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Abstract Recent failures translating preclinical behavioral treatment effects to positive clinical trial results in humans with Fragile X Syndrome (FXS) support refocusing attention on biological pathways and associated measures, such as electroencephalography (EEG), with strong translational potential and small molecule target engagement. This study utilized guided machine learning to test promising translational EEG measures (resting power and auditory chirp oscillatory variables) in a large heterogeneous sample of individuals with FXS to identify best performing EEG variables for reliably separating individuals with FXS, and genetically-mediated subgroups within FXS, from typically developing controls. Best performing variables included resting relative frontal theta power, all combined posterior-head resting power bands, posterior peak alpha frequency (PAF), combined PAF across all measured regions, combined theta, alpha, and gamma power during the chirp, and all combined chirp oscillatory variables. Sub-group analyses for resting EEG best discriminated non-mosaic FXS males via frontal theta resting relative power (AUC = 0.8759), even with data reduced to a 20-channel clinical montage (AUC = 0.9062). In the chirp task, FXS females and non-mosaic males were nearly perfectly discriminated by combined theta, alpha, and gamma power (AUC = 0.9444) and a combination of all variables (AUC = 0.9610), respectively. Results support use of resting and auditory oscillatory tasks to reliably identify neural deficit in FXS, and to identify specific translational targets for genetically-mediated sub-groups, supporting potential points for stratification.

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

Abstract Background Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are neurodevelopmental disorders with overlapping behavioral features and genetic etiology. While brain cortical thickness (CTh) alterations have been reported in ASD and ADHD separately, the degree to which ASD and ADHD are associated with common and distinct patterns of CTh changes is unclear. Methods We searched PubMed, Web of Science, Embase, and Science Direct from inception to 8 December 2023 and included studies of cortical thickness comparing youth (age less than 18) with ASD or ADHD with typically developing controls (TDC). We conducted a comparative meta-analysis of vertex-based studies to identify common and distinct CTh alterations in ASD and ADHD. Results Twelve ASD datasets involving 458 individuals with ASD and 10 ADHD datasets involving 383 individuals with ADHD were included in the analysis. Compared to TDC, ASD showed increased CTh in bilateral superior frontal gyrus, left middle temporal gyrus, and right superior parietal lobule (SPL) and decreased CTh in right temporoparietal junction (TPJ). ADHD showed decreased CTh in bilateral precentral gyri, right postcentral gyrus, and right TPJ relative to TDC. Conjunction analysis showed both disorders shared reduced TPJ CTh located in default mode network (DMN). Comparative analyses indicated ASD had greater CTh in right SPL and TPJ located in dorsal attention network and thinner CTh in right TPJ located in ventral attention network than ADHD. Conclusions These results suggest shared thinner TPJ located in DMN is an overlapping neurobiological feature of ASD and ADHD. This alteration together with SPL alterations might be related to altered biological motion processing in ASD, while abnormalities in sensorimotor systems may contribute to behavioral control problems in ADHD. The disorder-specific thinner TPJ located in disparate attention networks provides novel insight into distinct symptoms of attentional deficits associated with the two neurodevelopmental disorders. Trial registration PROSPERO CRD42022370620. Registered on November 9, 2022.

Summary: Background: Controllability analysis is an approach developed for evaluating the ability of a brain region to modulate function in other regions, which has been found to be altered in major depressive disorder (MDD). Both depressive symptoms and cognitive impairments are prominent features of MDD, but the case–control differences of controllability between MDD and controls can not fully interpret the contribution of both clinical symptoms and cognition to brain controllability and linked patterns among them in MDD. Methods: Sparse canonical correlation analysis was used to investigate the associations between resting-state functional brain controllability at the network level and clinical symptoms and cognition in 99 first-episode medication-naïve patients with MDD. Findings: Average controllability was significantly correlated with clinical features. The average controllability of the dorsal attention network (DAN) and visual network had the highest correlations with clinical variables. Among clinical variables, depressed mood, suicidal ideation and behaviour, impaired work and activities, and gastrointestinal symptoms were significantly negatively associated with average controllability, and reduced cognitive flexibility was associated with reduced average controllability. Interpretation: These findings highlight the importance of brain regions in modulating activity across brain networks in MDD, given their associations with symptoms and cognitive impairments observed in our study. Disrupted control of brain reconfiguration of DAN and visual network during their state transitions may represent a core brain mechanism for the behavioural impairments observed in MDD. Funding: National Natural Science Foundation of China (82001795 and 82027808), National Key R&D Program (2022YFC2009900), and Sichuan Science and Technology Program (2024NSFSC0653).

Abstract Investigation of the choroid plexus in schizophrenia has seen growing interest due to its role in the interaction between neuroinflammation and brain dysfunction. Most previous studies included treated and long-term ill patients, while antipsychotics and illness course might both affect the choroid plexus. Here, we recruited first-episode antipsychotic-naïve schizophrenia patients, performed high-resolution structural brain scan and manually extracted choroid plexus volume. Choroid plexus volume was compared between patients and healthy controls after controlling for age, sex and intracranial volume. Age and sex effects were examined on choroid plexus volume in patient and healthy control groups respectively. In patients, we also examined the correlation of choroid plexus volume with volume measures of cortical and subcortical gray matter, white matter, lateral ventricular as well as symptom severity and cognitive function. Schizophrenia patients showed significantly enlarged choroid plexus volume compared with healthy controls. Choroid plexus volume was positively correlated with age in only patient group and we found significantly larger choroid plexus volumes in males than females in both patient and healthy control groups, while the sex effects did not differ between groups. Choroid plexus volume was only found correlated with lateral ventricular volume among the brain volume measures. No significant correlation between choroid plexus volume and clinical ratings or cognitive performance was observed. Without potential confounding effects of pharmacotherapy or illness course, our findings indicated the enlargement of choroid plexus in schizophrenia might be an enduring trait for schizophrenia.

Abstract Although attention-deficit/hyperactivity disorder (ADHD) and a family history of bipolar I disorder (BD) are associated with increased risk for developing BD, their neuroanatomical substrates remain poorly understood. This study compared cortical and subcortical gray matter morphology in psychostimulant-free ADHD youth with and without a first-degree relative with BD and typically developing healthy controls. ADHD youth (ages 10-18 years) with (‘high-risk’, HR) or without (‘low-risk’, LR) a first-degree relative with BD and healthy comparison youth (HC) were enrolled. High-resolution 3D T1-weighted images were acquired using a Philips 3.0 T MR scanner. The FreeSurfer image analysis suite was used to measure cortical thickness, surface area, and subcortical volumes. A general linear model evaluated group differences in MRI features with age and sex as covariates, and exploratory correlational analyses evaluated associations with symptom ratings. A total of n = 142 youth (mean age: 14.16 ± 2.54 years, 35.9% female) were included in the analysis (HC, n = 48; LR, n = 49; HR, n = 45). The HR group exhibited a more severe symptom profile, including higher mania and dysregulation scores, compared to the LR group. For subcortical volumes, the HR group exhibited smaller bilateral thalamic, hippocampal, and left caudate nucleus volumes compared to both LR and HC, and smaller right caudate nucleus compared with LR. No differences were found between LR and HC groups. For cortical surface area, the HR group exhibited lower parietal and temporal surface area compared with HC and LR, and lower orbitofrontal and superior frontal surface area compared to LR. The HR group exhibited lower left anterior cingulate surface area compared with HC. LR participants exhibited greater right pars opercularis surface area compared with the HC. Some cortical alterations correlated with symptom severity ratings. These findings suggest that ADHD in youth with a BD family history is associated with a more a severe symptom profile and a neuroanatomical phenotype that distinguishes it from ADHD without a BD family history.

