Evidence for functional improvement in reward anticipation in recent onset schizophrenia after one year of coordinated specialty care.

BACKGROUND: Motivational impairment associated with deficits in processing the anticipation of future reward is hypothesized to be a cardinal feature of schizophrenia spectrum disorders (SZ). Evidence from short-term follow-up (6-week post-treatment) studies suggests that these deficits may improve or be reversed with treatment, although longer-term outcomes are unknown. Here we examined the one-year trajectory of functional activation in brain circuitry associated with reward anticipation in people with recent onset SZ who participated in coordinated specialty care (CSC) treatment, hypothesizing normalization of brain response mirroring previous short-term findings in first-episode individuals. METHOD: Blood oxygen level-dependent (BOLD) response in the dorsal anterior cingulate cortex, anterior insula, and ventral striatum (VS) associated with reward anticipation during the Incentivized Control Engagement Task (ICE-T) was analyzed in a baseline sample of 49 healthy controls (HCs) and 52 demographically matched people with SZ, with follow-up data available for 35 HCs and 17 people with SZ. RESULTS: In agreement with our hypothesis, significant time × diagnosis interactions were observed across all regions, in which reward anticipation-associated BOLD response increased in SZ to above baseline HC levels at follow-up. Increased VS activation was associated with decreased reality distortion symptoms over the follow-up period. Baseline reward anticipation-associated BOLD response in the right anterior insula was associated with improvement in reality distortion symptoms. CONCLUSIONS: These findings suggest that functional deficits in reward anticipation may be reversed after one year of CSC in recent onset participants with SZ, and that this improvement is associated with reduced positive symptoms in the illness.

Improvement in prefrontal thalamic connectivity during the early course of the illness in recent-onset psychosis: a 12-month longitudinal follow-up resting-state fMRI study.

BACKGROUND: Previous research in resting-state functional magnetic resonance imaging (rs-fMRI) has shown a mixed pattern of disrupted thalamocortical connectivity in psychosis. The clinical meaning of these findings and their stability over time remains unclear. We aimed to study thalamocortical connectivity longitudinally over a 1-year period in participants with recent-onset psychosis. METHODS: To this purpose, 129 individuals with recent-onset psychosis and 87 controls were clinically evaluated and scanned using rs-fMRI. Among them, 43 patients and 40 controls were re-scanned and re-evaluated 12 months later. Functional connectivity between the thalamus and the rest of the brain was calculated using a seed to voxel approach, and then compared between groups and correlated with clinical features cross-sectionally and longitudinally. RESULTS: At baseline, participants with recent-onset psychosis showed increased connectivity (compared to controls) between the thalamus and somatosensory and temporal regions (k = 653, T = 5.712), as well as decreased connectivity between the thalamus and left cerebellum and right prefrontal cortex (PFC; k = 201, T = -4.700). Longitudinal analyses revealed increased connectivity over time in recent-onset psychosis (relative to controls) in the right middle frontal gyrus. CONCLUSIONS: Our results support the concept of abnormal thalamic connectivity as a core feature in psychosis. In agreement with a non-degenerative model of illness in which functional changes occur early in development and do not deteriorate over time, no evidence of progressive deterioration of connectivity during early psychosis was observed. Indeed, regionally increased connectivity between thalamus and PFC was observed.

What transcranial direct current stimulation intensity is best for cognitive enhancement?

In a recent study published in The Journal of Neurophysiology, Ehrardt et al. (Ehrhardt SE, Filmer HL, Wards Y, Mattingley JB, Dux PE. J Neurophysiol 125: 385-397, 2021) report that moderate intensity (1 mA/25 cm2) transcranial direct current stimulation (tDCS) is optimal for improving performance on a stimulus-response matching task, as opposed to a lower 0.7 mA/25 cm2 or higher 2 mA/25 cm2 dose. This result suggests that behavioral effects of tDCS do not follow a linear dose-response curve. Potential neurobiological and neurocognitive implications of these findings, as well as suggested directions for future research, are discussed.

Comparing machine and deep learning-based algorithms for prediction of clinical improvement in psychosis with functional magnetic resonance imaging.

