Replication of a neuroimaging biomarker for striatal dysfunction in psychosis.

To bring biomarkers closer to clinical application, they should be generalizable, reliable, and maintain performance within the constraints of routine clinical conditions. The functional striatal abnormalities (FSA), is among the most advanced neuroimaging biomarkers in schizophrenia, trained to discriminate diagnosis, with post-hoc analyses indicating prognostic properties. Here, we attempt to replicate its diagnostic capabilities measured by the area under the curve (AUC) in receiver operator characteristic curves discriminating individuals with psychosis (n = 101) from healthy controls (n = 51) in the Human Connectome Project for Early Psychosis. We also measured the test-retest (run 1 vs 2) and phase encoding direction (i.e., AP vs PA) reliability with intraclass correlation coefficients (ICC). Additionally, we measured effects of scan length on classification accuracy (i.e., AUCs) and reliability (i.e., ICCs). Finally, we tested the prognostic capability of the FSA by the correlation between baseline scores and symptom improvement over 12 weeks of antipsychotic treatment in a separate cohort (n = 97). Similar analyses were conducted for the Yeo networks intrinsic connectivity as a reference. The FSA had good/excellent diagnostic discrimination (AUC = 75.4%, 95% CI = 67.0-83.3%; in non-affective psychosis AUC = 80.5%, 95% CI = 72.1-88.0%, and in affective psychosis AUC = 58.7%, 95% CI = 44.2-72.0%). Test-retest reliability ranged between ICC = 0.48 (95% CI = 0.35-0.59) and ICC = 0.22 (95% CI = 0.06-0.36), which was comparable to that of networks intrinsic connectivity. Phase encoding direction reliability for the FSA was ICC = 0.51 (95% CI = 0.42-0.59), generally lower than for networks intrinsic connectivity. By increasing scan length from 2 to 10 min, diagnostic classification of the FSA increased from AUC = 71.7% (95% CI = 63.1-80.3%) to 75.4% (95% CI = 67.0-83.3%) and phase encoding direction reliability from ICC = 0.29 (95% CI = 0.14-0.43) to ICC = 0.51 (95% CI = 0.42-0.59). FSA scores did not correlate with symptom improvement. These results reassure that the FSA is a generalizable diagnostic - but not prognostic - biomarker. Given the replicable results of the FSA as a diagnostic biomarker trained on case-control datasets, next the development of prognostic biomarkers should be on treatment-response data.

Replication of a neuroimaging biomarker for striatal dysfunction in psychosis.

To bring biomarkers closer to clinical application, they should be generalizable, reliable, and maintain performance within the constraints of routine clinical conditions. The functional striatal abnormalities (FSA), is among the most advanced neuroimaging biomarkers in schizophrenia, trained to discriminate diagnosis, with post-hoc analyses indicating prognostic properties. Here, we attempt to replicate its diagnostic capabilities measured by the area under the curve (AUC) in receiver operator characteristic curves discriminating individuals with psychosis (n=101) from healthy controls (n=51) in the Human Connectome Project for Early Psychosis. We also measured the test-retest (run 1 vs 2) and phase encoding direction (i.e., AP vs PA) reliability with intraclass correlation coefficients (ICC). Additionally, we measured effects of scan length on classification accuracy (i.e., AUCs) and reliability (i.e., ICCs). Finally, we tested the prognostic capability of the FSA by the correlation between baseline scores and symptom improvement over 12 weeks of antipsychotic treatment in a separate cohort (n=97). Similar analyses were conducted for the Yeo networks intrinsic connectivity as a reference. The FSA had good/excellent diagnostic discrimination (AUC=75.4%, 95%CI=67.0%-83.3%; in non-affective psychosis AUC=80.5%, 95%CI=72.1-88.0%, and in affective psychosis AUC=58.7%, 95%CI=44.2-72.0%). Test-retest reliability ranged between ICC=0.48 (95%CI=0.35-0.59) and ICC=0.22 (95%CI=0.06-0.36), which was comparable to that of networks intrinsic connectivity. Phase encoding direction reliability for the FSA was ICC=0.51 (95%CI=0.42-0.59), generally lower than for networks intrinsic connectivity. By increasing scan length from 2 to 10 minutes, diagnostic classification of the FSA increased from AUC=71.7% (95%CI=63.1%-80.3%) to 75.4% (95%CI=67.0%-83.3%) and phase encoding direction reliability from ICC=0.29 (95%CI=0.14-0.43) to ICC=0.51 (95%CI=0.42-0.59). FSA scores did not correlate with symptom improvement. These results reassure that the FSA is a generalizable diagnostic - but not prognostic - biomarker. Given the replicable results of the FSA as a diagnostic biomarker trained on case-control datasets, next the development of prognostic biomarkers should be on treatment-response data.

