Probabilistic Category Learning and Striatal Functional Activation in Psychosis Risk

A generalized reward processing deficit pathway to negative symptoms across diagnostic boundaries

BACKGROUND

Negative symptoms are a key feature of several psychiatric disorders. Difficulty identifying common neurobiological mechanisms that cut across diagnostic boundaries might result from equifinality (i.e., multiple mechanistic pathways to the same clinical profile), both within and across disorders. This study used a data-driven approach to identify unique subgroups of participants with distinct reward processing profiles to determine which profiles predicted negative symptoms.

METHODS

Participants were a transdiagnostic sample of youth from a multisite study of psychosis risk, including 110 individuals at clinical high-risk for psychosis (CHR; meeting psychosis-risk syndrome criteria), 88 help-seeking participants who failed to meet CHR criteria and/or who presented with other psychiatric diagnoses, and a reference group of 66 healthy controls. Participants completed clinical interviews and behavioral tasks assessing four reward processing constructs indexed by the RDoC Positive Valence Systems: hedonic reactivity, reinforcement learning, value representation, and effort-cost computation.

RESULTS

k-means cluster analysis of clinical participants identified three subgroups with distinct reward processing profiles, primarily characterized by: a value representation deficit (54%), a generalized reward processing deficit (17%), and a hedonic reactivity deficit (29%). Clusters did not differ in rates of clinical group membership or psychiatric diagnoses. Elevated negative symptoms were only present in the generalized deficit cluster, which also displayed greater functional impairment and higher psychosis conversion probability scores.

CONCLUSIONS

Contrary to the equifinality hypothesis, results suggested one global reward processing deficit pathway to negative symptoms independent of diagnostic classification. Assessment of reward processing profiles may have utility for individualized clinical prediction and treatment.

Global reward processing deficits predict negative symptoms transdiagnostically and transphasically in a severe mental illness-spectrum sample

Reward processing impairments are a key factor associated with negative symptoms in those with severe mental illnesses. However, past findings are inconsistent regarding which reward processing components are impaired and most strongly linked to negative symptoms. The current study examined the hypothesis that these mixed findings may be the result of multiple reward processing pathways (i.e., equifinality) to negative symptoms that cut across diagnostic boundaries and phases of illness. Participants included healthy controls (n = 100) who served as a reference sample and a severe mental illness-spectrum sample (n = 92) that included psychotic-like experiences, clinical high-risk for psychosis, bipolar disorder, and schizophrenia participants. All participants completed tasks measuring four RDoC Positive Valence System constructs: value representation, reinforcement learning, effort-cost computation, and hedonic reactivity. A k-means cluster analysis of the severe mental illness-spectrum samples identified three clusters with differential reward processing profiles that were characterized by: (1) global reward processing deficits (22.8%), (2) selective impairments in hedonic reactivity alone (40.2%), and (3) preserved reward processing (37%). Elevated negative symptoms were only observed in the global reward processing cluster. All clusters contained participants from each clinical group, and the distribution of these groups did not significantly differ among the clusters. Findings identified one pathway contributing to negative symptoms that was transdiagnostic and transphasic. Future work further characterizing divergent pathways to negative symptoms may help to improve symptom trajectories and personalized treatments.

Why do individuals with Williams syndrome or Down syndrome fail the Weather Prediction Task?

Williams syndrome (WS) and Down syndrome (DS) are two neurodevelopmental disorders with distinct genetic origins characterized by mild to moderate intellectual disability. Individuals with WS or DS exhibit impaired hippocampus-dependent place learning and enhanced striatum-dependent spatial response learning. Here, we used the Weather Prediction Task (WPT), which can be solved using hippocampus- or striatum-dependent learning strategies, to determine whether individuals with WS or DS exhibit similar profiles outside the spatial domain. Only 10% of individuals with WS or DS solved the WPT. We further assessed whether a concurrent memory task could promote reliance on procedural learning to solve the WPT in individuals with WS but found that the concurrent task did not improve performance. To understand how the probabilistic cue-outcome associations influences WPT performance, and whether individuals with WS or DS can ignore distractors, we assessed performance using a visual learning task with differing reward contingencies, and a modified WPT with unpredictive cues. Both probabilistic feedback and distractors negatively impacted the performance of individuals with WS or DS. These findings are consistent with deficits in hippocampus-dependent learning and executive functions, and reveal the importance of congruent feedback and the minimization of distractors to optimize learning in these two populations.