Previous work using logistic regression suggests that cognitive control-related frontoparietal activation in early psychosis can predict symptomatic improvement after 1 year of coordinated specialty care with 66% accuracy. Here, we evaluated the ability of six machine learning (ML) algorithms and deep learning (DL) to predict "Improver" status (>20% improvement on Brief Psychiatric Rating Scale [BPRS] total score at 1-year follow-up vs. baseline) and continuous change in BPRS score using the same functional magnetic resonance imaging-based features (frontoparietal activations during the AX-continuous performance task) in the same sample (individuals with either schizophrenia (n = 65, 49M/16F, mean age 20.8 years) or Type I bipolar disorder (n = 17, 9M/8F, mean age 21.6 years)). 138 healthy controls were included as a reference group. "Shallow" ML methods included Naive Bayes, support vector machine, K Star, AdaBoost, J48 decision tree, and random forest. DL included an explainable artificial intelligence (XAI) procedure for understanding results. The best overall performances (70% accuracy for the binary outcome and root mean square error = 9.47 for the continuous outcome) were achieved using DL. XAI revealed left DLPFC activation was the strongest feature used to make binary classification decisions, with a classification activation threshold (adjusted beta = .017) intermediate to the healthy control mean (adjusted beta = .15, 95% CI = -0.02 to 0.31) and patient mean (adjusted beta = -.13, 95% CI = -0.37 to 0.11). Our results suggest DL is more powerful than shallow ML methods for predicting symptomatic improvement. The left DLPFC may be a functional target for future biomarker development as its activation was particularly important for predicting improvement.

Neuronal effects of nicotine during auditory selective attention in schizophrenia.

Although nicotine has been shown to improve attention deficits in schizophrenia, the neurobiological mechanisms underlying this effect are poorly understood. We hypothesized that nicotine would modulate attention-associated neuronal response in schizophrenia patients in the ventral parietal cortex (VPC), hippocampus, and anterior cingulate based on previous findings in control subjects. To test this hypothesis, the present study examined response in these regions in a cohort of nonsmoking patients and healthy control subjects using an auditory selective attention task with environmental noise distractors during placebo and nicotine administration. In agreement with our hypothesis, significant diagnosis (Control vs. Patient) X drug (Placebo vs. Nicotine) interactions were observed in the VPC and hippocampus. The interaction was driven by task-associated hyperactivity in patients (relative to healthy controls) during placebo administration, and decreased hyperactivity in patients after nicotine administration (relative to placebo). No significant interaction was observed in the anterior cingulate. Task-associated hyperactivity of the VPC predicted poor task performance in patients during placebo. Poor task performance also predicted symptoms in patients as measured by the Brief Psychiatric Rating Scale. These results are the first to suggest that nicotine may modulate brain activity in a selective attention-dependent manner in schizophrenia.

Levodopa modulates small-world architecture of functional brain networks in Parkinson's disease.

BACKGROUND: PD is associated with disrupted connectivity to a large number of distributed brain regions. How the disease alters the functional topological organization of the brain, however, remains poorly understood. Furthermore, how levodopa modulates network topology in PD is largely unknown. The objective of this study was to use resting-state functional MRI and graph theory to determine how small-world architecture is altered in PD and affected by levodopa administration. METHODS: Twenty-one PD patients and 20 controls underwent functional MRI scanning. PD patients were scanned off medication and 1 hour after 200 mg levodopa. Imaging data were analyzed using 226 nodes comprising 10 intrinsic brain networks. Correlation matrices were generated for each subject and converted into cost-thresholded, binarized adjacency matrices. Cost-integrated whole-brain global and local efficiencies were compared across groups and tested for relationships with disease duration and severity. RESULTS: Data from 2 patients and 4 controls were excluded because of excess motion. Patients off medication showed no significant changes in global efficiency and overall local efficiency, but in a subnetwork analysis did show increased local efficiency in executive (P = 0.006) and salience (P = 0.018) networks. Levodopa significantly decreased local efficiency (P = 0.039) in patients except within the subcortical network, in which it significantly increased local efficiency (P = 0.007). CONCLUSIONS: Levodopa modulates global and local efficiency measures of small-world topology in PD, suggesting that degeneration of nigrostriatal neurons in PD may be associated with a large-scale network reorganization and that levodopa tends to normalize the disrupted network topology in PD. © 2016 International Parkinson and Movement Disorder Society.