A Functional Connectome-Based Neural Signature for Individualized Prediction of Antipsychotic Response in First-Episode Psychosis.

OBJECTIVE: Identification of robust biomarkers that predict individualized response to antipsychotic treatment at the early stage of psychotic disorders remains a challenge in precision psychiatry. The aim of this study was to investigate whether any functional connectome-based neural traits could serve as such a biomarker. METHODS: In a discovery sample, 49 patients with first-episode psychosis received multi-paradigm fMRI scans at baseline and were clinically followed up for 12 weeks under antipsychotic monotherapies. Treatment response was evaluated at the individual level based on the psychosis score of the Brief Psychiatric Rating Scale. Cross-paradigm connectivity and connectome-based predictive modeling were employed to train a predictive model that uses baseline connectomic measures to predict individualized change rates of psychosis scores, with model performance evaluated as the Pearson correlations between the predicted change rates and the observed change rates, based on cross-validation. The model generalizability was further examined in an independent validation sample of 24 patients in a similar design. RESULTS: The results revealed a paradigm-independent connectomic trait that significantly predicted individualized treatment outcome in both the discovery sample (predicted-versus-observed r=0.41) and the validation sample (predicted-versus-observed r=0.47, mean squared error=0.019). Features that positively predicted psychosis change rates primarily involved connections related to the cerebellar-cortical circuitry, and features that negatively predicted psychosis change rates were chiefly connections within the cortical cognitive systems. CONCLUSIONS: This study discovers and validates a connectome-based functional signature as a promising early predictor for individualized response to antipsychotic treatment in first-episode psychosis, thus highlighting the potential clinical value of this biomarker in precision psychiatry.

Replication of a neuroimaging biomarker for striatal dysfunction in psychosis.

To bring biomarkers closer to clinical application, they should be generalizable, reliable, and maintain performance within the constraints of routine clinical conditions. The functional striatal abnormalities (FSA), is among the most advanced neuroimaging biomarkers in schizophrenia, trained to discriminate diagnosis, with post-hoc analyses indicating prognostic properties. Here, we attempt to replicate its diagnostic capabilities measured by the area under the curve (AUC) in receiver operator characteristic curves discriminating individuals with psychosis (n=101) from healthy controls (n=51) in the Human Connectome Project for Early Psychosis. We also measured the test-retest (run 1 vs 2) and phase encoding direction (i.e., AP vs PA) reliability with intraclass correlation coefficients (ICC). Additionally, we measured effects of scan length on classification accuracy (i.e., AUCs) and reliability (i.e., ICCs). Finally, we tested the prognostic capability of the FSA by the correlation between baseline scores and symptom improvement over 12 weeks of antipsychotic treatment in a separate cohort (n=97). Similar analyses were conducted for the Yeo networks intrinsic connectivity as a reference. The FSA had good/excellent diagnostic discrimination (AUC=75.4%, 95%CI=67.0%-83.3%; in non-affective psychosis AUC=80.5%, 95%CI=72.1-88.0%, and in affective psychosis AUC=58.7%, 95%CI=44.2-72.0%). Test-retest reliability ranged between ICC=0.48 (95%CI=0.35-0.59) and ICC=0.22 (95%CI=0.06-0.36), which was comparable to that of networks intrinsic connectivity. Phase encoding direction reliability for the FSA was ICC=0.51 (95%CI=0.42-0.59), generally lower than for networks intrinsic connectivity. By increasing scan length from 2 to 10 minutes, diagnostic classification of the FSA increased from AUC=71.7% (95%CI=63.1%-80.3%) to 75.4% (95%CI=67.0%-83.3%) and phase encoding direction reliability from ICC=0.29 (95%CI=0.14-0.43) to ICC=0.51 (95%CI=0.42-0.59). FSA scores did not correlate with symptom improvement. These results reassure that the FSA is a generalizable diagnostic - but not prognostic - biomarker. Given the replicable results of the FSA as a diagnostic biomarker trained on case-control datasets, next the development of prognostic biomarkers should be on treatment-response data.