Changes in responses of the amygdala and hippocampus during fear conditioning are associated with persecutory beliefs

The persecutory delusion is the most common symptom of psychosis, yet its underlying neurobiological mechanisms are poorly understood. Prior studies have suggested that abnormalities in medial temporal lobe-dependent associative learning may contribute to this symptom. In the current study, this hypothesis was tested in a non-clinical sample of young adults without histories of psychiatric treatment (n = 64), who underwent classical Pavlovian fear conditioning while fMRI data were collected. During the fear conditioning procedure, participants viewed images of faces which were paired (the CS+) or not paired (the CS-) with an aversive stimulus (a mild electrical shock). Fear conditioning-related neural responses were measured in two medial temporal lobe regions, the amygdala and hippocampus, and in other closely connected brain regions of the salience and default networks. The participants without persecutory beliefs (n = 43) showed greater responses to the CS- compared to the CS+ in the right amygdala and hippocampus, while the participants with persecutory beliefs (n = 21) failed to exhibit this response. These between-group differences were not accounted for by symptoms of depression, anxiety or a psychosis risk syndrome. However, the severity of subclinical psychotic symptoms overall was correlated with the level of this aberrant response in the amygdala (p = .013) and hippocampus (p = .033). Thus, these findings provide evidence for a disruption of medial temporal lobe-dependent associative learning in young people with subclinical psychotic symptoms, specifically persecutory thinking.

Impaired implicit learning in adults with anorexia nervosa

OBJECTIVE

Cognitive alterations play an important role in the pathophysiology and treatment of anorexia nervosa (AN). Previous studies suggest that some implicit learning processes may be inhibited in AN. However, this has not yet been fully explored. The purpose of this study is to analyze implicit learning in patients with AN in comparison to healthy controls.

METHODS

In this pilot-study, a total of 21 patients diagnosed with AN and 21 matched controls were administered the weather prediction task (WPT), a probabilistic implicit category learning task that consists of two sub-variants. During the feedback (FB) version of the task, participants learn associations between tarot cards and weather outcomes via an operant learning model through which they receive immediate FB on their answers, whereas during the paired associate (PA) variant, participants are directly asked to memorize given associations.

RESULTS

AN patients showed selective impairment on the FB task where they scored significantly lower both in comparison to controls (p = .001) who completed the same task and when compared to their own performance on the PA variant (p = .006). Clinical measures showed no significant correlations with test scores.

DISCUSSION

Our results demonstrate implicit FB learning deficiencies in adult patients with AN. These impairments may have an impact on the effect of psychotherapeutic interventions and could partially explain the lack of treatment response in AN. Further studies are necessary to derive when and through which mechanisms these alterations originate, and to what extent they should be considered during treatment of the disorder.

PUBLIC SIGNIFICANCE

Cognitive impairments pose a challenge in the management of anorexia nervosa. Improved comprehension of cognitive alterations could lead to a greater understanding of the disease and adaptation of psychotherapeutic treatments. In this study, we found that implicit feedback learning in anorexia nervosa is impaired compared to healthy controls. This could indicate the necessity of treatment adaptations in the form of therapy tools without feedback and a larger focus on psychoeducation.