Abstract Traditional diagnostic formulations of psychotic disorders have low correspondence with underlying disease neurobiology. This has led to a growing interest in using brain-based biomarkers to capture biologically-informed psychosis constructs. Building upon our prior work on the B-SNIP Psychosis Biotypes, we aimed to examine whether structural MRI (an independent biomarker not used in the Biotype development) can effectively classify the Biotypes. Whole brain voxel-wise grey matter density (GMD) maps from T1-weighted images were used to train and test (using repeated randomized train/test splits) binary L2-penalized logistic regression models to discriminate psychosis cases (n = 557) from healthy controls (CON, n = 251). A total of six models were evaluated across two psychosis categorization schemes: (i) three Biotypes (B1, B2, B3) and (ii) three DSM diagnoses (schizophrenia (SZ), schizoaffective (SAD) and bipolar (BD) disorders). Above-chance classification accuracies were observed in all Biotype (B1 = 0.70, B2 = 0.65, and B3 = 0.56) and diagnosis (SZ = 0.64, SAD = 0.64, and BD = 0.59) models. However, the only model that showed evidence of specificity was B1, i.e., the model was able to discriminate B1 vs. CON and did not misclassify other psychosis cases (B2 or B3) as B1 at rates above nominal chance. The GMD-based classifier evidence for B1 showed a negative association with an estimate of premorbid general intellectual ability, regardless of group membership, i.e. psychosis or CON. Our findings indicate that, complimentary to clinical diagnoses, the B-SNIP Psychosis Biotypes may offer a promising approach to capture specific aspects of psychosis neurobiology.

Objective: Fragile X Syndrome (FXS) is the leading monogenic cause of intellectual disability and autism spectrum disorder. Currently, there are no established biomarkers for predicting and monitoring drug effects in FXS, and no approved therapies are available. Previous studies have shown electrophysiological changes in the brain using electroencephalography (EEG) in individuals with FXS and animal models. These changes may be influenced by drug therapies. In this study, we aimed to assess the reliability of resting-state EEG measures in individuals with FXS, which could potentially serve as a biomarker for drug discovery. Methods: We collected resting-state EEG data from 35 individuals with FXS participating in placebo-controlled clinical trials (23 males, 12 females; visit age mean+/-std 25.6 +/−8.3). The data were analyzed for various spectral features using intraclass correlation analysis to evaluate test-retest reliability. The intervals between EEG recordings ranged from same-day measurements to up to six weeks apart. Results: Our results showed high reliability for most spectral features, with same-day reliability exceeding 0.8. Features of interest demonstrated ICC values of 0.60 or above at longer intervals. Among the features, alpha band relative power exhibited the highest reliability. Conclusion: These findings indicate that resting-state EEG can provide consistent and reproducible measures of brain activity in individuals with FXS. This supports the potential use of EEG as an objective biomarker for evaluating the effects of new drugs in FXS. Significance: The reliable measurements obtained from power spectrum-based resting-state EEG make it a promising tool for assessing the impact of small molecule drugs in FXS.

Abstract Background Fragile X syndrome (FXS) is the leading inherited monogenic cause of intellectual disability and autism spectrum disorder. Executive function (EF), necessary for adaptive goal-oriented behavior and dependent on frontal lobe function, is impaired in individuals with FXS. Yet, little is known how alterations in frontal lobe neural activity is related to EF deficits in FXS. Methods Sixty-one participants with FXS (54% males) and 71 age- and sex-matched typically-developing controls (TDC; 58% males) completed a five-minute resting state electroencephalography (EEG) protocol and a computerized battery of tests of EF, the Test of Attentional Performance for Children (KiTAP). Following source localization (minimum-norm estimate), we computed debiased weighted phase lag index (dWPLI), a phase connectivity value, for pairings between 18 nodes in frontal regions for gamma (30–55 Hz) and alpha (10.5–12.5 Hz) bands. Linear models were generated with fixed factors of group, sex, frequency, and connection. Relationships between frontal connectivity and EF variables also were examined. Results Individuals with FXS demonstrated increased gamma band and reduced alpha band connectivity across all frontal regions and across hemispheres compared to TDC. After controlling for nonverbal IQ, increased error rates on EF tasks were associated with increased gamma band and reduced alpha band connectivity. Limitations Frontal connectivity findings are limited to intrinsic brain activity during rest and may not generalize to frontal connectivity during EF tasks or everyday function. Conclusions We report gamma hyper-connectivity and alpha hypo-connectivity within source-localized frontal brain regions in FXS compared to TDC during resting-state EEG. For the first time in FXS, we report significant associations between EF and altered frontal connectivity, with increased error rate relating to increased gamma band connectivity and reduced alpha band connectivity. These findings suggest increased phase connectivity within gamma band may impair EF performance, whereas greater alpha band connectivity may provide compensatory support for EF. Together, these findings provide important insight into neurophysiological mechanisms of EF deficits in FXS and provide novel targets for treatment development.

Abstract Background Fragile X syndrome (FXS) is the most common inherited form of neurodevelopmental disability. It is often characterized, especially in males, by intellectual disability, anxiety, repetitive behavior, social communication deficits, delayed language development, and abnormal sensory processing. Recently, we identified electroencephalographic (EEG) biomarkers that are conserved between the mouse model of FXS (Fmr1 KO mice) and humans with FXS. Methods In this report, we evaluate small molecule target engagement utilizing multielectrode array electrophysiology in the Fmr1 KO mouse and in humans with FXS. Neurophysiologic target engagement was evaluated using single doses of the GABAB selective agonist racemic baclofen (RBAC). Results In Fmr1 KO mice and in humans with FXS, baclofen use was associated with suppression of elevated gamma power and increase in low-frequency power at rest. In the Fmr1 KO mice, a baclofen-associated improvement in auditory chirp synchronization was also noted. Conclusions Overall, we noted synchronized target engagement of RBAC on resting state electrophysiology, in particular the reduction of aberrant high frequency gamma activity, across species in FXS. This finding holds promise for translational medicine approaches to drug development for FXS, synchronizing treatment study across species using well-established EEG biological markers in this field. Trial registration The human experiments are registered under NCT02998151.

Abstract Repetitive transcranial magnetic stimulation (rTMS) is increasingly used to treat neuropsychiatric disorders. Inhibitory and excitatory regimens have been both adopted but the exact mechanism of action remains unclear, and investigating their differential effects on laminar diffusion profiles of neocortex may add important evidence. Twenty healthy participants were randomly assigned to receive a low‐frequency/inhibitory or high‐frequency/excitatory rTMS targeting the left dorsolateral prefrontal cortex (DLPFC). With the brand‐new submillimeter diffusion tensor imaging of whole brain and specialized surface‐based laminar analysis, fractional anisotropy (FA) and mean diffusion (MD) profiles of cortical layers at different cortical depths were characterized before/after rTMS. Inhibitory and excitatory rTMS both showed impacts on diffusion metrics of somatosensory, limbic, and sensory regions, but different patterns of changes were observed—increased FA with inhibitory rTMS, whereas decreased FA with excitatory rTMS. More importantly, laminar analysis indicated laminar specificity of changes in somatosensory regions during different rTMS patterns—inhibitory rTMS affected the superficial layers contralateral to the DLPFC, while excitatory rTMS led to changes in the intermediate/deep layers bilateral to the DLPFC. These findings provide novel insights into acute neurobiological effects on diffusion profiles of rTMS that may add critical evidence relevant to different protocols of rTMS on neocortex.

Abstract Human brains experience whole-brain anatomic and functional changes throughout the lifespan. Age-related whole-brain network changes have been studied with functional magnetic resonance imaging (fMRI) to determine their low-frequency spatial and temporal characteristics. However, little is known about age-related changes in whole-brain fast dynamics at the scale of neuronal events. The present study investigated age-related whole-brain dynamics in resting-state electroencephalography (EEG) signals from 73 healthy participants from 6 to 65 years old via characterizing transient neuronal coactivations at a resolution of tens of milliseconds. These uncovered transient patterns suggest fluctuating brain states at different energy levels of global activations. Our results indicate that with increasing age, shorter lifetimes and more occurrences were observed in the brain states that show the global high activations and more consecutive visits to the global highest-activation brain state. There were also reduced transitional steps during consecutive visits to the global lowest-activation brain state. These age-related effects suggest reduced stability and increased fluctuations when visiting high-energy brain states and with a bias toward staying low-energy brain states. These age-related whole-brain dynamics changes are further supported by changes observed in classic alpha and beta power, suggesting its promising applications in examining the effect of normal healthy brain aging, brain development, and brain disease.

