Striatal dopamine and reward prediction error signaling in unmedicated schizophrenia patients

Increased striatal dopamine synthesis capacity has consistently been reported in patients with schizophrenia. However, the mechanism translating this into behavior and symptoms remains unclear. It has been proposed that heightened striatal dopamine may blunt dopaminergic reward prediction error signaling during reinforcement learning. In this study, we investigated striatal dopamine synthesis capacity, reward prediction errors, and their association in unmedicated schizophrenia patients (n = 19) and healthy controls (n = 23). They took part in FDOPA-PET and underwent functional magnetic resonance imaging (fMRI) scanning, where they performed a reversal-learning paradigm. The groups were compared regarding dopamine synthesis capacity (Kicer), fMRI neural prediction error signals, and the correlation of both. Patients did not differ from controls with respect to striatal Kicer. Taking into account, comorbid alcohol abuse revealed that patients without such abuse showed elevated Kicer in the associative striatum, while those with abuse did not differ from controls. Comparing all patients to controls, patients performed worse during reversal learning and displayed reduced prediction error signaling in the ventral striatum. In controls, Kicer in the limbic striatum correlated with higher reward prediction error signaling, while there was no significant association in patients. Kicer in the associative striatum correlated with higher positive symptoms and blunted reward prediction error signaling was associated with negative symptoms. Our results suggest a dissociation between striatal subregions and symptom domains, with elevated dopamine synthesis capacity in the associative striatum contributing to positive symptoms while blunted prediction error signaling in the ventral striatum related to negative symptoms

Modeling subjective relevance in schizophrenia and its relation to aberrant salience

In schizophrenia, increased aberrant salience to irrelevant events and reduced learning of relevant information may relate to an underlying deficit in relevance detection. So far, subjective estimates of relevance have not been probed in schizophrenia patients. The mechanisms underlying belief formation about relevance and their translation into decisions are unclear. Using novel computational methods, we investigated relevance detection during implicit learning in 42 schizophrenia patients and 42 healthy individuals. Participants underwent functional magnetic resonance imaging while detecting the outcomes in a learning task. These were preceded by cues differing in color and shape, which were either relevant or irrelevant for outcome prediction. We provided a novel definition of relevance based on Bayesian precision and modeled reaction times as a function of relevance weighted unsigned prediction errors (UPE). For aberrant salience, we assessed responses to subjectively irrelevant cue manifestations. Participants learned the contingencies and slowed down their responses following unexpected events. Model selection revealed that individuals inferred the relevance of cue features and used it for behavioral adaption to the relevant cue feature. Relevance weighted UPEs correlated with dorsal anterior cingulate cortex activation and hippocampus deactivation. In patients, the aberrant salience bias to subjectively task-irrelevant information was increased and correlated with decreased striatal UPE activation and increased negative symptoms. This study shows that relevance estimates based on Bayesian precision can be inferred from observed behavior. This underscores the importance of relevance detection as an underlying mechanism for behavioral adaptation in complex environments and enhances the understanding of aberrant salience in schizophrenia

Acute stress alters probabilistic reversal learning in healthy male adults

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Correction: Precision weighting of cortical unsigned prediction error signals benefits learning, is mediated by dopamine, and is impaired in psychosis.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.</jats:p

Precision weighting of cortical unsigned prediction error signals benefits learning, is mediated by dopamine, and is impaired in psychosis