Between-network connectivity occurs in brain regions lacking layer IV input.

To better understand the cortical circuitry underlying connectivity between large-scale neural networks, we develop a novel, data-driven approach to identify potential integration subregions. Between-network connectivity (BNC) associated with any anatomical region is the amount of connectivity between that point and all large-scale networks, as measured using simple and multiple correlations. It is straightforward to calculate and applicable to functional networks identified using independent components analysis. We calculated BNC for all fMRI voxels within the brain and compared the results to known regional cytoarchitectural patterns. Based on previous observations of the relationship between macroscopic connectivity and microscopic cytoarchitecture, we predicted that areas with high BNC will be located in paralimbic subregions with an undifferentiated laminar structure. Results suggest that the anterior insula and dorsal posterior cingulate cortices play prominent roles in information integration. Cytoarchitecturely, these areas show agranular or dysgranular cytologies with absent or disrupted cortical layer IV. Since layer IV is the primary recipient of feed-forward thalamocortical connections, and due to the exclusive nature of driving connections to this layer, we suggest that the absence of cortical layer IV might allow for information to be exchanged across networks, and is an organizational characteristic of brain-subregions serving as inter-network communication hubs.

Greater Choline-Containing Compounds and Myo-inositol in Treatment-Resistant Versus Responsive Schizophrenia: A 1H-Magnetic Resonance Spectroscopy Meta-analysis.

BACKGROUND: The neurobiology of treatment-resistant schizophrenia (TRS) is poorly understood, and meta-analytic consensus regarding magnetic resonance spectroscopic profiles of glutamate, choline-containing compounds, myo-inositol, and other metabolites in the condition is lacking. METHODS: In this meta-analysis, we examined published findings for N-acetylaspartate, choline-containing compounds (phosphocholine+glycerophosphocholine), myo-inositol, creatine+phosphocreatine, glutamate, and glutamate+glutamine in the anterior cingulate cortex and dorsal striatum in people with TRS versus non-TRS as well as TRS versus healthy control participants (HCs) and TRS versus ultra TRS (i.e., TRS with clozapine resistance). A MEDLINE search revealed 9 articles including 239 people with pooled TRS and ultra TRS, 59 with ultra TRS, 175 with non-TRS, and 153 (HCs) that met meta-analytic criteria. RESULTS: Significant effects included higher anterior cingulate cortex phosphocholine+glycerophosphocholine and myo-inositol in the pooled TRS and ultra TRS group than in both the non-TRS group and HCs as well as higher dorsal striatal phosphocholine+glycerophosphocholine in ultra TRS versus HCs, but no differences in other regional metabolites. CONCLUSIONS: The observed metabolite profile in TRS (higher phosphocholine+glycerophosphocholine and myo-inositol signal) is consistent with the hypothesis that TRS has a neuroinflammatory component, although this meta-analysis is not a critical test of that hypothesis. A similar profile is seen in healthy aging, which is known to involve increased neuroinflammation and glial activation. Because the overall number of datasets was low, however, results should be considered preliminary and highlight the need for additional studies of brain metabolites in TRS and their possible association with inflammatory processes.

Identification of distinct clinical profiles and trajectories in individuals at high risk of developing psychosis: A latent profile analysis of the north American prodrome longitudinal study consortium-3 dataset.

AIM: People at clinical high risk (CHR) for psychosis are a heterogeneous population in regard to clinical presentation and outcome. It is unclear, however, if their baseline clinical characteristics can be used to construct orthogonal subgroups that differ in their clinical trajectory to provide early identification of individuals in need of tailored interventions. METHODS: We used latent profile analysis (LPA) to determine the number of distinct clinical profiles within the CHR population using the NAPLS-3 dataset, focusing on the clinical features incorporated in the NAPLS psychosis risk calculator (including age, unusual thought content and suspiciousness, processing speed, verbal learning and memory function, social functioning decline, life events, childhood trauma, and family history of psychosis). We then conducted a between-profile comparisons of clinical trajectories based on psychotic and depressive symptoms as well as substance use disorder (SUD) related features over time. RESULTS: Two distinct profiles emerged. One profile, comprising approximately 25% of the sample, was significantly older, displayed better cognitive performance, experienced more types of traumatic and undesirable life events, exhibited a greater decline in functioning in the past year, and was more likely to have relatives with psychosis. This group showed worse positive symptoms and SUD-related features over time, although groups did not differ in the proportion of individuals who developed psychosis. CONCLUSIONS: LPA results suggest CHRs can be segregated into two profiles with different clinical trajectories. Characterizing individuals within these clinical profiles may help understand the divergent outcomes of this population and ultimately facilitate the development of specialized interventions.