Summary: Background: Identifying individuals at risk for severe mental illness (SMI) is crucial for prevention and early intervention strategies. While MRI shows potential for case identification even before illness onset, no practical model for mental health risk monitoring has been developed. This study aims to develop an initial version of an efficient and practical model for mental health screening among at-risk populations. Methods: A deep learning model known as Multiple Instance Learning (MIL) was adopted to train and test a SMI detection model with clinical MRI scans of 14,915 patients with SMI (age 32.98 ± 12.01 years, 9102 women) and 4538 healthy controls (age 40.60 ± 10.95 years, 2424 women) in the primary dataset. Validation analysis was conducted in an independent dataset with 290 patients (age 28.08 ± 10.95 years, 169 women) and 310 healthy participants (age 33.55 ± 11.09 years, 165 women). Another three machine learning models of ResNet, DenseNet and EfficientNet were used for comparison. We also recruited 148 individuals receiving high-stress medical school education to characterize the potential real-world utility of the MIL model in detecting risk of mental illness. Findings: Similar performance of successful differentiation of individuals with SMI and healthy controls was observed for the MIL model (AUC: 0.82) and other models (ResNet, DenseNet, EfficientNet, 0.83, 0.81, and 0.80 respectively). MIL had better generalization in the validation test than other models (AUC: 0.82 vs 0.59, 0.66 and 0.59), and less drop-off in performance from 3.0T to 1.5T scanners. The MIL model did better in predicting clinician ratings of distress than self-ratings with questionnaires (84% vs 22%) in the medical student sample. Brain regions that contributed to SMI identification were mainly neocortical, including right precuneus, bilateral temporal regions, left precentral/postcentral gyrus, bilateral medial prefrontal cortex and right cerebellum. Interpretation: Our digital model based on brief clinical MRI protocols identified individual SMI patients with good accuracy and high sensitivity, suggesting that with incremental improvements the approach may offer potentially useful aid for early identification and intervention to prevent illness onset in vulnerable at-risk populations. Funding: This study was supported by the National Natural Science Foundation of China, National Key Technologies R&D Program of China, and Sichuan Science and Technology Program.

Abstract Magnetization transfer imaging (MTI) may provide more sensitivity and mechanistic understanding of neuropathological changes associated with schizophrenia than volumetric MRI. This study aims to identify brain magnetization transfer ratio (MTR) changes in antipsychotic-naïve first-episode schizophrenia (FES), and to correlate MTR findings with clinical symptom severity. A total of 143 individuals with antipsychotic-naïve FES and 147 healthy controls (HCs) were included and underwent 3.0 T brain MTI between August 2005 and July 2014. Voxelwise analysis was performed to test for MTR differences with family-wise error corrections. Relationships of these differences to symptom severity were assessed using partial correlations. Exploratory analyses using a support vector machine (SVM) classifier were conducted to discriminate FES from HCs using MTR maps. Model performance was examined using a 10-fold stratified cross-validation. Compared with HCs, individuals with FES exhibited higher MTR values in left thalamus, precuneus, cuneus, and paracentral lobule, that were positively correlated with schizophrenia symptom severity [precuneus (r = 0.34, P = 0.0004), cuneus (r = 0.33, P = 0.0006) and paracentral lobule (r = 0.37, P = 0.001)]. Whole-brain MTR maps identified individuals with FES with overall accuracy 75.5% (219 of 290 individuals) based on SVM approach. In antipsychotic-naïve FES, clinically relevant biophysical abnormalities detected by MTI mainly in the left parieto-occipital regions are informative about local brain pathology, and have potential as diagnostic markers.

A large EEG dataset from 70 patients with Fragile X syndrome reveals unique changes in neural activity and highlight the role for disrupted thalamocortical modulation in local hyperexcitability.

Abstract Few technologies have been mired in hype more than blockchain, which is the underlying peer-to-peer network protocol for cryptocurrencies such as Bitcoin. Given the technology’s emphasis on purported “immutable ledgers” and trust-less sharing models, there has been a great deal of interest in applying blockchain to democratic reforms. From localized decision-making to national-scale voting systems, blockchain has spurred a surge of interest in how democracy might “get a software update”. While significant research exists on socio-technological imaginaries (perceptions) and potential applications (experiments) within the Global North, few studies have looked at more dynamic contexts, particularly Central Asia. In light of the violence surrounding elections in October 2020 and previous revolutions against the country’s central government, the status of democracy in Kyrgyzstan is, at best, fragile and, at worst, non-existent. This article explores alternative futures scenarios for localized, blockchain-driven governance futures in Kyrgyzstan and concludes with a proposal for deeper investigation.

IntroductionFragile X Syndrome (FXS) is rare genetic condition characterized by a repeat expansion (CGG) in the Fragile X messenger ribonucleoprotein 1 (FMR1) gene where individuals with greater than 200 repeats are defined as full mutation. FXS clinical presentation often includes intellectual disability, and autism-like symptoms, including anxiety and sensory hypersensitivities. Individuals with 55 to

IntroductionFragile X Syndrome (FXS) is a monogenic condition that leads to intellectual disability along with behavioral and learning difficulties. Among behavioral and learning difficulties, cognitive flexibility impairments are among the most commonly reported in FXS, which significantly impacts daily living. Despite the extensive use of the Fmr1 knockout (KO) mouse to understand molecular, synaptic and behavioral alterations related to FXS, there has been limited development of translational paradigms to understand cognitive flexibility that can be employed in both animal models and individuals with FXS to facilitate treatment development.MethodsTo begin addressing this limitation, a parallel set of studies were carried out that investigated probabilistic reversal learning along with other behavioral and cognitive tests in individuals with FXS and Fmr1 KO mice. Fifty-five adolescents and adults with FXS (67% male) and 34 age- and sex-matched typically developing controls (62% male) completed an initial probabilistic learning training task and a probabilistic reversal learning task.ResultsIn males with FXS, both initial probabilistic learning and reversal learning deficits were found. However, in females with FXS, we only observed reversal learning deficits. Reversal learning deficits related to more severe psychiatric features in females with FXS, whereas increased sensitivity to negative feedback (lose:shift errors) unexpectedly appear to be adaptive in males with FXS. Male Fmr1 KO mice exhibited both an initial probabilistic learning and reversal learning deficit compared to that of wildtype (WT) mice. Female Fmr1 KO mice were selectively impaired on probabilistic reversal learning. In a prepotent response inhibition test, both male and female Fmr1 KO mice were impaired in learning to choose a non-preferred spatial location to receive a food reward compared to that of WT mice. Neither male nor female Fmr1 KO mice exhibited a change in anxiety compared to that of WT mice.DiscussionTogether, our findings demonstrate strikingly similar sex-dependent learning disturbances across individuals with FXS and Fmr1 KO mice. This suggests the promise of using analogous paradigms of cognitive flexibility across species that may speed treatment development to improve lives of individuals with FXS.