Effects of phase encoding direction on test-retest reliability of human functional connectome.

The majority of human connectome studies in the literature based on functional magnetic resonance imaging (fMRI) data use either an anterior-to-posterior (AP) or a posterior-to-anterior (PA) phase encoding direction (PED). However, whether and how PED would affect test-retest reliability of functional connectome is unclear. Here, in a sample of healthy subjects with two sessions of fMRI scans separated by 12 weeks (two runs per session, one with AP, the other with PA), we tested the influence of PED on global, nodal, and edge connectivity in the constructed brain networks. All data underwent the state-of-the-art Human Connectome Project (HCP) pipeline to correct for phase-encoding-related distortions before entering analysis. We found that at the global level, the PA scans showed significantly higher intraclass correlation coefficients (ICCs) for global connectivity compared with AP scans, which was particularly prominent when using the Seitzman-300 atlas (versus the CAB-NP-718 atlas). At the nodal level, regions most strongly affected by PED were consistently mapped to the cingulate cortex, temporal lobe, sensorimotor areas, and visual areas, with significantly higher ICCs during PA scans compared with AP scans, regardless of atlas. Better ICCs were also observed during PA scans at the edge level, in particular when global signal regression (GSR) was not performed. Further, we demonstrated that the observed reliability differences between PEDs may relate to a similar effect on the reliability of temporal signal-to-noise ratio (tSNR) in the same regions (that PA scans were associated with higher reliability of tSNR than AP scans). Averaging the connectivity outcome from the AP and PA scans could increase median ICCs, especially at the nodal and edge levels. Similar results at the global and nodal levels were replicated in an independent, public dataset from the HCP-Early Psychosis (HCP-EP) study with a similar design but a much shorter scan session interval. Our findings suggest that PED has significant effects on the reliability of connectomic estimates in fMRI studies. We urge that these effects need to be carefully considered in future neuroimaging designs, especially in longitudinal studies such as those related to neurodevelopment or clinical intervention.

Right atrial structural remodeling predict worse outcomes in transcatheter mitral valve repair.

BACKGROUND: In the current study, we assess the predictive role of right and left atrial volume indices (RAVI and LAVI) as well as the ratio of RAVI/LAVI (RLR) on mortality following transcatheter mitral valve repair (TMVr). METHODS: Transthoracic echocardiograms of 158 patients who underwent TMVr at a single academic medical center from 2011 to 2018 were reviewed retrospectively. RAVI and LAVI were calculated using Simpson's method. Patients were stratified based on etiology of mitral regurgitation (MR). Cox proportional-hazard regression was created utilizing MR type, STS-score, and RLR to assess the independent association of RLR with survival. Kaplan-Meier analysis was used to analyze the association between RAVI and LAVI with all-cause mortality. Hemodynamic values from preprocedural right heart catheterization were also compared between RLR groups. RESULTS: Among 123 patients included (median age 81.3 years; 52.5% female) there were 50 deaths during median follow-up of 3.0 years. Patients with a high RAVI and low LAVI had significantly higher all-cause mortality while patients with high LAVI and low RAVI had significantly improved all-cause mortality compared to other groups (p = 0.0032). RLR was significantly associated with mortality in patients with both functional and degenerative MR (p = 0.0038). Finally, Cox proportion-hazard modeling demonstrated that an elevated RLR above the median value was an independent predictor of all-cause mortality [HR = 2.304; 95% CI = 1.26-4.21, p = 0.006] when MR type and STS score were accounted for. CONCLUSION: Patients with a high RAVI and low LAVI had significantly increased mortality than other groups following TMVr suggesting RA remodeling may predict worse outcomes following the procedure. Concordantly, RLR was predictive of mortality independent of MR type and preprocedural STS-score. These indices may provide additional risk stratification in patients undergoing evaluation for TMVr.