Abstract: Recent theories of cortical function construe the brain as performing hierarchical Bayesian inference. According to these theories, the precision of prediction errors plays a key role in learning and decision-making, is controlled by dopamine and contributes to the pathogenesis of psychosis. To test these hypotheses, we studied learning with variable outcome-precision in healthy individuals after dopaminergic modulation with a placebo, a dopamine receptor agonist bromocriptine or a dopamine receptor antagonist sulpiride (dopamine study n = 59) and in patients with early psychosis (psychosis study n = 74: 20 participants with first-episode psychosis, 30 healthy controls and 24 participants with at-risk mental state attenuated psychotic symptoms). Behavioural computational modelling indicated that precision weighting of prediction errors benefits learning in health and is impaired in psychosis. FMRI revealed coding of unsigned prediction errors, which signal surprise, relative to their precision in superior frontal cortex (replicated across studies, combined n = 133), which was perturbed by dopaminergic modulation, impaired in psychosis and associated with task performance and schizotypy (schizotypy correlation in 86 healthy volunteers). In contrast to our previous work, we did not observe significant precision-weighting of signed prediction errors, which signal valence, in the midbrain and ventral striatum in the healthy controls (or patients) in the psychosis study. We conclude that healthy people, but not patients with first-episode psychosis, take into account the precision of the environment when updating beliefs. Precision weighting of cortical prediction error signals is a key mechanism through which dopamine modulates inference and contributes to the pathogenesis of psychosis

Striatal dopamine and decreased prediction error coding in unmedicated schizophrenia patients

Background A hyperdopaminergic state in the striatum is a corner stone in psychosis research (1, 2). However, how this neurocognitively translates into symptoms is still unknown. In that sense, the reward prediction error (RPE; eq.1) reflecting the difference between a received reward and its anticipation has been proposed as such a mediating mechanism. Previous studies in unmedicated schizophrenia patients revealed deficient RPE coding (3, 4, 5), while these signals seemed to be intact when patients received antipsychotic medication (6). Thus, the literature points towards a relation between dopamine and neural RPE coding. To our knowledge, both measures have never been tested within one schizophrenia sample. The aim of the current study was to investigate striatal dopamine synthesis capacity and RPE coding as well as their potential correlation in a sample of unmedicated schizophrenia patients. Methods In this multimodal imaging study, 21 unmedicated schizophrenia patients (Sz) and 23 matched healthy controls (HC) underwent 1) an 18F-fluorodopa PET scan measuring presynaptic dopamine synthesis capacity as well as 2) fMRI scanning where they performed a reversal learning task (7). Via computational modeling of choice data in this task (3.), individual RPE trajectories were fitted. We compared Sz and HC in their Ki-values (influx rate constants of 18F-fluorodopa) for the striatal subregions (sensorimotor, associative, limbic) as well as regarding their striatal RPE coding. In a voxel-based analysis, we correlated individual RPE coding in the striatum with striatal Ki-values while also including a group factor. Results Sz did not differ from HC in any of the striatal subregions in terms of dopamine synthesis capacity (F=0.64, p=0.70). A post-hoc analysis revealed that when taking into account comorbid alcohol abuse, that Sz without alcohol abuse displayed increased Ki-values, whereas Sz with alcohol abuse displayed Ki-values comparable to HC (F=4.65, p=0.016 for sensorimotor striatum; F=5.11, p=0.011 for associative striatum). The model-based fMRI analysis revealed a main effect for Reward Prediction Error in the bilateral ventral striatum; [-10 12 10], t = 7.40, pFWE < 0.0001 and [10 12 -10], t = 6.56, pFWE = 0.006. Sz showed decreased striatal RPE coding compared to HC (t = 3.69, pSVC for nucleus accumbens = .015) and this decrease correlated with negative symptoms ([12 8 -10], t = 3.23, pSVC for striatal PE = 0.035). In a voxel-based analysis there was a significant interaction with group, so that the RPE signal positively correlated with the limbic dopamine synthesis capacity only in HC, but not in Sz ([12 8 -12], F=11.2, pSVC for striatal PE=0.031). Discussion While we could not replicate the finding of heightened striatal dopamine synthesis capacity in the associative striatum of Sz at first, our control analyses revealed increased dopamine levels only in Sz who were not diagnosed with a comorbid alcohol abuse, while those with a respective comorbidity showed comparably normal dopamine levels. In our comparably small sample we cannot rule out other confounding factors of this group and thus future studies with larger samples are warranted for testing whether this was due to a direct effect of alcohol on dopamine synthesis capacity. In line with previous findings, the striatal RPE coding was significantly decreased in Sz and this deficit correlated with PANSS negative symptoms. In healthy controls, increased limbic striatal dopamine correlated with higher RPE coding. In Sz, this correlation was absent. Further, our findings highlight the functional dissociations between the striatal subdivisions, since the RPE finding and correlation both refer to the limbic and thus not to the associative part where dopamine levels were increased