Environmental context predicts state fluctuations in negative symptoms in youth at clinical high risk for psychosis

BACKGROUND

Negative symptoms (avolition, anhedonia, asociality) are a prevalent symptom in those across the psychosis-spectrum and also occur at subclinical levels in the general population. Recent work has begun to examine how environmental contexts (e.g. locations) influence negative symptoms. However, limited work has evaluated how environments may contribute to negative symptoms among youth at clinical high risk for psychosis (CHR). The current study uses Ecological Momentary Assessment to assess how four environmental contexts (locations, activities, social interactions, social interaction method) impact state fluctuations in negative symptoms in CHR and healthy control (CN) participants.

METHODS

CHR youth (n = 116) and CN (n = 61) completed 8 daily surveys for 6 days assessing negative symptoms and contexts.

RESULTS

Mixed-effects modeling demonstrated that negative symptoms largely varied across contexts in both groups. CHR participants had higher negative symptoms than CN participants in most contexts, but groups had similar symptom reductions during recreational activities and phone call interactions. Among CHR participants, negative symptoms were elevated in several contexts, including studying/working, commuting, eating, running errands, and being at home.

CONCLUSIONS

Results demonstrate that negative symptoms dynamically change across some contexts in CHR participants. Negative symptoms were more intact in some contexts, while other contexts, notably some used to promote functional recovery, may exacerbate negative symptoms in CHR. Findings suggest that environmental factors should be considered when understanding state fluctuations in negative symptoms among those at CHR participants.

Reinforcement learning profiles and negative symptoms across chronic and clinical high-risk phases of psychotic illness

Negative symptoms are prominent in individuals with schizophrenia (SZ) and youth at clinical high-risk for psychosis (CHR). In SZ, negative symptoms are linked to reinforcement learning (RL) dysfunction; however, previous research suggests implicit RL remains intact. It is unknown whether implicit RL is preserved in the CHR phase where negative symptom mechanisms are unclear, knowledge of which may assist in developing early identification and prevention methods. Participants from two studies completed an implicit RL task: Study 1 included 53 SZ individuals and 54 healthy controls (HC); Study 2 included 26 CHR youth and 23 HCs. Bias trajectories reflecting implicit RL were compared between groups and correlations with negative symptoms were examined. Cluster analysis investigated RL profiles across the combined samples. Implicit RL was comparable between HC and their corresponding SZ and CHR groups. However, cluster analysis was able to parse performance heterogeneity across diagnostic boundaries into two distinct RL profiles: a Positive/Early Learning cluster (65% of participants) with positive bias scores increasing from the first to second task block, and a Negative/Late Learning cluster (35% of participants) with negative bias scores increasing from the second to third block. Clusters did not differ in the proportion of CHR vs. SZ cases; however, the Negative/Late Learning cluster had more severe negative symptoms. Although implicit RL is intact in CHR similar to SZ, distinct implicit RL phenotypic profiles with elevated negative symptoms were identified trans-phasically, suggesting distinct reward-processing mechanisms can contribute to negative symptoms independent of phases of illness.

When and how do children solve the Weather Prediction Task?

The Weather Prediction Task (WPT) can be solved by adults using several strategies dependent on different memory systems. One developmental study reported that 8-12-year-old children can solve WPT-like tasks but, because of inadequate analyses, the cognitive processes involved in solving the task have not been established. The present study aimed to determine at what age children can first solve the WPT and identify the strategies used by children of different ages. We tested 3-12-year-old typically developing children and 20-30-year-old adults on a modified WPT. We performed detailed analyses of performance for each pattern of cue-outcome associations to decipher the strategies used by participants. None of the 3-5.5-year-old children solved the task. About one third of 5.5-7.5-year-old children performed above chance, relying only on the two most predictive cues. In contrast, about 80% of 7.5-12-year-old children performed above chance, relying on a conditional hierarchical strategy. Similar to 20-30-year-old adults, 7.5-12-year-old children considered the highly predictive cues primarily and the less predictive cues secondarily. These findings indicate that the learning strategies used to solve the WPT evolve from middle to late childhood and reflect an increasing ability to use a conditional strategy concomitant with the development of the hippocampus-dependent memory system.