Contributions of Parasympathetic Arousal-Related Activity to Cognitive Performance in Patients With First-Episode Psychosis and Control Subjects.

BACKGROUND: Cognitive impairment is integral to the pathophysiology of psychosis. Recent findings implicate autonomic arousal-related activity in both momentary fluctuations and individual differences in cognitive performance. Although altered autonomic arousal is common in patients with first-episode psychosis (FEP), its contribution to cognitive performance is unknown. METHODS: A total of 24 patients with FEP (46% male, age = 24.31 [SD 4.27] years) and 24 control subjects (42% male, age = 27.06 [3.44] years) performed the Multi-Source Interference Task in-scanner with simultaneous pulse oximetry. First-level models included the cardiac-blood oxygen level-dependent regressor, in addition to task (congruent, interference, and error) and nuisance (motion and CompCor physiology) regressors. The cardiac-blood oxygen level-dependent regressor reflected parasympathetic arousal-related activity and was created by convolving the interbeat interval at each heartbeat with the hemodynamic response function. Group models examined the effect of group or cognitive performance (reaction times × error rate) on arousal-related and task activity, while controlling for sex, age, and framewise displacement. RESULTS: Parasympathetic arousal-related activity was robust in both groups but localized to different regions for patients with FEP and healthy control subjects. Within both groups, arousal-related activity was significantly associated with cognitive performance across occipital and temporal cortical regions. Greater arousal-related activity in the bilateral prefrontal cortex (Brodmann area 9) was related to better performance in healthy control subjects but not patients with FEP. CONCLUSIONS: Autonomic arousal circuits contribute to cognitive performance and the pathophysiology of FEP. Arousal-related functional activity is a novel indicator of cognitive ability and should be incorporated into neurobiological models of cognition in psychosis.

Frontal lobe fALFF measured from resting-state fMRI as a prognostic biomarker in first-episode psychosis.

Clinical response to antipsychotic drug treatment is highly variable, yet prognostic biomarkers are lacking. The goal of the present study was to test whether the fractional amplitude of low-frequency fluctuations (fALFF), as measured from baseline resting-state fMRI data, can serve as a potential biomarker of treatment response to antipsychotics. Patients in the first episode of psychosis (n = 126) were enrolled in two prospective studies employing second-generation antipsychotics (risperidone or aripiprazole). Patients were scanned at the initiation of treatment on a 3T MRI scanner (Study 1, GE Signa HDx, n = 74; Study 2, Siemens Prisma, n = 52). Voxelwise fALFF derived from baseline resting-state fMRI scans served as the primary measure of interest, providing a hypothesis-free (as opposed to region-of-interest) search for regions of the brain that might be predictive of response. At baseline, patients who would later meet strict criteria for clinical response (defined as two consecutive ratings of much or very much improved on the CGI, as well as a rating of ≤3 on psychosis-related items of the BPRS-A) demonstrated significantly greater baseline fALFF in bilateral orbitofrontal cortex compared to non-responders. Thus, spontaneous activity in orbitofrontal cortex may serve as a prognostic biomarker of antipsychotic treatment.

Relationship of ejection fraction and natriuretic peptide trajectories in heart failure with baseline reduced and mid-range ejection fraction.