Glutamate in the dorsolateral prefrontal cortex in patients with schizophrenia: A meta-analysis of 1H-magnetic resonance spectroscopy studies

Background: To date, there is no systematic overview of glutamate in the dorsolateral prefrontal cortex (DLPFC) of patients with schizophrenia. Here, we meta-analyzed case-control studies of high-field proton magnetic resonance spectroscopy (1H-MRS) investigating glutamate in DLPFC. Additionally, we estimated variance ratios to investigate homo/heterogeneity. Methods: Preregistration of the study was performed on September 20, 2019. The predefined literature search on PubMed comprised articles with search terms (magnetic resonance spectroscopy OR MRS) AND (glutamate OR glut∗ OR GLX) AND (schizophrenia OR psychosis OR schizophren∗). Meta-analyses with a fixed- and random-effects model with inverse variance method, DerSimonian-Laird estimator for τ2, and Cohen's d were calculated. For differences in variability, we calculated a random-effects model for measures of variance ratios. The primary study outcome was the difference in glutamate in the DLPFC in cases versus controls. Secondary outcomes were differences in variability. Results: The quantitative analysis comprised 429 cases and 365 controls. Overall, we found no group difference (d = 0.03 [95% confidence interval (CI), -0.20 to 0.26], z = 0.28, p = .78). Sensitivity analysis revealed an effect for medication status (Q = 8.35, p = .039), i.e., increased glutamate in antipsychotic-naïve patients (d = 0.46 [95% CI, 0.08 to 0.84], z = 2.37, p = .018). Concerning variance ratios, we found an effect of medication status (Q = 16.95, p < .001) due to lower coefficient of variation ratio (CVR) in medication-naïve patients (logCVR = -0.49 [95% CI, -0.78 to -0.20], z = -3.33, p < .001). In studies with medicated patients, we found higher CVR (logCVR = 0.22 [95% CI, 0.06 to 0.39], z = 2.67; p = .008). Conclusions: We carefully interpret the higher levels and lower variability in cortical glutamate in antipsychotic-naïve patients as a possible key factor resulting from a putative allostatic mechanism. We conclude that care has to be taken when evaluating metabolite levels in clinical samples in which medication might confound findings

Validating the construct of aberrant salience in schizophrenia: Behavioral evidence for an automatic process

Suspecting significance behind ordinary events is a common feature in psychosis and it is assumed to occur due to aberrant salience attribution. The Salience Attribution Test (SAT; Roiser et al., 2009) measures aberrant salience as a bias towards one out of two equally reinforced cue features as opposed to adaptive salience towards features indicating high reinforcement. This is the first study to validate the latent constructs involved in salience attribution in patients. Forty-nine schizophrenia patients and forty-four healthy individuals completed the SAT, a novel implicit salience paradigm (ISP), a reversal learning task and a neuropsychological test battery. First, groups were compared on raw measures. Second and within patients, these were correlated and then used for a principal component analysis (PCA). Third, sum scores matching the correlation and component pattern were correlated with psychopathology. Compared to healthy individuals, patients exhibited more implicit aberrant salience in the SAT and ISP and less implicit and explicit adaptive salience attribution in the SAT. Implicit aberrant salience from the SAT and ISP positively correlated with each other and negatively with reversal learning. Whereas explicit aberrant salience was associated with cognition, implicit and explicit adaptive salience were positively correlated. A similar pattern emerged in the PCA and implicit aberrant salience was associated with negative symptoms. Taken together, implicit aberrant salience from the SAT and ISP seems to reflect an automatic process that is independent from deficient salience ascription to relevant events. Its positive correlation with negative symptoms might reflect motivational deficits present in chronic schizophrenia patients