What Is the Weather Prediction Task Good for? A New Analysis of Learning Strategies Reveals How Young Adults Solve the Task

The Weather Prediction Task (WPT) was originally designed to assess probabilistic classification learning. Participants were believed to gradually acquire implicit knowledge about cue–outcome association probabilities and solve the task using a multicue strategy based on the combination of all cue–outcome probabilities. However, the cognitive processes engaged in the resolution of this task have not been firmly established, and despite conflicting results, the WPT is still commonly used to assess striatal or procedural learning capacities in various populations. Here, we tested young adults on a modified version of the WPT and performed novel analyses to decipher the learning strategies and cognitive processes that may support above chance performance. The majority of participants used a hierarchical strategy by assigning different weights to the different cues according to their level of predictability. They primarily based their responses on the presence or absence of highly predictive cues and considered less predictive cues secondarily. However, the influence of the less predictive cues was inconsistent with the use of a multicue strategy, since they did not affect choices when both highly predictive cues associated with opposite outcomes were present simultaneously. Our findings indicate that overall performance is inadequate to draw conclusions about the cognitive processes assessed by the WPT. Instead, detailed analyses of performance for the different patterns of cue–outcome associations are essential to determine the learning strategies used by participants to solve the task.

The Electroretinogram as a Potential Biomarker of Psychosis in Children at Familial Risk

We previously proposed the electroretinogram (ERG) as a promising biomarker of major psychiatric disorders such as schizophrenia (SZ) and bipolar disorder (BP), given that we found anomalies in the ERG parameters of patients with these diagnoses as well as in their children who are at high risk (HR) of developing such disorders. The aim of the present study is to investigate the usefulness of the ERG for individual detection, among HR children, of an ERG profile resembling that of a SZ patient, as this may indicate a stronger likelihood of transition to psychosis. Using a logistic regression model previously derived from the ERG assessments of SZ patients and control (CT) subjects, individual risk scores were obtained for 61 HR and 80 CT youth. Those with a very high individual risk score were classified as "schizophrenia-like" (SZ-like). We found that the HR subjects were 3.5 times more likely to be classified as SZ-like than the CT subjects (95% CI [1.1-11.8]). Furthermore, among the HR subjects, we studied the relationship between the SZ-like classification and psychotic-like experiences and found that HR subjects classified as SZ-like were 2.7 times more likely than all remaining HR subjects to have experienced psychotic-like symptoms (95% CI [1.3-4.6]), and 6.8 times more likely than those with a very low individual risk score (95% CI [1.4-40.4]). Our results suggest that a model previously derived from ERG data on SZ patients could be a potential tool for early detection of the susceptibility to a psychotic-like disorder among familial HR children.

Strategy Development and Feedback Processing During Complex Category Learning

In this study, 38 young adults participated in a probabilistic A/B prototype category learning task under observational and feedback-based conditions. The study compared learning success (testing accuracy) and strategy use (multi-cue vs. single feature vs. random pattern) between training conditions. The feedback-related negativity (FRN) and P3a event related potentials were measured to explore the relationships between feedback processing and strategy use under a probabilistic paradigm. A greater number of participants were found to utilize an optimal, multi-cue strategy following feedback-based training than observational training, adding to the body of research suggesting that feedback can influence learning approach. There was a significant interaction between training phase and strategy on FRN amplitude. Specifically, participants who used a strategy in which category membership was determined by a single feature (single feature strategy) exhibited a significant decrease in FRN amplitude from early training to late training, perhaps due to reduced utilization of feedback or reduced prediction error. There were no significant main or interaction effects between valence, training phase, or strategy on P3a amplitude. Findings are consistent with prior research suggesting that learners vary in their approach to learning and that training method influences learning. Findings also suggest that measures of feedback processing during probabilistic category learning may reflect changes in feedback utilization and may further illuminate differences among individual learners.

