Resting-state functional connectivity (FC) fMRI (rs-fcMRI) offers an appealing approach to mapping the brain's intrinsic functional organization. Blood oxygen level dependent (BOLD) and arterial spin labeling (ASL) are the two main rs-fcMRI approaches to assess alterations in brain networks associated with individual differences, behavior and psychopathology. While the BOLD signal is stronger with a higher temporal resolution, ASL provides quantitative, direct measures of the physiology and metabolism of specific networks. This study systematically investigated the similarity and reliability of resting brain networks (RBNs) in BOLD and ASL. A 2 × 2 × 2 factorial design was employed where each subject underwent repeated BOLD and ASL rs-fcMRI scans on two occasions on two MRI scanners respectively. Both independent and joint FC analyses revealed common RBNs in ASL and BOLD rs-fcMRI with a moderate to high level of spatial overlap, verified by Dice Similarity Coefficients. Test-retest analyses indicated more reliable spatial network patterns in BOLD (average modal Intraclass Correlation Coefficients: 0.905 ± 0.033 between-sessions; 0.885 ± 0.052 between-scanners) than ASL (0.545 ± 0.048; 0.575 ± 0.059). Nevertheless, ASL provided highly reproducible (0.955 ± 0.021; 0.970 ± 0.011) network-specific CBF measurements. Moreover, we observed positive correlations between regional CBF and FC in core areas of all RBNs indicating a relationship between network connectivity and its baseline metabolism. Taken together, the combination of ASL and BOLD rs-fcMRI provides a powerful tool for characterizing the spatiotemporal and quantitative properties of RBNs. These findings pave the way for future BOLD and ASL rs-fcMRI studies in clinical populations that are carried out across time and scanners.

Reduced fractional anisotropy (FA) is a well-established correlate of schizophrenia, but it remains unclear whether these tensor-based differences are the result of axon damage and/or organizational changes and whether the changes are progressive in the adult course of illness. Diffusion MRI data were collected in 81 schizophrenia patients (54 first episode and 27 chronic) and 64 controls. Analysis of FA was combined with "fixel-based" analysis, the latter of which leverages connectivity and crossing-fiber information to assess both fiber bundle density and organizational complexity (i.e., presence and magnitude of off-axis diffusion signal). Compared with controls, patients with schizophrenia displayed clusters of significantly lower FA in the bilateral frontal lobes, right dorsal centrum semiovale, and the left anterior limb of the internal capsule. All FA-based group differences overlapped substantially with regions containing complex fiber architecture. FA within these clusters was positively correlated with principal axis fiber density, but inversely correlated with both secondary/tertiary axis fiber density and voxel-wise fiber complexity. Crossing fiber complexity had the strongest (inverse) association with FA (r = -0.82). When crossing fiber structure was modeled in the MRtrix fixel-based analysis pipeline, patients exhibited significantly lower fiber density compared to controls in the dorsal and posterior corpus callosum (central, postcentral, and forceps major). Findings of lower FA in patients with schizophrenia likely reflect two inversely related signals: reduced density of principal axis fiber tracts and increased off-axis diffusion sources. Whereas the former confirms at least some regions where myelin and or/axon count are lower in schizophrenia, the latter indicates that the FA signal from principal axis fiber coherence is broadly contaminated by macrostructural complexity, and therefore does not necessarily reflect microstructural group differences. These results underline the need to move beyond tensor-based models in favor of acquisition and analysis techniques that can help disambiguate different sources of white matter disruptions associated with schizophrenia.