BACKGROUND: The prognostic importance of trajectories of neurohormones relative to left ventricular function over time in heart failure with reduced and mid-range EF (HFrEF and HFmrEF) is poorly defined. OBJECTIVE: To evaluate left ventricular ejection fraction (LVEF) and B-type natriuretic peptide (BNP) trajectories in HFrEF and HFmrEF. METHODS: Analyses of LVEF and BNP trajectories after incident HF admissions presenting with abnormal LV systolic function were performed using 3 methods: a Cox proportional hazards model with time-varying covariates, a dual longitudinal-survival model with shared random effects, and an unsupervised analysis to capture 3 discrete trajectories for each parameter. RESULTS: Among 1,158 patients (68.9 ± 13.0 years, 53.3% female), both time-varying LVEF measurements (P=.001) and log-transformed BNP measurements (p-values=2 × 10-16) were independently associated with survival during 6 years after covariate adjustment. In the dual longitudinal/survival model, both LVEF and BNP trajectories again were independently associated with survival (P<.0001 in each model); however, LVEF was more dynamic than BNP (P <.0001 for time covariate in LVEF longitudinal model versus P=.88 for the time covariate in BNP longitudinal model). In the unsupervised analysis, 3 discrete LVEF trajectories (dividing the cohort into approximately thirds) and 3 discrete BNP trajectories were identified. Discrete LVEF and BNP trajectories had independent prognostic value in Kaplan-Meier analyses (P<.0001), and substantial membership variability across BNP and LVEF trajectories was noted. CONCLUSION: Although LVEF trajectories have greater temporal variation, BNP trajectories provide additive prognostication and an even stronger association with survival times in heart failure patients with abnormal LV systolic function.

Striatal functional connectivity in psychosis relapse: A hypothesis generating study.

Most individuals with psychotic disorders relapse over their course of illness, yet the neural processes that may lead to symptom worsening are poorly understood. Importantly, such processes could be potentially affected by antipsychotic adherence status upon relapse (i.e., relapse despite ongoing antipsychotic maintenance vs following antipsychotic discontinuation), reflecting distinct mechanisms. As a first foray into this question, we aim to compare the striatal connectivity index (SCI), a biomarker derived from striatal resting state functional connectivity predictive of treatment response, by adherence status upon relapse. In order to confirm adherence status upon relapse, we compared individuals treated with long-acting injectable antipsychotics upon relapse (i.e., breakthrough psychosis) (n = 23), with individuals who had decided to interrupt antipsychotic treatment and then relapsed (n = 27), as well as healthy controls (n = 26). We acquired for each individual >10 min of resting state fMRI, to generate functional connectivity maps. Region of interest (ROI) analyses were conducted to calculate SCI values for each participant. These values were entered as dependent variable in a linear regression adjusted for sex and age for which adherence status was the independent variable. Individuals in the breakthrough psychosis group had significantly lower SCI values than healthy controls (Cohen's d = 0.99, p < 0.001), and non-adherent individuals upon relapse (Cohen's d = 0.58, p = 0.032), whereas non-adherent individuals had also trend level lower SCI values than healthy controls (Cohen's d = 0.44, p = 0.09). These results suggest the hypothesis that striatal functional connectivity may be aberrant in psychosis relapse, and that this dysfunction may be greater among individuals who developed relapse despite ongoing antipsychotic treatment.

Heritability of Functional Connectivity in Resting State: Assessment of the Dynamic Mean, Dynamic Variance, and Static Connectivity across Networks.

Recent efforts to evaluate the heritability of the brain's functional connectome have predominantly focused on static connectivity. However, evaluating connectivity changes across time can provide valuable insight about the inherent dynamic nature of brain function. Here, the heritability of Human Connectome Project resting-state fMRI data was examined to determine whether there is a genetic basis for dynamic fluctuations in functional connectivity. The dynamic connectivity variance, in addition to the dynamic mean and standard static connectivity, was evaluated. Heritability was estimated using Accelerated Permutation Inference for the ACE (APACE), which models the additive genetic (h2), common environmental (c2), and unique environmental (e2) variance. Heritability was moderate (mean h2: dynamic mean = 0.35, dynamic variance = 0.45, and static = 0.37) and tended to be greater for dynamic variance compared to either dynamic mean or static connectivity. Further, heritability of dynamic variance was reliable across both sessions for several network connections, particularly between higher-order cognitive and visual networks. For both dynamic mean and static connectivity, similar patterns of heritability were found across networks. The findings support the notion that dynamic connectivity is genetically influenced. The flexibility of network connections, not just their strength, is a heritable endophenotype that may predispose trait behavior.