Are factors that predict conversion to psychosis associated with initial transition to a high risk state? An adolescent brain cognitive development study analysis.

OBJECTIVE: Previous work suggests that cognitive and environmental risk factors may predict conversion to psychosis in individuals at clinical high risk (CHRs) for the disorder. Less clear, however, is whether these same factors are also associated with the initial emergence of the high risk state in individuals who do not meet current threshold criteria for being considered high risk. METHOD: Here, using data from the Adolescent Brain Cognitive Development (ABCD) study, we examined associations between factors previously demonstrated to predict conversion to psychosis in CHRs with transition to a "high risk" state, here defined as having a distress score between 2 and 5 on any unusual thought content question in the Prodromal Questionnaire-Brief Child version. Of a sample of 5237 children (ages 11-12) studied at baseline, 470 transitioned to the high-risk state the following year. A logistic regression model was evaluated using age, cognition, negative and traumatic experiences, decline in school performance, and family history of psychosis as predictors. RESULTS: The overall model was significant (χ2 = 100.89, R2 = 0.042, p < .001). Significant predictors included number of negative life events, decline in school performance, number of trauma types, and verbal learning task performance. CONCLUSIONS: These results suggest that factors that predict conversion in CHR teenagers are also associated with initial emergence of a "high-risk" state in preadolescents. Limitations regarding the degree to which model factors and outcome in this study parallel those used in previous work involving psychosis risk in older teenagers are discussed.

Elevated extracellular free water in the brain predicts clinical improvement in first-episode psychosis.

BACKGROUND: Despite the diverse nature of clinical trajectories after a first-episode of psychosis, few baseline characteristics have been predictive of clinical improvement, and the neurobiological underpinnings of this heterogeneity remain largely unknown. Elevated extracellular free water (FW) in the brain is a diffusion imaging measure that has been consistently reported in different phases of psychosis that may indicate a neuroinflammatory state. Its predictive capacity in terms of clinical outcomes, however, is unknown. METHODS: We used diffusion imaging to determine FW and tissue-specific fractional anisotropy (FA-t) in first-episode psychosis. Forty-seven participants were categorized as clinical "Improvers" (n=26) if they achieved a 20% decrease in total Brief Psychiatric Rating Scale (BPRS) score at 12 months. To determine the predictive capacity of FW and FA-t, these measures were introduced in a stepwise logistic regression model to predict clinical improvement. For those measures surviving the model, regional between-group differences were also investigated in cortical surface or white matter tracts as applicable. RESULTS: Higher gray matter (GM) FW (OR-CI 1.134 - 2.543) and FA-t (OR-CI: 0.905 - 2.038) both predicted Improver status. FW in GM also linearly correlated with BPRS total score at 12 months follow-up. Examining regional specificity, Improvers showed greater FW predominantly in temporal regions and higher FA-t values in several white matter tracts, including bilateral longitudinal superior fasciculus. CONCLUSIONS: Our results show that elevated FW in GM and FA-t predict further clinical improvement during the initial phases of psychosis. The potential roles of brain inflammatory processes in predicting clinical improvement are discussed.

Whole-brain intrinsic functional connectivity predicts symptoms and functioning in early psychosis.