Spontaneous neural activity in human as assessed with resting-state functional magnetic resonance imaging (fMRI) exhibits brain-wide coordinated patterns in the frequency of

Abstract Background Sensorimotor issues are common in autism spectrum disorder (ASD), related to core symptoms, and predictive of worse functional outcomes. Deficits in rapid behaviors supported primarily by feedforward mechanisms, and continuous, feedback-guided motor behaviors each have been reported, but the degrees to which they are distinct or co-segregate within individuals and across development are not well understood. Methods We characterized behaviors that varied in their involvement of feedforward control relative to feedback control across skeletomotor (precision grip force) and oculomotor (saccades) control systems in 109 individuals with ASD and 101 age-matched typically developing controls (range: 5–29 years) including 58 individuals with ASD and 57 controls who completed both grip and saccade tests. Grip force was examined across multiple force (15, 45, and 85% MVC) and visual gain levels (low, medium, high). Maximum grip force also was examined. During grip force tests, reaction time, initial force output accuracy, variability, and entropy were examined. For the saccade test, latency, accuracy, and trial-wise variability of latency and accuracy were examined. Results Relative to controls, individuals with ASD showed similar accuracy of initial grip force but reduced accuracy of saccadic eye movements specific to older ages of our sample. Force variability was greater in ASD relative to controls, but saccade gain variability (across trials) was not different between groups. Force entropy was reduced in ASD, especially at older ages. We also find reduced grip strength in ASD that was more severe in dominant compared to non-dominant hands. Limitations Our age-related findings rely on cross-sectional data. Longitudinal studies of sensorimotor behaviors and their associations with ASD symptoms are needed. Conclusions We identify reduced accuracy of initial motor output in ASD that was specific to the oculomotor system implicating deficient feedforward control that may be mitigated during slower occurring behaviors executed in the periphery. Individuals with ASD showed increased continuous force variability but similar levels of trial-to-trial saccade accuracy variability suggesting that feedback-guided refinement of motor commands is deficient specifically when adjustments occur rapidly during continuous behavior. We also document reduced lateralization of grip strength in ASD implicating atypical hemispheric specialization.

Abstract Background Fragile X syndrome is characterized by a myriad of physical features, behavioral features, and medical problems. Commonly found behavioral features are hyperactivity, anxiety, socialization difficulties, and ASD. There is also a higher incidence than in the general population of strabismus, otitis media, and mitral valve prolapse. In addition, one of the most common medical problems associated with FXS is an increased risk of seizures. A subset of individuals carrying the full mutation of the FMR1 gene and diagnosed with fragile X syndrome (FXS) are reported to experience seizures, mostly during the first 10 years of their life span. Methods As part of a larger project to identify genetic variants that modify the risk of seizures, we collected clinical information from 49 carriers with FXS who experienced seizures and 46 without seizures. We compared seizure type and comorbid conditions based on the source of data as well as family history of seizures. Results We found that the concordance of seizure types observed by parents and medical specialists varied by type of seizure. The most common comorbid condition among those with seizures was autism spectrum disorder (47% per medical records vs. 33% per parent report compared with 19% among those without seizures per parent report); the frequency of other comorbid conditions did not differ among groups. We found a slightly higher frequency of family members who experienced seizures among the seizure group compared with the nonseizure group. Conclusion This study confirms previously reported features of seizures in FXS, supports additional genetic factors, and highlights the importance of information sources, altogether contributing to a better understanding of seizures in FXS.

Cardiometabolic disorders have known inflammatory implications, and peripheral measures of inflammation and cardiometabolic disorders are common in persons with psychotic disorders. Inflammatory signatures are also related to neurobiological and behavioral changes in psychosis. Relationships between systemic inflammation and cardiometabolic genetic risk in persons with psychosis have not been examined. Thirteen peripheral inflammatory markers and genome-wide genotyping were assessed in 122 participants (n ​= ​86 psychosis, n ​= ​36 healthy controls) of European ancestry. Cluster analyses of inflammatory markers classified higher and lower inflammation subgroups. Single-trait genetic risk scores (GRS) were constructed for each participant using previously reported GWAS summary statistics for the following traits: schizophrenia, bipolar disorder, major depressive disorder, coronary artery disease, type-2 diabetes, low-density lipoprotein, high-density lipoprotein, triglycerides, and waist-to-hip ratio. Genetic correlations across traits were quantified. Principal component (PC) analysis of the cardiometabolic GRSs generated six PC loadings used in regression models to examine associations with inflammation markers. Functional module discovery explored biological mechanisms of the inflammation association of cardiometabolic GRS genes. A subgroup of 38% persons with psychotic disorders was characterized with higher inflammation status. These higher inflammation individuals had lower BACS scores (p ​= ​0.038) compared to those with lower inflammation. The first PC of the cardiometabolic GRS matrix was related to higher inflammation status in persons with psychotic disorders (OR ​= ​2.037, p ​= ​0.001). Two of eight modules within the functional interaction network of cardiometabolic GRS genes were enriched for immune processes. Cardiometabolic genetic risk may predispose some individuals with psychosis to elevated inflammation which adversely impacts cognition associated with illness.

Abstract Background Given that psychopharmacological approaches routinely used to treat mood-related problems may result in adverse outcomes in mood dysregulated adolescents at familial risk for bipolar disorder (BD), Mindfulness-Based Cognitive Therapy for Children (MBCT-C) provides an alternative effective and safe option. However, little is known about the brain mechanisms of beneficial outcomes from this intervention. Herein, we aimed to investigate the network-level neurofunctional effects of MBCT-C in mood dysregulated adolescents. Methods Ten mood dysregulated adolescents at familial risk for BD underwent a 12-week MBCT-C intervention. Resting-state functional magnetic resonance imaging (fMRI) was performed prior to and following MBCT-C. Topological metrics of three intrinsic functional networks (default mode network (DMN), fronto-parietal network (FPN) and cingulo-opercular network (CON)) were investigated respectively using graph theory analysis. Results Following MBCT-C, mood dysregulated adolescents showed increased global efficiency and decreased characteristic path length within both CON and FPN. Enhanced functional connectivity strength of frontal and limbic areas were identified within the DMN and CON. Moreover, change in characteristic path length within the CON was suggested to be significantly related to change in the Emotion Regulation Checklist score. Conclusions 12-week MBCT-C treatment in mood dysregulated adolescents at familial risk for BD yield network-level neurofunctional effects within the FPN and CON, suggesting enhanced functional integration of the dual-network. Decreased characteristic path length of the CON may be associated with the improvement of emotion regulation following mindfulness training. However, current findings derived from small sample size should be interpreted with caution. Future randomized controlled trials including larger samples are critical to validate our findings.

BackgroundSensorimotor issues are common in autism spectrum disorder (ASD), though their neural bases are not well understood. The cerebellum is vital to sensorimotor control and reduced cerebellar volumes in ASD have been documented. Our study examined the extent to which cerebellar volumes are associated with multiple sensorimotor behaviors in ASD.Materials and MethodsFifty-eight participants with ASD and 34 typically developing (TD) controls (8–30 years) completed a structural MRI scan and precision grip testing, oculomotor testing, or both. Force variability during precision gripping as well as absolute error and trial-to-trial error variability of visually guided saccades were examined. Volumes of cerebellar lobules, vermis, and white matter were quantified. The relationships between each cerebellar region of interest (ROI) and force variability, saccade error, and saccade error variability were examined.ResultsRelative to TD controls, individuals with ASD showed increased force variability. Individuals with ASD showed a reduced volume of cerebellar vermis VI-VII relative to TD controls. Relative to TD females, females with ASD showed a reduced volume of bilateral cerebellar Crus II/lobule VIIB. Increased volume of Crus I was associated with increased force variability. Increased volume of vermal lobules VI-VII was associated with reduced saccade error for TD controls but not individuals with ASD. Increased right lobule VIII and cerebellar white matter volumes as well as reduced right lobule VI and right lobule X volumes were associated with greater ASD symptom severity. Reduced volumes of right Crus II/lobule VIIB were associated with greater ASD symptom severity in only males, while reduced volumes of right Crus I were associated with more severe restricted and repetitive behaviors only in females.ConclusionOur finding that increased force variability in ASD is associated with greater cerebellar Crus I volumes indicates that disruption of sensory feedback processing supported by Crus I may contribute to skeletomotor differences in ASD. Results showing that volumes of vermal lobules VI-VII are associated with saccade precision in TD but not ASD implicates atypical organization of the brain systems supporting oculomotor control in ASD. Associations between volumes of cerebellar subregions and ASD symptom severity suggest cerebellar pathological processes may contribute to multiple developmental challenges in ASD.