Introduction Understanding the relationship between brain and complex latent behavioral constructs like cognitive control will require an inordinate amount of data. Internet-based methods can rapidly and efficiently refine behavioral measures in very large samples that are needed for genetics and behavioral research. Cognitive control is a multifactorial latent construct that is considered to be an endophenotype in numerous neuropsychiatric disorders, including attention deficit/hyperactivity disorder (ADHD). While previous studies have demonstrated high correlations between Web- and lab-based scores, skepticism remains for its broad implementation. Methods Here, we promote a different approach by characterizing a completely Web-recruited and tested community family sample on measures of cognitive control. We examine the prevalence of attention deficit symptoms in an online community sample of adolescents, demonstrate familial correlations in cognitive control measures, and use construct validation techniques to validate our high-throughput assessment approach. Results A total of 1214 participants performed Web-based tests of cognitive control with over 200 parent-child pairs analyzed as part of the primary study aims. The data show a wide range of "subclinical" symptomatology in a web community sample of adolescents that supports a dimensional view of attention and also provide preliminary narrow-sense heritability estimates for commonly used working memory and response inhibition tests. Conclusions Finally, we show strong face and construct validity for these measures of cognitive control that generally exceeds the evidence required of new lab-based measures. We discuss these results and how broad implementation of this platform may allow us to uncover important brain-behavior relationships quickly and efficiently.

DISC1 is considered a susceptibility gene for schizophrenia and schizoaffective disorder, but little is known regarding the potential mechanisms through which it may confer increased risk. Given that DISC1 plays a role in cerebral cortex development, polymorphisms in this gene may have relevance for neurobiological models of schizophrenia that have implicated cortical deficits in its pathophysiology.

In a recent machine learning study classifying "brain age" based on cross-sectional neuroanatomical data, clinical high-risk (CHR) individuals were observed to show deviation from the normal neuromaturational pattern, which in turn was predictive of greater risk of conversion to psychosis and a pattern of stably poor functional outcome. These effects were unique to cases who were between 12 and 17 years of age when their prodromal and psychotic symptoms began, suggesting that neuroanatomical deviance observable at the point of ascertainment of a CHR syndrome marks risk for an early onset form of psychosis. In the present study, we sought to clarify the pattern of neuroanatomical deviance linked to this "early onset" form of psychosis and whether this deviance is associated with poorer premorbid functioning. T1 MRI scans from 378 CHR individuals and 190 healthy controls (HC) from the North American Prodrome Longitudinal Study (NAPLS2) were analyzed. Widespread smaller cortical volume was observed among CHR individuals compared with HC at baseline evaluation, particularly among the younger group (i.e., those who were 12 to 17 years of age). Moreover, the younger CHR individuals who converted or presented worsened clinical symptoms at follow-up (within 2 years) exhibited smaller surface area in rostral anterior cingulate, lateral and medial prefrontal regions, and parahippocampal gyrus relative to the younger CHR individuals who remitted or presented a stable pattern of prodromal symptoms at follow-up. In turn, poorer premorbid functioning in childhood was associated with smaller surface area in medial orbitofrontal, lateral frontal, rostral anterior cingulate, precuneus, and temporal regions. Together with our prior report, these results are consistent with the view that neuroanatomical deviance manifesting in early adolescence marks vulnerability to a form of psychosis presenting with poor premorbid adjustment, an earlier age of onset (generally prior to the age of 18 years), and poor long-term outcome.

Mismatch negativity (MMN), an auditory event-related potential sensitive to deviance detection, is smaller in schizophrenia and psychosis risk. In a multisite study, a regression approach to account for effects of site and age (12-35 years) was evaluated alongside the one-year stability of MMN.

Working memory (WM) has been defined as the active maintenance and flexible updating of goal-relevant information in a form that has limited capacity and resists interference. Complex measures of WM recruit multiple subprocesses, making it difficult to isolate specific contributions of putatively independent subsystems. The present study was designed to determine whether neurophysiological indicators of proposed subprocesses of WM predict WM performance. We recruited 200 individuals defined by care-seeking status and measured neural responses using electroencephalography (EEG), while participants performed four WM tasks. We extracted spectral and time-domain EEG features from each task to quantify each of the hypothesized WM subprocesses: maintenance (storage of content), goal maintenance, and updating. We then used EEG measures of each subprocess as predictors of task performance to evaluate their contribution to WM. Significant predictors of WM capacity included contralateral delay activity and frontal theta, features typically associated with maintenance (storage of content) processes. In contrast, significant predictors of reaction time and its variability included contingent negative variation and the P3b, features typically associated with goal maintenance and updating. Broadly, these results suggest two principal dimensions that contribute to WM performance, tonic processes during maintenance contributing to capacity, and phasic processes during stimulus processing that contribute to response speed and variability. The analyses additionally highlight that reliability of features across tasks was greater (and comparable to that of WM performance) for features associated with stimulus processing (P3b and alpha), than with maintenance (gamma, theta and cross-frequency coupling).