Theories of psychotic illness suggest that abnormal intrinsic functional connectivity may explain its characteristic positive and disorganization symptoms as well as lead to impaired general functioning. Here we used resting state functional magnetic resonance imaging (fMRI) to evaluate associations between these symptoms and the degree to which global connectivity is abnormal in early psychosis (EP). Eighty-six healthy controls (HCs) and 108 individuals with EP with resting state fMRI data were included in primary analyses. The EP group included 83 participants with schizophrenia-spectrum disorders and 25 with bipolar disorder type I with psychotic features. A global intrinsic connectivity "similarity index" for each EP individual was determined by calculating its correlation with the average HC connectivity matrix extracted using Schaefer atlases of multiple parcellations (100, 200, 300, and 400 region parcellations). As hypothesized, connectivity similarity with the average HC matrix was negatively associated with Brief Psychiatric Rating Scale total score, Scale for the Assessment of Positive Symptoms total score, and disorganization symptoms. Similarity was also positively associated with Global Assessment of Functioning score. Results were not driven by sex or diagnosis effects and were consistent across parcellation schemes. These results support the hypothesis that changes in whole-brain connectivity patterns are associated with psychosis symptoms and support the use of functional connectivity as a biomarker for these symptoms in EP.

Predicting Clinical Improvement in Early Psychosis Using Circuit-Based Resting-State Functional Magnetic Resonance Imaging.

BACKGROUND AND HYPOTHESIS: Identifying biomarkers that predict treatment response in early psychosis (EP) is a priority for psychiatry research. Previous work suggests that resting-state connectivity biomarkers may have promise as predictive measures, although prior results vary considerably in direction and magnitude. Here, we evaluated the relationship between intrinsic functional connectivity of the attention, default mode, and salience resting-state networks and 12-month clinical improvement in EP. STUDY DESIGN: Fifty-eight individuals with EP (less than 2 years from illness onset, 35 males, average age 20 years) had baseline and follow-up clinical data and were included in the final sample. Of these, 30 EPs showed greater than 20% improvement in Brief Psychiatric Rating Scale (BPRS) total score at follow-up and were classified as "Improvers." STUDY RESULTS: The overall logistic regression predicting Improver status was significant (χ2 = 23.66, Nagelkerke's R2 = 0.45, P < .001, with 85% concordance). Significant individual predictors of Improver status included higher default mode within-network connectivity, higher attention-default mode between-network connectivity, and higher attention-salience between-network connectivity. Including baseline BPRS as a predictor increased model significance and concordance to 92%, and the model was not significantly influenced by the dose of antipsychotic medication (chlorpromazine equivalents). Linear regression models predicting percent change in BPRS were also significant. CONCLUSIONS: Overall, these results suggest that resting-state functional magnetic resonance imaging connectivity may serve as a useful biomarker of clinical outcomes in recent-onset psychosis.

Neuronal effects of auditory distraction on visual attention.

Selective attention in the presence of distraction is a key aspect of healthy cognition. The underlying neurobiological processes, have not, however, been functionally well characterized. In the present study, we used functional magnetic resonance imaging to determine how ecologically relevant distracting noise affects cortical activity in 27 healthy adults during two versions of the visual Sustained Attention To Response Task (SART) that differ in difficulty (and thus attentional load). A significant condition (noise or silence) by task (easy or difficult) interaction was observed in several areas, including dorsolateral prefrontal cortex (DLPFC), fusiform gyrus (FG), posterior cingulate (PCC), and pre-supplementary motor area (PreSMA). Post hoc analyses of interaction effects revealed deactivation of DLPFC, PCC, and PreSMA during distracting noise under conditions of low attentional load, and activation of FG and PCC during distracting noise under conditions of high attentional load. These results suggest that distracting noise may help alert subjects to task goals and reduce demands on cortical resources during tasks of low difficulty and attentional load. Under conditions of higher load, however, additional cognitive resources may be required in the presence of noise.

Spectroscopic meta-analyses reveal novel metabolite profiles across methamphetamine and cocaine substance use disorder.