Summary: Background: Establishing objective and quantitative neuroimaging biomarkers at individual level can assist in early and accurate diagnosis of major depressive disorder (MDD). However, most previous studies using machine learning to identify MDD were based on small sample size and did not account for the brain connectome that is associated with the pathophysiology of MDD. Here, we addressed these limitations by applying graph convolutional network (GCN) in a large multi-site MDD dataset. Methods: Resting-state functional MRI scans of 1586 participants (821 MDD vs. 765 controls) across 16 sites of Rest-meta-MDD consortium were collected. GCN model was trained with individual whole-brain functional network to identify MDD patients from controls, characterize the most salient regions contributing to classification, and explore the relationship between topological characteristics of salient regions and clinical measures. Findings: GCN achieved an accuracy of 81·5% (95%CI: 80·5–82·5%, AUC: 0·865), which was higher than other common machine learning classifiers. The most salient regions contributing to classification were primarily identified within the default mode, fronto-parietal, and cingulo-opercular networks. Nodal topologies of the left inferior parietal lobule and left dorsolateral prefrontal cortex were associated with depressive severity and illness duration, respectively. Interpretation: These findings based on a large, multi-site dataset support the feasibility and effectiveness of GCN in characterizing MDD, and also illustrate the potential utility of GCN for enhancing understanding of the neurobiology of MDD by detecting clinically-relevant disruption in functional network topology. Funding: This study was supported by the National Natural Science Foundation of China (Grant Nos. 81621003, 82027808, 81820108018).

Abstract Chronic pain surrounding the temporomandibular joints and masticatory muscles is often the primary chief complaint of patients with temporomandibular disorders (TMD) seeking treatment. Yet, the neuro-pathophysiological basis underlying it remains to be clarified. Neuroimaging techniques have provided a deeper understanding of what happens to brain structure and function in TMD patients with chronic pain. Therefore, we performed a systematic review of magnetic resonance imaging (MRI) studies investigating structural and functional brain alterations in TMD patients to further unravel the neurobiological underpinnings of TMD-related pain. Online databases (PubMed, EMBASE, and Web of Science) were searched up to August 3, 2019, as complemented by a hand search in reference lists. A total of 622 papers were initially identified after duplicates removed and 25 studies met inclusion criteria for this review. Notably, the variations of MRI techniques used and study design among included studies preclude a meta-analysis and we discussed the findings qualitatively according to the specific neural system or network the brain regions were involved in. Brain changes were found in pathways responsible for abnormal pain perception, including the classic trigemino-thalamo-cortical system and the lateral and medial pain systems. Dysfunction and maladaptive changes were also identified in the default mode network, the top-down antinociceptive periaqueductal gray-raphe magnus pathway, as well as the motor system. TMD patients displayed altered brain activations in response to both innocuous and painful stimuli compared with healthy controls. Additionally, evidence indicates that splint therapy can alleviate TMD-related symptoms by inducing functional brain changes. In summary, MRI research provides important novel insights into the altered neural manifestations underlying chronic pain in TMD.

Over 200 Cytosine-guanine-guanine (CGG) trinucleotide repeats in the 5′ untranslated region of the Fragile X mental retardation 1 (FMR1) gene results in a “full mutation,” clinically Fragile X Syndrome (FXS), whereas 55 – 200 repeats result in a “premutation.” FMR1 premutation carriers (PMC) are at an increased risk for a range of psychiatric, neurocognitive, and physical conditions. Few studies have examined the variable expression of neuropsychiatric features in female PMCs, and whether heterogeneous presentation among female PMCs may reflect differential presentation of features in unique subgroups. In the current pilot study, we examined 41 female PMCs (ages 17–78 years) and 15 age-, sex-, and IQ-matched typically developing controls (TDC) across a battery of self-report, eye tracking, expressive language, neurocognitive, and resting state EEG measures to determine the feasibility of identifying discrete clusters. Secondly, we sought to identify the key features that distinguished these clusters of female PMCs. We found a three cluster solution using k-means clustering. Cluster 1 represented a psychiatric feature group (27% of our sample); cluster 2 represented a group with executive dysfunction and elevated high frequency neural oscillatory activity (32%); and cluster 3 represented a relatively unaffected group (41%). Our findings indicate the feasibility of using a data-driven approach to identify naturally occurring clusters in female PMCs using a multi-method assessment battery. CGG repeat count and its association with neuropsychiatric features differ across clusters. Together, our findings provide important insight into potential diverging pathophysiological mechanisms and risk factors for each female PMC cluster, which may ultimately help provide novel and individualized targets for treatment options.

Abstract Background Diminished cognitive control, including reduced behavioral flexibility and behavioral response inhibition, has been repeatedly documented in autism spectrum disorder (ASD). We evaluated behavioral flexibility and response inhibition in probands and their parents using a family trio design to determine the extent to which these cognitive control impairments represent familial traits associated with ASD. Methods We examined 66 individuals with ASD (probands), 135 unaffected biological parents, and 76 typically developing controls. Participants completed a probabilistic reversal learning task (PRL) and a stop-signal task (SST) to assess behavioral flexibility and response inhibition respectively. Rates of PRL and SST errors were examined across groups, within families, and in relation to clinical and subclinical traits of ASD. Based on prior findings that subclinical broader autism phenotypic (BAP) traits may co-segregate within families and reflect heritable risk factors, we also examined whether cognitive control deficits were more prominent in families in which parents showed BAP features (BAP+). Results Probands and parents each showed increased rates of PRL and SST errors relative to controls. Error rates across tasks were not related. SST error rates inter-correlated among probands and their parents. PRL errors were more severe in BAP+ parents and their children relative to BAP− parents and their children. For probands of BAP+ parents, PRL and SST error rates were associated with more severe social-communication abnormalities and repetitive behaviors, respectively. Conclusion Reduced behavioral flexibility and response inhibition are present among probands and their unaffected parents, but represent unique familial deficits associated with ASD that track with separate clinical issues. Specifically, behavioral response inhibition impairments are familial in ASD and manifest independently from parental subclinical features. In contrast, behavioral flexibility deficits are selectively present in families with BAP characteristics, suggesting they co-segregate in families with parental subclinical social, communication, and rigid personality traits. Together, these findings provide evidence that behavioral flexibility and response inhibition impairments track differentially with ASD risk mechanisms and related behavioral traits.

Background: The hippocampus (HP) is affected across psychoses, including schizophrenia (SZ), bipolar type 1 (BDP) and schizoaffective (SAD) disorders. We examined HP subfield volumetric abnormalities along the anterior-posterior (ventral-dorsal) axis of the HP in psychosis probands, defined by traditional (DSM) diagnoses and biologically defined subtypes (biotypes, based on cognition and electrophysiology). We hypothesized that biotypes would be better discriminated by HP longitudinal axis subfields abnormalities than DSM. Methods: The sample included 455 probands from the Bipolar Schizophrenia Network for intermediate Phenotypes (BSNIP) dataset (age 35 ± 12.0): 124 unaffected (age 40.4 ± 15.8) and 299 healthy controls (HC; 37 ± 12.0). Probands were: SZ (190), BDP (151), SAD (114). Probands according to B-SNIP defined biotypes were: biotype-1 (BT1; 120), biotype-2 (BT2; 145), biotype-3 (BT3, 190). 3 T MRI scans were processed with FreeSurfer6.0. The anterior (aHP) and posterior (pHP) HP and aHP and pHP subfields were extracted. Cognitive and clinical data were collected. Results: All biotypes had smaller aHP subfields compared to HC. BT1 had smaller aHP than both BT2 and BT3. pHP subfields were also smaller in BT1 compared to HC and BT3, while the granule cells layer of the dentate gyrus distinguished BT2 from HC. DSM: aHP subfields were smaller in all DSM types compared to HC and did not differ among DSM categories. A few pHP subfields were affected in SAD and SZ compared to HC and distinguished SAD and SZ from BDP. Probands had smaller aHP compared to unaffected relatives. Conclusions: Differences in subfield volumetric abnormalities along the anterior- posterior axis of the HP exist across psychoses. aHP abnormalities differ between psychosis probands and HC but do not discriminate among DSM categories. In contrast, biotypes can be differentiated from HC and from each other according to aHP-pHP subfields volumetric abnormalities. Thus, biotype typology may better reflect underlying neurobiology.