Schizophrenia and bipolar disorder share genetic liability, and some structural brain abnormalities are common to both conditions. First-degree relatives of patients with schizophrenia (FDRs-SZ) show similar brain abnormalities to patients, albeit with smaller effect sizes. Imaging findings in first-degree relatives of patients with bipolar disorder (FDRs-BD) have been inconsistent in the past, but recent studies report regionally greater volumes compared with control subjects.

Cognitive neuroscience aims to map mental processes onto brain function, which begs the question of what "mental processes" exist and how they relate to the tasks that are used to manipulate and measure them. This topic has been addressed informally in prior work, but we propose that cumulative progress in cognitive neuroscience requires a more systematic approach to representing the mental entities that are being mapped to brain function and the tasks used to manipulate and measure mental processes. We describe a new open collaborative project that aims to provide a knowledge base for cognitive neuroscience, called the Cognitive Atlas (accessible online at http://www.cognitiveatlas.org), and outline how this project has the potential to drive novel discoveries about both mind and brain.

Individuals at clinical high risk (CHR) who progress to fully psychotic symptoms have been observed to show a steeper rate of cortical gray matter reduction compared with individuals without symptomatic progression and with healthy control subjects. Whether such changes reflect processes associated with the pathophysiology of schizophrenia or exposure to antipsychotic drugs is unknown.

Behavioral genetic studies of humans have associated variation in the DTNBP1 gene with schizophrenia and its cognitive deficit phenotypes. The protein coded for by DTNBP1, dysbindin, is expressed within forebrain glutamatergic neurons, in which it interacts with proteins involved in vesicular trafficking and exocytosis. In order to further delineate the cellular, physiological, and behavioral phenotypes associated with reduced dysbindin expression, we conducted studies in mice carrying a null mutation within the dtnbp1 gene. Dysbindin mutants showed impairments of spatial working memory compared with wild-type controls; heterozygous mice showed intermediate levels of cognitive dysfunction. Deep-layer pyramidal neurons recorded in the prefrontal cortex of mutant mice showed reductions in paired-pulse facilitation, and evoked and miniature excitatory post-synaptic currents, indicating a difference in the function of pre-synaptic glutamatergic terminals as well as elevated spike thresholds. Taken together, these data indicate that dysbindin potently regulates excitatory transmission in the prefrontal cortex, potentially through a pre-synaptic mechanism, and consequently modulates cognitive functions depending on this brain region, providing new insights into the molecular mechanisms underlying cortical dysfunction in schizophrenia.

Both working memory (WM) and controlled (attention-mediated) semantic processing functions have been thought to operate as limited capacity systems, but the possible link between these processes has not been investigated. We found that increased WM load attenuated semantic priming (i.e., reduced the response time advantage for semantically primed relative to unprimed items) and changed fMRI signal intensities in brain regions usually associated with both WM (dorsolateral prefrontal cortex) and controlled semantic retrieval (inferior frontal gyrus [IFG], pars orbitalis). fMRI signal changes in dorsolateral prefrontal cortex were negatively correlated with signal changes in pars orbitalis. The findings suggest that controlled semantic processing and working memory share neural system resources.

