every second. We used joint independent components analysis (jICA) to combine EEG-based event-related potential (ERP) and fMRI responses to tones. Five ERP-fMRI joint independent components (JIC) were extracted. The “N100” JIC had temporal weights during N100 (peaking at 100 ms post-tone onset) and fMRI spatial weights in superior and middle temporal gyri (STG/MTG); however, it did not differ between groups. The “P200” JIC had temporal weights during P200 and positive fMRI spatial weights in STG/MTG and frontal areas, and negative spatial weights in the nodes of the default mode network (DMN) and visual cortex. Groups differed on the “P200” JIC: SZ had smaller “P200” JIC, especially those with more severe avolition/apathy. This is consistent with negative symptoms being related to perceptual deficits, and suggests patients with avolition/apathy may allocate too few resources to processing external auditory events and too many to processing internal events., Highlights • Perceptual deficits in schizophrenia (SZ) were assessed using concurrent EEG + fMRI. • Joint independent components (JIC) analysis integrated EEG-based ERP and fMRI data. • “N100” and “P200” JICs were associated with auditory cortical activity. • “P200” JIC was inversely related to visual and default mode network (DMN) activity. • SZ had smaller “P200” JICs, especially those with severe negative symptoms.