Background: Convergent evidence is increasing to indicate progressive brain abnormalities in schizophrenia. Knowing the brain network features over the illness course in schizophrenia, independent of effects of antipsychotic medications, would extend our sight on this question. Methods: We recruited 237 antipsychotic-naive patients with schizophrenia range from 16 to 73 years old, and 254 healthy controls. High-resolution T1 weighted images were obtained with a 3.0T MR scanner. Grey matter networks were constructed individually based on the similarities of regional grey matter measurements. Network metrics were compared between patient groups and healthy controls, and regression analyses with age were conducted to determine potential differential rate of age-related changes between them. Findings: Nodal centrality abnormalities were observed in patients with untreated schizophrenia, particularly in the central executive, default mode and salience networks. Accelerated age-related declines and illness duration-related declines were observed in global assortativity, and in nodal metrics of left superior temporal pole in schizophrenia patients. Although no significant intergroup differences in age-related regression were observed, the pattern of network metric alternation of left thalamus indicated higher nodal properties in early course patients, which decreased in long-term ill patients. Interpretations: Global and nodal alterations in the grey matter connectome related to age and duration of illness in antipsychotic-naive patients, indicating potentially progressive network organizations mainly involving temporal regions and thalamus in schizophrenia independent from medication effects. Funding: The National Natural Science Foundation of China, Sichuan Science and Technology Program, the Fundamental Research Funds for the Central Universities, Post-Doctor Research Project, West China Hospital, Sichuan University , the Science and Technology Project of the Health Planning Committee of Sichuan, Postdoctoral Interdisciplinary Research Project of Sichuan University and 1.3.5 Project for Disciplines of Excellence, West China Hospital, Sichuan University.

Our current diagnostic methods for treatment planning in Psychiatry and Neurodevelopmental Disabilities leave room for improvement, and null results in clinical trials in these fields may be a result of insufficient tools for patient stratification. Great hope has been placed in novel technologies to improve clinical and trial outcomes, but we have yet to see a substantial change in clinical practice. As we examine attempts at biomarker validation within these fields, we find that it may be the diagnoses themselves that fall short. We now need to improve neuropsychiatric nosologies with a focus on validity based not solely on behavioral features, but on a synthesis that includes genetic and biological data as well. The eventual goal is diagnostic biomarkers and diagnoses themselves based on distinct mechanisms, but such an understanding of the causal relationship across levels of analysis is likely to be elusive for some time. Rather, we propose an approach in the near-term that deconstructs diagnosis into a series of independent, empiric and clinically relevant associations among a single, defined patient group, a single biomarker, a single intervention and a single clinical outcome. Incremental study across patient groups, interventions, outcomes and modalities will lead to a more interdigitated network of knowledge, and correlations in metrics across levels of analysis will eventually give way to the causal understanding that will allow for mechanistically based diagnoses.

Abstract Background Fragile X syndrome (FXS) is the leading inherited cause of autism spectrum disorder, but there remains debate regarding the clinical presentation of social deficits in FXS. The aim of this study was to compare individuals with FXS to typically developing controls (TDC) and individuals with idiopathic autism spectrum disorder (ASD) across two social eye tracking paradigms. Methods Individuals with FXS and age- and gender-matched TDC and individuals with idiopathic ASD completed emotional face and social preference eye tracking tasks to evaluate gaze aversion and social interest, respectively. Participants completed a battery of cognitive testing and caregiver-reported measures for neurobehavioral characterization. Results Individuals with FXS exhibited reduced eye and increased mouth gaze to emotional faces compared to TDC. Gaze aversive findings were found to correlate with measures of anxiety, social communication deficits, and behavioral problems. In the social interest task, while individuals with idiopathic ASD showed significantly less social preference, individuals with FXS displayed social preference similar to TDC. Conclusions These findings suggest fragile X syndrome social deficits center on social anxiety without the prominent reduction in social interest associated with autism spectrum disorder. Specifically designed eye tracking techniques clarify the nature of social deficits in fragile X syndrome and may have applications to improve phenotyping and evaluate interventions targeting social functioning impairments.

Pharmacotherapy is the most common treatment for schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD). Pharmacogenetic studies have achieved results with limited clinical utility. DNA methylation (DNAm), an epigenetic modification, has been proposed to be involved in both the pathology and drug treatment of these disorders. Emerging data indicates that DNAm could be used as a predictor of drug response for psychiatric disorders. In this study, we performed a systematic review to evaluate the reproducibility of published changes of drug response-related DNAm in SCZ, BD and MDD. A total of 37 publications were included. Since the studies involved patients of different treatment stages, we partitioned them into three groups based on their primary focuses: (1) medication-induced DNAm changes (n = 8); (2) the relationship between DNAm and clinical improvement (n = 24); and (3) comparison of DNAm status across different medications (n = 14). We found that only BDNF was consistent with the DNAm changes detected in four independent studies for MDD. It was positively correlated with clinical improvement in MDD. To develop better predictive DNAm factors for drug response, we also discussed future research strategies, including experimental, analytical procedures and statistical criteria. Our review shows promising possibilities for using BDNF DNAm as a predictor of antidepressant treatment response for MDD, while more pharmacoepigenetic studies are needed for treatments of various diseases. Future research should take advantage of a system-wide analysis with a strict and standard analytical procedure.

Abstract Objective To identify the most prominent and replicable fractional anisotropy (FA) alterations of white matter associated with obsessive‐compulsive disorder (OCD) in tract‐based spatial statistics (TBSS) studies. Methods We reviewed previous TBSS studies (n = 20) in OCD and performed a meta‐analysis (n = 16) of FA differences. Results No between‐group differences in FA were detected in the pooled meta‐analysis. However, reduced FA was identified in the genu and anterior body of corpus callosum (CC) in adult OCD. FA reductions in the anterior body of CC were associated with a later age of onset in adult patients with OCD. For pediatric OCD, decreased FA in earlier adolescence and increased FA in later adolescence were seemingly related to an altered trajectory of brain maturation. Conclusions Absent in the pooled sample but robust in adults, disrupted microstructural organization in the anterior part of CC indicates a bias of deficits toward connections in interhemispheric connections of rostral neocortical regions, which could lead to deficits of interhemispheric communication and thus contribute to cognitive and emotional deficits in adult OCD. The correlation between FA in the anterior body of CC and older illness onset suggests that patients with later adult onset of illness may represent a biologically distinct subgroup. For pediatric OCD, alterations in neurodevelopmental maturation may contribute to inconsistent patterns of FA alteration relative to controls during adolescence. While most studies of OCD have emphasized alterations of within hemisphere fronto‐striatal circuits, these results indicate that between hemisphere connectivity of this circuitry may also represent important pathophysiology of the illness.

Previous studies have demonstrated relations between spontaneous neural activity evaluated by resting-state functional magnetic resonance imaging (fMRI) and symptom severity in post-traumatic stress disorder. However, few studies have used brain-based measures to identify imaging associations with illness severity at the level of individual patients. This study applied connectome-based predictive modeling (CPM), a recently developed data-driven and subject-level method, to identify brain function features that are related to symptom severity of trauma survivors. Resting-state fMRI scans and clinical ratings were obtained 10–15 months after the earthquake from 122 earthquake survivors. Symptom severity of post-traumatic stress disorder features for each survivor was evaluated using the Clinician Administered Post-traumatic Stress Disorder Scale (CAPS-IV). A functionally pre-defined atlas was applied to divide the human brain into 268 regions. Each individual’s functional connectivity 268 × 268 matrix was created to reflect correlations of functional time series data across each pair of nodes. The relationship between CAPS-IV scores and brain functional connectivity was explored in a CPM linear model. Using a leave-one-out cross-validation (LOOCV) procedure, findings showed that the positive network model predicted the left-out individual’s CAPS-IV scores from resting-state functional connectivity. CPM predicted CAPS-IV scores, as indicated by a significant correspondence between predicted and actual values (r = 0.30, P = 0.001) utilizing primarily functional connectivity between visual cortex, subcortical-cerebellum, limbic, and motor systems. The current study provides data-driven evidence regarding the functional brain features that predict symptom severity based on the organization of intrinsic brain networks and highlights its potential application in making clinical evaluation of symptom severity at the individual level.