Having a first-degree relative with a psychotic disorder increases an individual's risk for developing psychosis to 10% compared to 1% in the general population. The impact of being at family high-risk for psychosis (FHR) has been examined in samples of youth who are at clinical high-risk for psychosis (CHR). The second North American Prodrome Longitudinal Study (NAPLS-2) identified very few clinical differences between CHR individuals with and without FHR. This paper aims to confirm these results in a new CHR sample, NAPLS-3. The NAPLS-3 sample consisted of 703 CHR participants, of whom 82 were at FHR (CHR+FHR), and 621 were not (CHR+FHRneg). The Family Interview for Genetic Studies was used to determine the presence of a first-degree relative with a psychotic disorder. The groups were compared on social and role functioning, positive and negative symptoms, IQ, cannabis use, and trauma. At baseline, the CHR+FHR group reported a statistically significant increased severity of positive and negative symptoms, lower IQ scores, and increased reports of trauma, psychological and physical abuse. There were no differences in transition rates between the two groups. This study supports some of the already reported differences in trauma, physical and psychological abuse between CHR individuals with and without FHR.

Psychotic symptoms are not only an important feature of severe neuropsychiatric disorders, but are also common in the general population, especially in youth. The genetic etiology of psychosis symptoms in youth remains poorly understood. To characterize genetic risk for psychosis spectrum symptoms (PS), we leverage a community-based multiethnic sample of children and adolescents aged 8-22 years, the Philadelphia Neurodevelopmental Cohort (n = 7225, 20% PS). Using an elastic net regression model, we aim to classify PS status using polygenic scores (PGS) based on a range of heritable psychiatric and brain-related traits in a multi-PGS model. We also perform univariate PGS associations and evaluate age-specific effects. The multi-PGS analyses do not improve prediction of PS status over univariate models, but reveal that the attention deficit hyperactivity disorder (ADHD) PGS is robustly and uniquely associated with PS (OR 1.12 (1.05, 1.18) P = 0.0003). This association is driven by subjects of European ancestry (OR = 1.23 (1.14, 1.34), P = 4.15 × 10-7) but is not observed in African American subjects (P = 0.65). We find a significant interaction of ADHD PGS with age (P = 0.01), with a stronger association in younger children. The association is independent of phenotypic overlap between ADHD and PS, not indirectly driven by substance use or childhood trauma, and appears to be specific to PS rather than reflecting general psychopathology in youth. In an independent sample, we replicate an increased ADHD PGS in 328 youth at clinical high risk for psychosis, compared to 216 unaffected controls (OR 1.06, CI(1.01, 1.11), P = 0.02). Our findings suggest that PS in youth may reflect a different genetic etiology than psychotic symptoms in adulthood, one more akin to ADHD, and shed light on how genetic risk can be investigated across early disease trajectories.

Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify "druggable" targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing.

Understanding the fundamental alterations in brain functioning that lead to psychotic disorders remains a major challenge in clinical neuroscience. In particular, it is unknown whether any state-independent biomarkers can potentially predict the onset of psychosis and distinguish patients from healthy controls, regardless of paradigm. Here, using multi-paradigm fMRI data from the North American Prodrome Longitudinal Study consortium, we show that individuals at clinical high risk for psychosis display an intrinsic "trait-like" abnormality in brain architecture characterized as increased connectivity in the cerebello-thalamo-cortical circuitry, a pattern that is significantly more pronounced among converters compared with non-converters. This alteration is significantly correlated with disorganization symptoms and predictive of time to conversion to psychosis. Moreover, using an independent clinical sample, we demonstrate that this hyperconnectivity pattern is reliably detected and specifically present in patients with schizophrenia. These findings implicate cerebello-thalamo-cortical hyperconnectivity as a robust state-independent neural signature for psychosis prediction and characterization.

Recent research has started to focus on identifying individuals who are at clinical high risk of developing psychosis as a means to try and understand the predictors and mechanisms involved in the progress to a full psychotic episode. The aim of the current study was to provide an initial description and prevalence rates of specific content found within attenuated positive symptoms. The Content of Attenuated Positive Symptoms (CAPS) codebook was used by independent raters to determine the presence of content within a sample of written vignettes. Krippendorff's alpha was used to determine inter-rater reliability. Overall, the majority of items fell in or above an acceptable range of reliability. There was heterogeneity present in the types of content endorsed. However, the most commonly endorsed items included being perplexed by reality, increased hypervigilence, being gifted, hearing indistinct and distinct sounds, seeing figures or shadows, something touching the individual, and unpleasant smells. The use of the CAPS codebook is a reliable way to code the content of attenuated positive symptoms. Identifying and monitoring the presence of certain content may provide insight into the presence of other comorbid issues and the potential for future conversion.