BACKGROUND: Although proton magnetic resonance spectroscopy (MRS) has been used to study metabolite alterations in stimulant (methamphetamine and cocaine) substance use disorders (SUDs) for over 25 years, data-driven consensus regarding the nature and magnitude of these alterations is lacking. METHOD: In this meta-analysis, we examined associations between SUD and regional metabolites (N-acetyl aspartate (NAA), choline, myo-inositol, creatine, glutamate, and glutamate+glutamine (glx)) in the medial prefrontal cortex (mPFC), frontal white matter (FWM), occipital cortex, and basal ganglia as measured by 1 H-MRS. We also examined moderating effects of MRS acquisition parameters (echo time (TE), field strength), data quality (coefficient of variation (COV)), and demographic/clinical variables. RESULTS: A MEDLINE search revealed 28 articles that met meta-analytic criteria. Significant effects included lower mPFC NAA, higher mPFC myo-inositol, and lower mPFC creatine in SUD relative to people without SUD. mPFC NAA effects were moderated by TE, with larger effects at longer TEs. For choline, although no group effects were observed, effect sizes in the mPFC were related to MRS technical indicators (field strength, COV). No effects of age, sex, primary drug of use (methamphetamine vs. cocaine), duration of use, or duration of abstinence were observed. Evidence for moderating effects of TE and COV may have implications for future MRS studies in SUDs. CONCLUSIONS: The observed metabolite profile in methamphetamine and cocaine SUD (lower NAA and creatine with higher myo-inositol) parallels that observed in Alzheimer's disease and mild cognitive impairment, suggesting these drugs are associated with neurometabolic differences similar to those characterizing these neurodegenerative conditions.

Meta-analytic evidence of elevated choline, reduced N-acetylaspartate, and normal creatine in schizophrenia and their moderation by measurement quality, echo time, and medication status.

BACKGROUND: Brain metabolite abnormalities measured with magnetic resonance spectroscopy (MRS) provide insight into pathological processes in schizophrenia. Prior meta-analyses have not yet answered important questions about the influence of clinical and technical factors on neurometabolite abnormalities and brain region differences. To address these gaps, we performed an updated meta-analysis of N-acetylaspartate (NAA), choline, and creatine levels in patients with schizophrenia and assessed the moderating effects of medication status, echo time, measurement quality, and other factors. METHODS: We searched citations from three earlier meta-analyses and the PubMed database after the most recent meta-analysis to identify studies for screening. In total, 113 publications reporting 366 regional metabolite datasets met our inclusion criteria and reported findings in medial prefrontal cortex (MPFC), dorsolateral prefrontal cortex, frontal white matter, hippocampus, thalamus, and basal ganglia from a total of 4445 patient and 3944 control observations. RESULTS: Patients with schizophrenia had reduced NAA in five of the six brain regions, with a statistically significant sparing of the basal ganglia. Patients had elevated choline in the basal ganglia and both prefrontal cortical regions. Patient creatine levels were normal in all six regions. In some regions, the NAA and choline differences were greater in studies enrolling predominantly medicated patients compared to studies enrolling predominantly unmedicated patients. Patient NAA levels were more reduced in hippocampus and frontal white matter in studies using longer echo times than those using shorter echo times. MPFC choline and NAA abnormalities were greater in studies reporting better metabolite measurement quality. CONCLUSIONS: Choline is elevated in the basal ganglia and prefrontal cortical regions, suggesting regionally increased membrane turnover or glial activation in schizophrenia. The basal ganglia are significantly spared from the well-established widespread reduction of NAA in schizophrenia suggesting a regional difference in disease-associated factors affecting NAA. The echo time findings agree with prior reports and suggest microstructural changes cause faster NAA T2 relaxation in hippocampus and frontal white matter in schizophrenia. Separating the effects of medication status and illness chronicity on NAA and choline abnormalities will require further patient-level studies. Metabolite measurement quality was shown to be a critical factor in MRS studies of schizophrenia.

Altered Associations Between Task Performance and Dorsolateral Prefrontal Cortex Activation During Cognitive Control in Schizophrenia.

BACKGROUND: Dysfunctional cognitive control processes are now well understood to be core features of schizophrenia (SZ). A body of work suggests that the dorsolateral prefrontal cortex (DLPFC) plays a critical role in explaining cognitive control disruptions in SZ. Here, we examined relationships between DLPFC activation and drift rate (DR), a model-based performance measure that combines reaction time and accuracy, in people with SZ and healthy control (HC) participants. METHODS: One hundred fifty-one people with recent-onset SZ spectrum disorders and 118 HC participants performed the AX-Continuous Performance Task during functional magnetic resonance imaging scanning. Proactive cognitive control-associated activation was extracted from left and right DLPFC regions of interest. Individual behavior was fit using a drift diffusion model, allowing DR to vary between task conditions. RESULTS: Behaviorally, people with SZ showed significantly lower DRs than HC participants, particularly during high proactive control trial types ("B" trials). Recapitulating previous findings, the SZ group also demonstrated reduced cognitive control-associated DLPFC activation compared with HC participants. Furthermore, significant group differences were also observed in the relationship between left and right DLPFC activation with DR, such that positive relationships between DR and activation were found in HC participants but not in people with SZ. CONCLUSIONS: These results suggest that DLPFC activation is less associated with cognitive control-related behavioral performance enhancements in SZ. Potential mechanisms and implications are discussed.