Development of lateral pulvinar resting state functional connectivity and its role in attention.

OBJECTIVE: The lateral pulvinar nucleus (LPN) has a well-established role in visual attention. Oscillatory activity of the LPN is critical for cortico-cortical communication within and among occipital and temporal visual processing regions. However, the functional development of the LPN and its role in attention deficits is not understood. This study examined the development of thalamic functional connectivity and its relation to attention abilities. METHOD: Resting state functional Magnetic Resonance Imaging images from 950 participants (ages 8-21) in the Philadelphia Neurodevelopmental Cohort (PNC) were used to examine age effects. Follow-up General Linear Models were performed to examine brain-behavior effects with Attention Deficit Hyperactivity Disorder (ADHD) symptom ratings and D-prime scores from the Penn Continuous Performance Task, a behavioral measure of selective attention. RESULTS: LPN functional connectivity with ventral visual stream regions of the occipital and temporal cortices decreased with age, while LPN functional connectivity with the supplementary motor area increased with age. Weaker LPN connectivity in the inferior parietal lobule, supramarginal gyrus, posterior insula, and inferior frontal gyrus was associated with more ADHD symptoms; stronger pulvinar-cerebellar connectivity was also associated with more ADHD symptoms. Better D-prime scores were associated with greater connectivity between the pulvinar and superior parietal gyrus; better D-prime scores were associated with weaker pulvinar connectivity with striatal, middle temporal gyrus, and medial prefrontal cortex regions. CONCLUSION: These findings implicate the LPN in the development of the ventral visual processing stream between late childhood and early adulthood and suggest that LPN connectivity with higher order attention networks is important for attention abilities.

Overlapping Neurobiological Substrates for Early-Life Stress and Resilience to Psychosis.

Early-life stress, such as childhood maltreatment, is a well-known etiological factor in psychopathology, including psychosis. Exposure to early-life stress disrupts the neurodevelopment of widespread brain systems, including key components of the hypothalamic-pituitary-adrenal axis stress response, such as the amygdala, hippocampus, and medial prefrontal cortex, as well as key components of the brain's reward system, such as the nucleus accumbens and orbitofrontal cortex. These disruptions have a considerable impact on the function of emotion and reward circuitry, which play a central role in the emergence and severity of psychosis. While this overlap may provide insight into the pathophysiology of psychosis, it also provides unique opportunities to elucidate neurobiological substrates that may promote resilience to psychosis. In this review, we discuss the hypothalamic-pituitary-adrenal axis stress response, discuss the disruption in the neurodevelopment of emotion and reward processing associated with early stress exposures, and examine how this circuitry may contribute to resilience to psychotic disorders.

Parasympathetic arousal-related cortical activity is associated with attention during cognitive task performance.

Parasympathetic arousal is associated with states of heightened attention and well-being. Arousal may affect widespread cortical and subcortical systems across the brain, however, little is known about its influence on cognitive task processing and performance. In the current study, healthy adult participants (n â€‹= â€‹20) underwent multi-band echo-planar imaging (TR â€‹= â€‹0.72 â€‹s) with simultaneous pulse oximetry recordings during performance of the Multi Source Interference Task (MSIT), the Oddball Task (OBT), and during rest. Processing speed on both tasks was robustly related to heart rate (HR). Participants with slower HR responded faster on both the MSIT (33% variance explained) and the OBT (25% variance explained). Within all participants, trial-to-trial fluctuations in processing speed were robustly related to the heartbeat-stimulus interval, a metric that is dependent both on the concurrent HR and the stimulus timing with respect to the heartbeat. Models examining the cardiac-BOLD response revealed that a distributed set of regions showed arousal-related activity that was distinct for different task conditions. Across these cortical regions, activity increased with slower HR. Arousal-related activity was distinct from task-evoked activity and it was robust to the inclusion of additional physiological nuisance regressors into the models. For the MSIT, such arousal-related activity occurred across visual and dorsal attention network regions. For the OBT, this activity occurred within fronto-parietal regions. For rest, arousal-related activity also occurred, but was confined to visual regions. The pulvinar nucleus of the thalamus showed arousal-related activity during all three task conditions. Widespread cortical activity, associated with increased parasympathetic arousal, may be propagated by thalamic circuits and contributes to improved attention. This activity is distinct from task-evoked activity, but affects cognitive performance and therefore should be incorporated into neurobiological models of cognition and clinical disorders.