Recent years have witnessed an increasing number of multisite MRI functional connectivity (fcMRI) studies. While multisite studies provide an efficient way to accelerate data collection and increase sample sizes, especially for rare clinical populations, any effects of site or MRI scanner could ultimately limit power and weaken results. Little data exists on the stability of functional connectivity measurements across sites and sessions. In this study, we assess the influence of site and session on resting state functional connectivity measurements in a healthy cohort of traveling subjects (8 subjects scanned twice at each of 8 sites) scanned as part of the North American Prodrome Longitudinal Study (NAPLS). Reliability was investigated in three types of connectivity analyses: (1) seed-based connectivity with posterior cingulate cortex (PCC), right motor cortex (RMC), and left thalamus (LT) as seeds; (2) the intrinsic connectivity distribution (ICD), a voxel-wise connectivity measure; and (3) matrix connectivity, a whole-brain, atlas-based approach to assessing connectivity between nodes. Contributions to variability in connectivity due to subject, site, and day-of-scan were quantified and used to assess between-session (test-retest) reliability in accordance with Generalizability Theory. Overall, no major site, scanner manufacturer, or day-of-scan effects were found for the univariate connectivity analyses; instead, subject effects dominated relative to the other measured factors. However, summaries of voxel-wise connectivity were found to be sensitive to site and scanner manufacturer effects. For all connectivity measures, although subject variance was three times the site variance, the residual represented 60-80% of the variance, indicating that connectivity differed greatly from scan to scan independent of any of the measured factors (i.e., subject, site, and day-of-scan). Thus, for a single 5min scan, reliability across connectivity measures was poor (ICC=0.07-0.17), but increased with increasing scan duration (ICC=0.21-0.36 at 25min). The limited effects of site and scanner manufacturer support the use of multisite studies, such as NAPLS, as a viable means of collecting data on rare populations and increasing power in univariate functional connectivity studies. However, the results indicate that aggregation of fcMRI data across longer scan durations is necessary to increase the reliability of connectivity estimates at the single-subject level.

Disruptions in thalamic functional connectivity have been observed in people with schizophrenia and in youth at clinical high risk (CHR) of psychosis. However, the impact of environmental risk factors for psychosis on thalamic dysconnectivity is poorly understood. We tested whether thalamic dysconnectivity is related to patterns of cannabis use in a CHR sample.

Response inhibition is thought to improve throughout childhood and into adulthood. Despite the relationship between age and the ability to stop ongoing behavior, questions remain regarding whether these age-related changes reflect improvements in response inhibition or in other factors that contribute to response performance variability. Functional neuroimaging data shows age-related changes in neural activity during response inhibition. While traditional methods of exploring neuroimaging data are limited to determining correlational relationships, newer methods can determine predictability and can begin to answer these questions. Therefore, the goal of the current study was to determine which aspects of neural function predict individual differences in age, inhibitory function, response speed, and response time variability. We administered a stop-signal task requiring rapid inhibition of ongoing motor responses to healthy participants aged 9-30. We conducted a standard analysis using GLM and a predictive analysis using high-dimensional regression methods. During successful response inhibition we found regions typically involved in motor control, such as the ACC and striatum, that were correlated with either age, response inhibition (as indexed by stop-signal reaction time; SSRT), response speed, or response time variability. However, when examining which variables neural data could predict, we found that age and SSRT, but not speed or variability of response execution, were predicted by neural activity during successful response inhibition. This predictive relationship provides novel evidence that developmental differences and individual differences in response inhibition are related specifically to inhibitory processes. More generally, this study demonstrates a new approach to identifying the neurocognitive bases of individual differences.