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

The hippocampus plays a crucial role in the psychophysiology of schizophrenia. The past few years have seen a rapid growth in studies of hippocampal subfield anatomy using MRI-based volumetry, with exciting new findings particularly in studies of schizophrenia. As findings varied across studies, and given limitations to conducting a meta-analysis at this time based on the number of available studies and their variability in methods, we conducted a literature review to investigate whether volume alterations of hippocampal subfields in schizophrenia are shared across subfields or specific in terms of severity and location, and their relation to genetic and clinical features. Current studies show that severity and location of subfield volume changes are related to risk for schizophrenia, discrimination of psychiatric disorders, severity of psychotic symptoms and cognitive dysfunction, duration of illness, and treatment response. These diverse findings indicate that MRI-based hippocampal subfield volume measurements are a promising clinically-relevant biomarker for future schizophrenia research.

Background: Bipolar disorder (BD) is a mental disorder characterized by mood fluctuations between an acute episodic state of either mania or depression and a clinically remitted state. Dysfunction of large-scale intrinsic brain networks has been demonstrated in this disorder, but it remains unknown whether those network alterations are related to different states. Methods: In the present study, we performed a meta-analysis of whole-brain seed-based resting-state functional connectivity (rsFC) studies in BD patients to compare the intrinsic function of brain networks between episodic and remitted states. Thirty-nine seed-based voxel-wise rsFC datasets from thirty publications (1047 BD patients vs 1081 controls) were included in the meta-analysis. Seeds were categorized into networks by their locations within a priori functional networks. Seed-based d mapping analysis of between-state effects identified brain systems in which different states were associated with increased connectivity or decreased connectivity within and between each seed network. Findings: We found that BD patients presented decreased connectivity within the affective network (AN) in acute episodes but not in the remitted state of the illness. Similar decreased connectivity within the default-mode network (DMN) was also found in the acute state, but it was replaced by increased connectivity in the remitted state. In addition, different patterns of between-network dysconnectivity were observed between the acute and remitted states. Interpretation: This study is the first to identify different patterns of intrinsic function in large-scale brain networks between the acute and remitted states of BD through meta-analysis. The findings suggest that a shift in network function between the acute and remitted states may be related to distinct emotional and cognitive dysfunctions in BD, which may have important implications for identifying clinically relevant biomarkers to guide alternative treatment strategies for BD patients during active episodes or remission. Funding: This study was supported by grants from the National Natural Science Foundation of China (81171488, 81671669 and 81820108018) and by a Sichuan Provincial Youth Grant (2017JQ0001). Keywords: Bipolar disorder (BD), Resting-state functional connectivity (rsFC), Meta-analysis, Functional network, Mood states

Background: Auditory hallucinations are prevalent across the major psychotic disorders, but their underlying mechanism is poorly understood. Limited prior work supports a hypothesis of altered auditory/language brain systems. To more definitively assess this, we examined whether alterations in resting state connectivity of auditory and language cortices are associated with hallucination severity in a large sample of individuals in the schizo-bipolar spectrum. Methods: Whole brain resting state connectivity of auditory and language cortex (primary auditory cortex, unimodal auditory association cortex, Wernicke’s area [speech and heteromodal association cortex] and Broca’s area [speech production motor]) was evaluated for 243 subjects with schizophrenia, schizoaffective, or bipolar disorder with psychosis and 186 healthy controls from the Bipolar Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study. Regression analyses were conducted to evaluate whether resting state connectivity of auditory and language cortex was a significant predictor of current overall hallucination severity (information about specific modality of hallucinations experienced was not available). Results: Increased connectivity between lower and higher order regions of left temporal-parietal auditory/language processing cortex was associated with worse hallucination severity for all psychosis patients. Additionally, within bipolar subjects, increased interhemispheric connectivity between higher order temporal-parietal auditory/language regions was related to greater hallucination severity. When patients were categorized by B-SNIP biomarker-based Biotype groups, interhemispheric connectivity between left auditory association cortex and right core auditory cortex was related to greater hallucination severity for Biotype 1 patients. Exploratory analyses resulted in different patterns of connectivity of auditory/language cortex in patients and controls, unrelated to current hallucination severity. Conclusions: Although the findings cannot be precisely attributed to auditory hallucination severity or possible differences in such experiences between groups, increased connectivity among the left hemisphere auditory and receptive language cortex may represent a significant factor contributing to hallucination severity across psychotic disorders, and additional subgroup specific connectivity alterations may also be present.

The nature of hippocampal changes in schizophrenia before first treatment, and whether hippocampal subfields are affected by antipsychotic treatment are important questions for schizophrenia research. Forty-one first-episode antipsychotic-naïve acutely ill schizophrenia inpatients had MRI scans before and six weeks after antipsychotic treatment. Thirty-nine matched healthy controls were also scanned, twenty-two of which were scanned a second time six weeks later. Volumes of hippocampal subfields were measured via FreeSurfer v6.0 using a longitudinal analysis pipeline. Before treatment, schizophrenia patients had no significant changes in total hippocampal volume but exhibited significantly greater subfield volumes than controls in bilateral molecular layers of the hippocampus (ML), bilateral granular cell layers of the dentate gyrus (GC-DG), and bilateral cornu ammonis area 4 (CA4). After six weeks of antipsychotic treatment, patients showed volume reductions compared with pretreatment scans in total hippocampus bilaterally, with subfield volume reduction noted in previously enlarged subfields (i.e., bilateral ML, GC-DG and CA4) and in bilateral hippocampal tails, left CA1, CA3, and fimbria. Subfields with volume increases before treatment were reduced to the level of healthy controls (bilateral ML and GC-DG) or near to it (bilateral CA4) after treatment. These results indicate subfield-specific hippocampal hypertrophy prior to treatment, and that these abnormalities were reduced after acute antipsychotic therapy in a dose-related manner together with volume reductions in other areas that were not hypertrophic before treatment. Keywords: Antipsychotic-naïve schizophrenia, Hippocampal subfields, Antipsychotics, Psychoradiology

Purpose: Auditory hallucinations (AH), typically hearing voices, are a core symptom in schizophrenia. They may result from deficits in dynamic functional connectivity (FC) between cortical regions supporting speech production and language perception that interfere with the ability to recognize self-generated speech as not coming from external sources. We tested this hypothesis by investigating dynamic connectivity between the frontal cortex region related to language production and the temporal cortex region related to auditory processing. Methods: Resting-state fMRI scans were acquired from 18 schizophrenia patients with AH (AH+), 17 schizophrenia patients without AH (AH-) and 22 healthy controls. A multiband sequence with TR = 427 ms was adopted to provide relatively high temporal resolution data for characterizing dynamic FC. Analysis focused on connectivity between speech production and language comprehension areas, eloquent language cortex in the left hemisphere. Two frequency bands of brain oscillatory activity were evaluated (0.01–0.027 Hz, 0.027–0.08 Hz) in which differential alterations that have been previously linked to schizophrenia. Conventional static FC maps of these seeds were also calculated. Results: Dynamic connectivity analysis indicated that AH+ patients showed not only less temporal variability but transient lower strength in connectivity between speech and auditory areas than healthy controls, while AH- patients not. These findings were restricted to 0.027–0.08 Hz activity. In static connectivity analysis, no significant differences were observed in connectivity between speech production and language comprehension areas in either frequency band. Conclusions: Reduced temporal variability and connectivity strength between key regions of eloquent language cortex may represent a mechanism for AH in schizophrenia. Keywords: Schizophrenia, Auditory hallucinations, Dynamic, Functional connectivity, Language areas, Multiband