Altered Associations Between Motivated Performance and Frontostriatal Functional Connectivity During Reward Anticipation in Schizophrenia.

BACKGROUND AND HYPOTHESIS: The neuronal mechanisms that underlie deficits in effort cost computation in schizophrenia (SZ) are poorly understood. Given the role of frontostriatal circuits in valence-oriented motivation, we hypothesized that these circuits are either dysfunctional in SZ or do not appropriately predict behavior in SZ when task conditions are difficult and good performance is rewarded. STUDY DESIGN: A total of 52 people with recent onset SZ-spectrum disorders and 48 healthy controls (HCs) performed a 3T fMRI task with 2 valence conditions (rewarded vs neutral) and 2 difficulty conditions. Frontostriatal connectivity was extracted during the cue (anticipatory) phase. Individual behavior was fit using a drift-diffusion model, allowing the performance parameter, drift rate (DR), to vary between task conditions. Three models were examined: A group × condition model of DR, a group × condition model of connectivity, and a regression model of connectivity predicting DR depending on group and condition. STUDY RESULTS: DRs showed the expected positive correlation with accuracy and a negative association with reaction time. The SZ group showed a deficit in DR but did not differ in overall connectivity or show a valence-specific deficit in connectivity. Significant group × valence × difficulty interactions, however, were observed on the relationship between right dorsolateral prefrontal (DLPFC)-striatal connectivity and DR (DLPFC-Caudate: F = 10.92, PFDR = .004; DLPFC-Putamen: F = 5.14, PFDR = .048) driven by more positive relationships between DR and connectivity during cues for the difficult-rewarded condition in HCs compared to SZ. CONCLUSIONS: These findings suggest that frontostriatal connectivity is less predictive of performance in SZ when task difficulty is increased and a reward incentive is applied.

Increased Striatal Presynaptic Dopamine in a Nonhuman Primate Model of Maternal Immune Activation: A Longitudinal Neurodevelopmental Positron Emission Tomography Study With Implications for Schizophrenia.

BACKGROUND: Epidemiological studies suggest that maternal immune activation (MIA) is a significant risk factor for future neurodevelopmental disorders, including schizophrenia (SZ), in offspring. Consistent with findings in SZ research and work in rodent systems, preliminary cross-sectional findings in nonhuman primates suggest that MIA is associated with dopaminergic hyperfunction in young adult offspring. METHODS: In this unique prospective longitudinal study, we used [18F]fluoro-l-m-tyrosine positron emission tomography to examine the developmental time course of striatal presynaptic dopamine synthesis in male rhesus monkeys born to dams (n = 13) injected with a modified form of the inflammatory viral mimic, polyinosinic:polycytidylic acid [poly(I:C)], in the late first trimester. Striatal (caudate, putamen, and nucleus accumbens) dopamine from these animals was compared with that of control offspring born to dams that received saline (n = 10) or no injection (n = 4). Dopamine was measured at 15, 26, 38, and 48 months of age. Prior work with this cohort found decreased prefrontal gray matter volume in MIA offspring versus controls between 6 and 45 months of age. Based on theories of the etiology and development of SZ-related pathology, we hypothesized that there would be a delayed (relative to the gray matter decrease) increase in striatal fluoro-l-m-tyrosine signal in the MIA group versus controls. RESULTS: [18F]fluoro-l-m-tyrosine signal showed developmental increases in both groups in the caudate and putamen. Group comparisons revealed significantly greater caudate dopaminergic signal in the MIA group at 26 months. CONCLUSIONS: These findings are highly relevant to the known pathophysiology of SZ and highlight the translational relevance of the MIA model in understanding mechanisms by which MIA during pregnancy increases risk for later illness in offspring.