Striatal volume and functional connectivity correlate with weight gain in early-phase psychosis.

Second-generation antipsychotic drugs (SGAs) are essential in the treatment of psychotic disorders, but are well-known for inducing substantial weight gain and obesity. Critically, weight gain may reduce life expectancy for up to 20-30 years in patients with psychotic disorders, and prognostic biomarkers are generally lacking. Even though other receptors are also implicated, the dorsal striatum, rich in dopamine D2 receptors, which are antagonized by antipsychotic medications, plays a key role in the human reward system and in appetite regulation, suggesting that altered dopamine activity in the striatal reward circuitry may be responsible for increased food craving and weight gain. Here, we measured striatal volume and striatal resting-state functional connectivity at baseline, and weight gain over the course of 12 weeks of antipsychotic treatment in 81 patients with early-phase psychosis. We also included a sample of 58 healthy controls. Weight measurements were completed at baseline, and then weekly for 4 weeks, and every 2 weeks until week 12. We used linear mixed models to compute individual weight gain trajectories. Striatal volume and whole-brain striatal connectivity were then calculated for each subject, and used to assess the relationship between striatal structure and function and individual weight gain in multiple regression models. Patients had similar baseline weights and body mass indices (BMI) compared with healthy controls. There was no evidence that prior drug exposure or duration of untreated psychosis correlated with baseline BMI. Higher left putamen volume and lower sensory motor connectivity correlated with the magnitude of weight gain in patients, and these effects multiplied when the structure-function interaction was considered in an additional exploratory analysis. In conclusion, these results provide evidence for a correlation of striatal structure and function with antipsychotic-induced weight gain. Lower striatal connectivity was associated with more weight gain, and this relationship was stronger for higher compared with lower left putamen volumes.

Deconstructing Avolition: Initiation vs persistence of reward-directed effort.

Avolition, a decrease in the initiation and persistence of goal-directed behavior, is a critical determinant of disability in patients with schizophrenia. Recent studies have demonstrated that avolition can be modeled using reward-based, behavioral paradigms. These studies suggest that avolition represents a motivational deficit, accounted for by a diminished ability to anticipate pleasurable experiences. Notably, although data suggest that "initiation" and "persistence" of goal-directed behavior may depend on different processes, few studies have sought to distinguish between these two components of avolitional symptoms. Such distinctions could have real consequences for the development and evaluation of interventions designed to ameliorate avolitional symptoms. Thus, the present study examined the relationship between anticipatory pleasure, a key driver of avolition, and both the initiation and persistence of reward-directed, effortful responding during the Effort Expenditures for Rewards Task in 103 healthy participants. We found that anticipatory pleasure was not significantly predictive of the initiation of effortful responding but was significantly predictive of the persistence of effortful responding; most notably when the probabilities of reward and non-reward were equivalent. These data suggest that although deficits in reward processes contribute to the likelihood of persisting in reward-driven behavior, they contribute little to the initiation of such behavior.

Age-Normative Pathways of Striatal Connectivity Related to Clinical Symptoms in the General Population.