Introduction: Disrupted topological organization of brain functional networks has been widely observed in posttraumatic stress disorder (PTSD). However, the topological organization of the brain grey matter (GM) network has not yet been investigated in pediatric PTSD who was more vulnerable to develop PTSD when exposed to stress. Materials and methods: Twenty two pediatric PTSD patients and 22 matched trauma-exposed controls who survived a massive earthquake (8.0 magnitude on Richter scale) in Sichuan Province of western China in 2008 underwent structural brain imaging with MRI 8–15 months after the earthquake. Brain networks were constructed based on the morphological similarity of GM across regions, and analyzed using graph theory approaches. Nonparametric permutation testing was performed to assess group differences in each topological metric. Results: Compared with controls, brain networks of PTSD patients were characterized by decreased characteristic path length (P = 0.0060) and increased clustering coefficient (P = 0.0227), global efficiency (P = 0.0085) and local efficiency (P = 0.0024). Locally, patients with PTSD exhibited increased centrality in nodes of the default-mode (DMN), central executive (CEN) and salience networks (SN), involving medial prefrontal (mPFC), parietal, anterior cingulate (ACC), occipital and olfactory cortex and hippocampus. Conclusions: Our analyses of topological brain networks in children with PTSD indicate a significantly more segregated and integrated organization. The associations and disassociations between these grey matter findings and white matter (WM) and functional changes previously reported in this sample may be important for diagnostic purposes and understanding the brain maturational effects of pediatric PTSD. Keywords: Pediatric PTSD, Topological organization, Graph theory, Brain network, MRI, Psychoradiology

Previous studies using resting-state functional MRI (rs-fMRI) have revealed alterations in graphical metrics in groups of individuals with posttraumatic stress disorder (PTSD). To explore the ability of graph measures to diagnose PTSD and capture its essential features in individual patients, we used a deep learning (DL) model based on a graph-theoretic approach to discriminate PTSD from trauma-exposed non-PTSD at the individual level and to identify its most discriminant features. Our study was performed on rs-fMRI data from 91 individuals with PTSD and 126 trauma-exposed non-PTSD patients. To evaluate our DL method, we used the traditional support vector machine (SVM) classifier as a reference. Our results showed that the proposed DL model allowed single-subject discrimination of PTSD and trauma-exposed non-PTSD individuals with higher accuracy (average: 80%) than the traditional SVM (average: 57.7%). The top 10 DL features were identified within the default mode, central executive, and salience networks; the first two of these networks were also identified in the SVM classification. We also found that nodal efficiency in the left fusiform gyrus was negatively correlated with the Clinician Administered PTSD Scale score. These findings demonstrate that DL based on graphical features is a promising method for assisting in the diagnosis of PTSD.

Abstract Our understanding of fragile X syndrome (FXS) pathophysiology continues to improve and numerous potential drug targets have been identified. Yet, current prescribing practices are only symptom-based in order to manage difficult behaviors, as no drug to date is approved for the treatment of FXS. Drugs impacting a diversity of targets in the brain have been studied in recent FXS-specific clinical trials. While many drugs have focused on regulation of enhanced glutamatergic or deficient GABAergic neurotransmission, compounds studied have not been limited to these mechanisms. As a single-gene disorder, it was thought that FXS would have consistent drug targets that could be modulated with pharmacotherapy and lead to significant improvement. Unfortunately, despite promising results in FXS animal models, translational drug treatment development in FXS has largely failed. Future success in this field will depend on learning from past challenges to improve clinical trial design, choose appropriate outcome measures and age range choices, and find readily modulated drug targets. Even with many negative placebo-controlled study results, the field continues to move forward exploring both the new mechanistic drug approaches combined with ways to improve trial execution. This review summarizes the known phenotype and pathophysiology of FXS and past clinical trial rationale and results, and discusses current challenges facing the field and lessons from which to learn for future treatment development efforts.

Abstract Background Studies in the fmr1 KO mouse demonstrate hyper-excitability and increased high-frequency neuronal activity in sensory cortex. These abnormalities may contribute to prominent and distressing sensory hypersensitivities in patients with fragile X syndrome (FXS). The current study investigated functional properties of auditory cortex using a sensory entrainment task in FXS. Methods EEG recordings were obtained from 17 adolescents and adults with FXS and 17 age- and sex-matched healthy controls. Participants heard an auditory chirp stimulus generated using a 1000-Hz tone that was amplitude modulated by a sinusoid linearly increasing in frequency from 0–100 Hz over 2 s. Results Single trial time-frequency analyses revealed decreased gamma band phase-locking to the chirp stimulus in FXS, which was strongly coupled with broadband increases in gamma power. Abnormalities in gamma phase-locking and power were also associated with theta-gamma amplitude-amplitude coupling during the pre-stimulus period and with parent reports of heightened sensory sensitivities and social communication deficits. Conclusions This represents the first demonstration of neural entrainment alterations in FXS patients and suggests that fast-spiking interneurons regulating synchronous high-frequency neural activity have reduced functionality. This reduced ability to synchronize high-frequency neural activity was related to the total power of background gamma band activity. These observations extend findings from fmr1 KO models of FXS, characterize a core pathophysiological aspect of FXS, and may provide a translational biomarker strategy for evaluating promising therapeutics.

Sensory hypersensitivities are common and distressing features of Fragile X Syndrome (FXS). While there are many drug interventions that reduce behavioral deficits in Fmr1 mice and efforts to translate these preclinical breakthroughs into clinical trials for FXS, evidence-based clinical interventions are almost non-existent potentially due to lack of valid neural biomarkers. Local circuit function in sensory networks is dependent on the dynamic balance of activity in inhibitory/excitatory synapses. Studies are needed to examine the association of electrophysiological alterations in neural systems with sensory and other clinical features of FXS to establish their clinical relevance. Adolescents and adults with FXS (n = 38, Mean age = 25.5, std = 10.1; 13 females) and age matched typically developing controls (n = 40, Mean age = 27.7, std = 12.1; 17 females) completed auditory chirp and auditory habituation tasks while undergoing dense array electroencephalography (EEG). Amplitude, latency, and percent change (habituation) in N1 and P2 event-related potential (ERP) components were characterized for the habituation task; time-frequency calculations using Morlet wavelets characterized phase-locking and single trial power for the habituation and chirp tasks. FXS patients showed increased amplitude but some evidence for reduced habituation of the N1 ERP, and reduced phase-locking in the low and high gamma frequency range and increased low gamma power to the chirp stimulus. FXS showed increased theta power in both tasks. While the habituation finding was weaker than previously found, the remaining findings replicate our previous work in a new sample of patients with FXS. Females showed less deficit in the chirp task but not the habituation task. Abnormal increases in gamma power were related to more severe behavioral and psychiatric features as well as reductions in neurocognitive abilities. Replicating electrophysiological deficits in a new group of patients using different EEG equipment at a new data collection site with differing levels of environmental noise that were robust to data processing techniques utilizing multiple researchers, indicates a potential for scalability to multi-site clinical trials. Given the robust replicability, relevance to clinical measures, and preclinical evidence for sensitivity of these EEG measures to pharmacological intervention, the observed abnormalities may provide novel translational markers of target engagement and potentially outcome measures in large-scale studies evaluating new treatments targeting neural hyperexcitability in FXS.

A vivid sense of motion can be inferred from static pictures of objects in motion. Like perception of real motion (RM), viewing photographs with implied motion (IM) can also activate the motion-sensitive visual cortex, including the middle temporal complex (hMT+) of the human extrastriate cortex. Moreover, extrastriate cortical activity also increases with motion coherence. Based on these previous findings, this study examined whether similar coherence level-dependent activity in motion-sensitive human extrastriate cortex is seen with IM stimuli of varying coherence. Photographic stimuli showing a human moving in four directions (left, right, toward, or away from the viewer) were presented to 15 participants. The coherence of the stimuli was manipulated by changing the percentage of pictures implying movement in one direction. Electroencephalographic data were collected while participants viewed IM or counterpart non-IM stimuli. The P2 response of extrastriate visual cortex (source located at hMT+) increased bilaterally with coherence level in the IM conditions but not in the non-IM conditions. This finding demonstrates that extrastriate visual cortical responses are progressively activated as motion coherence increases, even when motion is inferred, providing new support for the view that the activity of human motion-sensitive extrastriate visual cortex can be modulated by top-down perceptual influences in addition to its well-established role in processing bottom-up sensory signals.