Disrupted prediction-error signal in psychosis: evidence for an associative account of delusions

Deficits in multi-scale top-down processes distorting auditory perception in schizophrenia

Cognitive models postulate that impaired source monitoring incorrectly weights the top-down prediction and bottom-up sensory processes and causes hallucinations. However, the underlying mechanisms of the interaction, such as whether the incorrectly weighting is ubiquitously on all levels of sensory features and whether different top-down processes have distinct effects in subgroups of schizophrenia are still unclear. This study investigates how multi-scale predictions influence perception of basic tonal features in schizophrenia. Sixty-three schizophrenia patients with and without symptoms of auditory verbal hallucinations (AVHs), and thirty healthy controls identified target tones in noise at the end of tone sequences. Predictions of different timescales were manipulated by either an alternating pattern in the preceding tone sequences (long-term regularity) or a repetition between the target tone and the tone immediately before (short-term repetition). The sensitivity index, d prime (d'), was obtained to assess the modulation of predictions on tone identification. Patients with AVHs showed higher d' when the target tones conformed to the long-term regularity of alternating pattern in the preceding tone sequence than when the target tones were inconsistent with the pattern. Whereas, the short-term repetition modulated the tone identification in patients without AVHs. Predictions did not influence tone identification in healthy controls. Our results suggest that impaired source monitoring in schizophrenia patients with AVHs heavily weights top-down predictions over bottom-up perceptual processes to form incorrect perception. The weighting function in source monitoring can extend to the processes of basic tonal features, and predictions at multiple timescales could differentially modulate perception in different clinical populations. The impaired interaction between top-down and bottom-up processes might underlie the development of hallucination symptoms in schizophrenia.

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.

Abnormal prediction error processing in schizophrenia and depression

To make adaptive decisions under uncertainty, individuals need to actively monitor the discrepancy between expected outcomes and actual outcomes, known as prediction errors. Reward‐based learning deficits have been shown in both depression and schizophrenia patients. For this study, we compiled studies that investigated prediction error processing in depression and schizophrenia patients and performed a series of meta‐analyses. In both groups, positive t‐maps of prediction error tend to yield striatum activity across studies. The analysis of negative t‐maps of prediction error revealed two large clusters within the right superior and inferior frontal lobes in schizophrenia and the medial prefrontal cortex and bilateral insula in depression. The concordant posterior cingulate activity was observed in both patient groups, more prominent in the depression group and absent in the healthy control group. These findings suggest a possible role in dopamine‐rich areas associated with the encoding of prediction errors in depression and schizophrenia.

Psychiatric Neural Networks and Precision Therapeutics by Machine Learning

Learning and environmental adaptation increase the likelihood of survival and improve the quality of life. However, it is often difficult to judge optimal behaviors in real life due to highly complex social dynamics and environment. Consequentially, many different brain regions and neuronal circuits are involved in decision-making. Many neurobiological studies on decision-making show that behaviors are chosen through coordination among multiple neural network systems, each implementing a distinct set of computational algorithms. Although these processes are commonly abnormal in neurological and psychiatric disorders, the underlying causes remain incompletely elucidated. Machine learning approaches with multidimensional data sets have the potential to not only pathologically redefine mental illnesses but also better improve therapeutic outcomes than DSM/ICD diagnoses. Furthermore, measurable endophenotypes could allow for early disease detection, prognosis, and optimal treatment regime for individuals. In this review, decision-making in real life and psychiatric disorders and the applications of machine learning in brain imaging studies on psychiatric disorders are summarized, and considerations for the future clinical translation are outlined. This review also aims to introduce clinicians, scientists, and engineers to the opportunities and challenges in bringing artificial intelligence into psychiatric practice.