BACKGROUND: Altered striatal development contributes to core deficits in motor and inhibitory control, impulsivity, and inattention associated with attention-deficit/hyperactivity disorder and may likewise play a role in deficient reward processing and emotion regulation in psychosis and depression. The maturation of striatal connectivity has not been well characterized, particularly as it relates to clinical symptomatology. METHODS: Resting-state functional connectivity with striatal subdivisions was examined for 926 participants (8-22 years of age, 44% male) from the general population who had participated in two large cross-sectional studies. Developing circuits were identified and growth charting of age-related connections was performed to obtain individual scores reflecting relative neurodevelopmental attainment. Associations of clinical symptom scales (attention-deficit/hyperactivity disorder, psychosis, depression, and general psychopathology) with the resulting striatal connectivity age-deviation scores were then tested using elastic net regression. RESULTS: Linear and nonlinear developmental patterns occurred across 231 striatal age-related connections. Both unique and overlapping striatal age-related connections were associated with the four symptom domains. Attention-deficit/hyperactivity disorder severity was related to age-advanced connectivity across several insula subregions, but to age-delayed connectivity with the nearby inferior frontal gyrus. Psychosis was associated with advanced connectivity with the medial prefrontal cortex and superior temporal gyrus, while aberrant limbic connectivity predicted depression. The dorsal posterior insula, a region involved in pain processing, emerged as a strong contributor to general psychopathology as well as to each individual symptom domain. CONCLUSIONS: Developmental striatal pathophysiology in the general population is consistent with dysfunctional circuitry commonly found in clinical populations. Atypical age-normative connectivity may thereby reflect aberrant neurodevelopmental processes that contribute to clinical risk.

Affective modulation of target detection in deficit and non-deficit schizophrenia.

Emotional deficits are an integral feature of schizophrenia (SZ), but our understanding of these deficits is limited. In the present study, we examined whether the severity of emotional deficits reflects difficulty in the cognitive processing of affectively valenced stimuli. Healthy controls (HC; N = 170) and stable outpatients with SZ (N = 245), characterized as either deficit syndrome (DS; N = 62) or non-deficit syndrome (NDS; N = 183), completed an Affective Go/NoGo task requiring discrimination of positively, negatively or neutrally valenced words. Accuracy (d') and response bias (c) were calculated for each of the three conditions, and a series of ANOVAs were carried out to examine group differences. Examination of accuracy revealed significant main effects of group and valence and a significant valence × group interaction, indicating that while affective valence impacted accuracy for the HC and NDS groups, the DS group maintained the same low level of accuracy across all levels of affective valence. Examination of response bias also revealed significant main effects of group and valence and a significant valence × group interaction. Specifically, within the HC and NDS groups, response bias did not differ between negatively and positively valenced words while response bias in the DS group was lowest for neutral, higher for negatively valenced and higher still for positively valenced words. These results suggest that emotional deficits in DS may be directly related to deficits in processing affective information. Moreover, although this deficit is observed across both positively and negatively valenced stimuli, it is most pronounced for positively valenced material.

Altered functional connectivity between sub-regions in the thalamus and cortex in schizophrenia patients measured by resting state BOLD fMRI at 7T.

The thalamus is a small brain structure that relays neuronal signals between subcortical and cortical regions. Abnormal thalamocortical connectivity in schizophrenia has been reported in previous studies using blood-oxygenation-level-dependent (BOLD) functional MRI (fMRI) performed at 3T. However, anatomically the thalamus is not a single entity, but is subdivided into multiple distinct nuclei with different connections to various cortical regions. We sought to determine the potential benefit of using the enhanced sensitivity of BOLD fMRI at ultra-high magnetic field (7T) in exploring thalamo-cortical connectivity in schizophrenia based on subregions in the thalamus. Seeds placed in thalamic subregions of 14 patients and 14 matched controls were used to calculate whole-brain functional connectivity. Our results demonstrate impaired thalamic connectivity to the prefrontal cortex and the cerebellum, but enhanced thalamic connectivity to the motor/sensory cortex in schizophrenia. This altered functional connectivity significantly correlated with disease duration in the patients. Remarkably, comparable effect sizes observed in previous 3T studies were detected in the current 7T study with a heterogeneous and much smaller cohort, providing evidence that ultra-high field fMRI may be a powerful tool for measuring functional connectivity abnormalities in schizophrenia. Further investigation with a larger cohort is merited to validate the current findings.