Associations between long-term psychosis risk, probabilistic category learning, and attenuated psychotic symptoms with cortical surface morphometry

Neuroimaging studies have consistently found structural cortical abnormalities in individuals with schizophrenia, especially in structural hubs. However, it is unclear what abnormalities predate psychosis onset and whether abnormalities are related to behavioral performance and symptoms associated with psychosis risk. Using surface-based morphometry, we examined cortical volume, gyrification, and thickness in a psychosis risk group at long-term risk for developing a psychotic disorder (n = 18; i.e., extreme positive schizotypy plus interview-rated attenuated psychotic symptoms [APS]) and control group (n = 19). Overall, the psychosis risk group exhibited cortical abnormalities in multiple structural hub regions, with abnormalities associated with poorer probabilistic category learning, a behavioral measure strongly associated with psychosis risk. For instance, the psychosis risk group had hypogyria in a right posterior midcingulate cortical hub and left superior parietal cortical hub, as well as decreased volume in a right pericalcarine hub. Morphometric measures in all of these regions were also associated with poorer probabilistic category learning. In addition to decreased right pericalcarine volume, the psychosis risk group exhibited a number of other structural abnormalities in visual network structural hub regions, consistent with previous evidence of visual perception deficits in psychosis risk. Further, severity of APS hallucinations, delusional ideation, and suspiciousness/persecutory ideas were associated with gyrification abnormalities, with all domains associated with hypogyria of the right lateral orbitofrontal cortex. Thus, current results suggest that structural abnormalities, especially in structural hubs, are present in psychosis risk and are associated both with poor learning on a psychosis risk-related task and with APS severity.

Reinforcement learning abnormalities in the attenuated psychosis syndrome and first episode psychosis

Prior studies indicate that chronic schizophrenia (SZ) is associated with a specific profile of reinforcement learning abnormalities. These impairments are characterized by: 1) reductions in learning rate, and 2) impaired Go learning and intact NoGo learning. Furthermore, each of these deficits are associated with greater severity of negative symptoms, consistent with theoretical perspectives positing that avolition and anhedonia are associated with impaired value representation. However, it is unclear whether these deficits extend to earlier phases of psychotic illness and when individuals are unmedicated. Two studies were conducted to examine reinforcement learning deficits in earlier phases of psychosis and in high risk patients. In study 1, participants included 35 participants with first episode psychosis (FEP) with limited antipsychotic medication exposure and 25 healthy controls (HC). Study 2 included 17 antipsychotic naïve individuals who were at clinical high-risk for psychosis (CHR) (i.e., attenuated psychosis syndrome) and 18 matched healthy controls (HC). In both studies, participants completed the Temporal Utility Integration Task, a measure of probabilistic reinforcement learning that contained Go and NoGo learning blocks. FEP displayed impaired Go and NoGo learning. In contrast, CHR did not display impairments in Go or NoGo learning. Impaired Go learning was not significantly associated with clinical outcomes in the CHR or FEP samples. Findings provide new evidence for areas of spared and impaired reinforcement learning in early phases of psychosis.

Evidence of reward system dysfunction in youth at clinical high-risk for psychosis from two event-related fMRI paradigms

Abnormal reward processing is thought to play an important role in the development of psychosis, but relatively few studies have examined reward prediction errors, reinforcement learning (RL), and the reward circuitry that subserves these interconnected processes among individuals at clinical high-risk (CHR) for the disorder. Here, we present behavioral and functional neuroimaging results of two experimental tasks designed to measure overlapping aspects of reward processing among individuals at CHR (n = 22) and healthy controls (n = 19). We found no group differences in response times to positive, negative, or neutral outcome-signaling cues, and no significant differences in brain activation during reward anticipation or receipt. Youth at CHR, however, displayed clear RL impairments, as well as attenuated responses to rewards and blunted prediction error signals in the ventral striatum, dorsal anterior cingulate cortex (dACC), and ventromedial prefrontal cortex (vmPFC). Greater contrasts for cue valence (gain-loss) and outcome magnitude (large-small) in the vmPFC were associated with more severe negative symptoms, and deficits in dACC signaling during RL were associated with more depressive symptoms. Our results provide evidence for RL deficits and abnormal prediction error signaling in the brain's reward circuitry among individuals at CHR, while also suggesting that reward motivation may be relatively preserved at this stage in development. Longitudinal studies, medication-free participants, and comparison of neurobehavioral measures against both healthy and clinical controls are needed to better understand the role of reward system abnormalities in the development of psychosis.