Paranoia and belief updating during a crisis

The 2019 coronavirus (COVID-19) pandemic has made the world seem unpredictable. During such crises we can experience concerns that others might be against us, culminating perhaps in paranoid conspiracy theories. Here, we investigate paranoia and belief updating in an online sample (N=1,010) in the United States of America (U.S.A). We demonstrate the pandemic increased individuals’ self-rated paranoia and rendered their task-based belief updating more erratic. Local lockdown and reopening policies, as well as culture more broadly, markedly influenced participants’ belief-updating: an early and sustained lockdown rendered people’s belief updating less capricious. Masks are clearly an effective public health measure against COVID-19. However, state-mandated mask wearing increased paranoia and induced more erratic behaviour. Remarkably, this was most evident in those states where adherence to mask wearing rules was poor but where rule following is typically more common. This paranoia may explain the lack of compliance with this simple and effective countermeasure. Computational analyses of participant behaviour suggested that people with higher paranoia expected the task to be more unstable, but at the same time predicted more rewards. In a follow-up study we found people who were more paranoid endorsed conspiracies about mask-wearing and potential vaccines – again, mask attitude and conspiratorial beliefs were associated with erratic task behaviour and changed priors. Future public health responses to the pandemic might leverage these observations, mollifying paranoia and increasing adherence by tempering people’s expectations of other’s behaviour, and the environment more broadly, and reinforcing compliance.

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

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.

Cerebellar Activation Deficits in Schizophrenia During an Eyeblink Conditioning Task

The cognitive dysmetria theory of psychotic disorders posits that cerebellar circuit abnormalities give rise to difficulties coordinating motor and cognitive functions. However, brain activation during cerebellar-mediated tasks is understudied in schizophrenia. Accordingly, this study examined whether individuals with schizophrenia have diminished neural activation compared to controls in key regions of the delay eyeblink conditioning (dEBC) cerebellar circuit (eg, lobule VI) and cerebellar regions associated with cognition (eg, Crus I). Participants with schizophrenia-spectrum disorders (n = 31) and healthy controls (n = 43) underwent dEBC during functional magnetic resonance imaging (fMRI). Images were normalized using the Spatially Unbiased Infratentorial Template (SUIT) of the cerebellum and brainstem. Activation contrasts of interest were "early" and "late" stages of paired tone and air puff trials minus unpaired trials. Preliminary whole brain analyses were conducted, followed by cerebellar-specific SUIT and region of interest (ROI) analyses of lobule VI and Crus I. Correlation analyses were conducted between cerebellar activation, neuropsychological test scores, and psychotic symptom scores. In controls, the largest clusters of cerebellar activation peaked in lobule VI during early dEBC and Crus I during late dEBC. The schizophrenia group showed robust cortical activation to unpaired trials but no significant conditioning-related cerebellar activation. Crus I ROI activation during late dEBC was greater in the control than schizophrenia group. Greater Crus I activation correlated with higher working memory scores in the full sample and lower positive psychotic symptom severity in schizophrenia. Findings indicate functional cerebellar abnormalities in schizophrenia which relate to psychotic symptoms, lending direct support to the cognitive dysmetria framework.

Chronic fatigue syndrome and fibromyalgia-like symptoms are an integral component of the phenome of schizophrenia: neuro-immune and opioid system correlates

Physiosomatic symptoms are an important part of schizophrenia phenomenology. The aim of this study is to examine the biomarker, neurocognitive and symptomatic correlates of physiosomatic symptoms in schizophrenia. We recruited 115 schizophrenia patients and 43 healthy controls and measured the Fibromyalgia and Chronic Fatigue Syndrome Rating (FF) scale, schizophrenia symptom dimensions, and the Brief Assessment of Cognition in Schizophrenia. We measured neuro-immune markers including plasma CCL11 (eotaxin), interleukin-(IL)-6, IL-10, Dickkopf protein 1 (DKK1), high mobility group box 1 protein (HMGB1) and endogenous opioid system (EOS) markers including κ-opioid receptor (KOR), μ-opioid receptor (MOR), endomorphin-2 (EM2) and β-endorphin. Patients with an increased FF score display increased ratings of psychosis, hostility, excitement, formal though disorders, psycho-motor retardation and negative symptoms as compared with patients with lower FF scores. A large part of the variance in the FF score (55.1%) is explained by the regression on digit sequencing task, token motor task, list learning, IL-10, age (all inversely) and IL-6 (positively). Neural network analysis shows that the top-6 predictors of the FF score are (in descending order): IL-6, HMGB1, education, MOR, KOR and IL-10. We found that 45.1% of the variance in a latent vector extracted from cognitive test scores, schizophrenia symptoms and the FF score was explained by HMGB1, MOR, EM2, DKK1, and CCL11. Physiosomatic symptoms are an integral part of the phenome of schizophrenia. Neurotoxic immune pathways and lowered immune regulation coupled with alterations in the EOS appear to drive the physiosomatic symptoms of schizophrenia.