Psychosis risk is associated with decreased white matter integrity in limbic network corticostriatal tracts

It is thought that altered connectivity between the striatum and the cortex could contribute to psychosis. However, whether psychosis risk is associated with altered white matter connectivity between the striatum and any cortical region is still unclear. Further, no previous study has directly examined whether psychosis risk is associated with altered striatal connectivity with specific cortical networks. The current study examined the integrity of corticostriatal white matter tracts in psychosis risk (n=18) and in non-psychosis risk comparison participants (n=19). We used probabilistic tractography to identify white matter tracts connecting each of four different striatal subregions with their most functionally connected cortical network: limbic, default mode, frontoparietal, and motor networks. We then compared groups on fractional anisotropy in these four tracts. Psychosis risk was associated with decreased fractional anisotropy in white matter tracts connecting the limbic striatum with the limbic cortical network, especially in an anterior right external capsule segment and in tracts specifically connected to the right prefrontal cortex. In contrast, psychosis risk was not associated with decreased white matter integrity in other corticostriatal tracts. Hence, the current research suggests that psychosis risk is especially associated with decreased corticostriatal white matter integrity involved in processing emotional and personally relevant information.

Terminology and assessment tools of psychosis: A systematic narrative review

AIM

Phenomena within the psychosis continuum that varies in frequency/duration/intensity have been increasingly identified. Different terms describe these phenomena, however there is no standardization within the terminology. This review evaluated the definitions and assessment tools of seven terms - (i) 'psychotic experiences'; (ii) 'psychotic-like experiences'; (iii) 'psychotic-like symptoms'; (iv) 'attenuated psychotic symptoms'; (v) 'prodromal psychotic symptoms'; (vi) 'psychotic symptomatology'; and (vii) 'psychotic symptoms'.

METHODS

EMBASE, MEDLINE, and CINAHL were searched during February-March 2019. Inclusion criteria included 1989-2019, full text, human, and English. Papers with no explicit definition or assessment tool, duplicates, conference abstracts, systematic reviews, meta-analyses, or no access were excluded.

RESULTS

A total of 2238 papers were identified and of these, 627 were included. Definitions and assessment tools varied, but some trends were found. Psychotic experiences and psychotic-like experiences were transient and mild, found in the general population and those at-risk. Psychotic-like symptoms were subthreshold and among at-risk populations and non-psychotic mental disorders. Attenuated psychotic symptoms were subthreshold but associated with distress, risk, and help-seeking. Prodromal psychotic symptoms referred to the prodrome of psychotic disorders. Psychotic symptomatology included delusions and hallucinations within psychotic disorders. Psychotic symptoms was the broadest term, encompassing a range of populations but most commonly involving hallucinations, delusions, thought disorder, and disorganization.

DISCUSSION

A model for conceptualizing the required terms is proposed and future directions needed to advance this field of research are discussed.

Functional, Anatomical, and Morphological Networks Highlight the Role of Basal Ganglia-Thalamus-Cortex Circuits in Schizophrenia

Evidence from electrophysiological, functional, and structural research suggests that abnormal brain connectivity plays an important role in the pathophysiology of schizophrenia. However, most previous studies have focused on single modalities only, each of which is associated with its own limitations. Multimodal combinations can more effectively utilize various information, but previous multimodal research mostly focuses on extracting local features, rather than carrying out research based on network perspective. This study included 135 patients with schizophrenia and 148 sex- and age-matched healthy controls. Functional magnetic resonance imaging, diffusion tensor imaging, and structural magnetic resonance imaging data were used to construct the functional, anatomical, and morphological networks of each participant, respectively. These networks were used in combination with machine learning to identify more consistent biomarkers of brain connectivity and explore the relationships between different modalities. We found that although each modality had divergent connectivity biomarkers, the convergent pattern was that all were mostly located within the basal ganglia-thalamus-cortex circuit. Furthermore, using the biomarkers of these 3 modalities as a feature yielded the highest classification accuracy (91.75%, relative to a single modality), suggesting that the combination of multiple modalities could be effectively utilized to obtain complementary information regarding different mode networks; furthermore, this information could help distinguish patients. These findings provide direct evidence for the disconnection hypothesis of schizophrenia, suggesting that abnormalities in the basal ganglia-thalamus-cortex circuit can be used as a biomarker of schizophrenia.

Striatum-related functional activation during reward- versus punishment-based learning in psychosis risk

Psychosis is strongly related to increased striatal dopamine. However, the neural consequences of increased striatal dopamine in psychosis risk are still not fully understood. Consistent with an increase in striatal dopamine, in previous research, psychosis risk has been associated with neural EEG evidence of a greater response to unexpected reward than unexpected punishment feedback on a reversal-learning task. However, previous research has not directly examined whether psychosis risk is associated with altered striatal activation when receiving unexpected feedback on this task. There were two groups of participants: an antipsychotic medication-naive psychosis risk group (n = 21) who had both (a) extreme levels of self-reported psychotic-like beliefs and experiences and (b) interview-rated current-attenuated psychotic symptoms; and a comparison group (n = 20) who had average levels of self-reported psychotic-like beliefs and experiences. Participants completed a reversal-leaning task during fMRI scanning. As expected, in both ROI and whole-brain analyses, the psychosis risk group exhibited greater striatal activation (for whole-brain analyses, the peak was located in the right caudate) to unexpected reward than unexpected punishment feedback relative to the comparison group. These results indicate that psychosis risk is associated with a relatively increased neural sensitivity to unexpected reward than unexpected punishment outcomes and appears consistent with increased striatal dopamine. The results may help us better understand and detect striatal dysfunction in psychosis risk.

Psychosis risk is associated with decreased resting-state functional connectivity between the striatum and the default mode network

Psychosis is linked to aberrant salience or to viewing neutral stimuli as self-relevant, suggesting a possible impairment in self-relevance processing. Psychosis is also associated with increased dopamine in the dorsal striatum, especially the anterior caudate (Kegeles et al., 2010). Critically, the anterior caudate is especially connected to (a) the cortical default mode network (DMN), centrally involved in self-relevance processing, and (b) to a lesser extent, the cortical frontoparietal network (FPN; Choi, Yeo, & Buckner, 2012). However, no previous study has directly examined striatal-cortical DMN connectivity in psychosis risk. In Study 1, we examined resting-state functional connectivity in psychosis risk (n = 18) and control (n = 19) groups between (a) striatal DMN and FPN subregions and (b) cortical DMN and FPN. The psychosis risk group exhibited decreased connectivity between the striatal subregions and the cortical DMN. In contrast, the psychosis risk group exhibited intact connectivity between the striatal subregions and the cortical FPN. Additionally, recent distress was also associated with decreased striatal-cortical DMN connectivity. In Study 2, to determine whether the decreased striatal-cortical DMN connectivity was specific to psychosis risk or was related to recent distress more generally, we examined the relationship between connectivity and distress in individuals diagnosed with nonpsychotic emotional distress disorders (N = 25). In contrast to Study 1, here we found that distress was associated with evidence of increased striatal-cortical DMN connectivity. Overall, the present results suggest that decreased striatal-cortical DMN connectivity is associated with psychosis risk and could contribute to aberrant salience.