Modeling perception and behavior in individuals at clinical high risk for psychosis: Support for the predictive processing framework

Early intervention in psychotic spectrum disorders is critical for maximizing key clinical outcomes. While there is some evidence for the utility of intervention during the prodromal phase of the illness, efficacy of interventions is difficult to assess without appropriate risk stratification. This will require biomarkers that robustly help to identify risk level and are also relatively easy to obtain. Recent work highlights the utility of computer-based behavioral tasks for understanding the pathophysiology of psychotic symptoms. Computational modeling of performance on such tasks may be particularly useful because they explicitly and formally link performance and symptom expression. Several recent studies have successfully applied principles of Bayesian inference to understanding the computational underpinnings of hallucinations. Within this framework, hallucinations are seen as arising from an over-weighting of prior beliefs relative to sensory evidence. This view is supported by recently-published data from two tasks: the Conditioned Hallucinations (CH) task, which determines the degree to which participants use expectations in detecting a target tone; and a Sine-Vocoded Speech (SVS) task, in which participants can use prior exposure to speech samples to inform their understanding of degraded speech stimuli. We administered both of these tasks to two samples of participants at clinical high risk for psychosis (CHR; N = 19) and healthy controls (HC; N = 17). CHR participants reported both more conditioned hallucinations and more pre-training SVS detection. In addition, relationships were found between participants' performance on both tasks. On computational modeling of behavior on the CH task, CHR participants demonstrate significantly poorer recognition of task volatility as well as a trend toward higher weighting of priors. A relationship was found between this latter effect and performance on both tasks. Taken together, these results support the assertion that these two tasks may be driven by similar latent factors in perceptual inference, and highlight the potential utility of computationally-based tasks in identifying risk.

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.

Parietal-Prefrontal Feedforward Connectivity in Association With Schizophrenia Genetic Risk and Delusions

OBJECTIVE

Conceptualizations of delusion formation implicate deficits in feedforward information updating across the posterior to prefrontal cortices, resulting in dysfunctional integration of new information about contexts in working memory and, ultimately, failure to update overfamiliar prior beliefs. The authors used functional MRI and machine learning models to address individual variability in feedforward parietal-prefrontal information updating in patients with schizophrenia. They examined relationships between feedforward connectivity, and delusional thinking and polygenic risk for schizophrenia.

METHODS

The authors studied 66 schizophrenia patients and 143 healthy control subjects during performance of context updating in working memory. Dynamic causal models of effective connectivity were focused on regions of the prefrontal and parietal cortex potentially implicated in delusion processes. The effect of polygenic risk for schizophrenia on connectivity was examined in healthy individuals. The authors then leveraged support vector regression models to define optimal normalized target connectivity tailored for each patient and tested the extent to which deviation from this target could predict individual variation in severity of delusions.

RESULTS

In schizophrenia patients, updating and manipulating context information was disproportionately less accurate than was working memory maintenance, with an interaction of task accuracy by diagnosis. Patients with delusions also tended to have relatively reduced parietal-prefrontal feedforward effective connectivity during context updating in working memory manipulation. The same connectivity was adversely influenced by polygenic risk for schizophrenia in healthy subjects. Individual patients' deviation from predicted "normal" feedforward connectivity based on the support vector regression models correlated with severity of delusions.

CONCLUSIONS

These computationally derived observations support a role for feedforward parietal-prefrontal information processing deficits in delusional psychopathology and in genetic risk for schizophrenia.

Distinct hierarchical alterations of intrinsic neural timescales account for different manifestations of psychosis

Hierarchical perceptual-inference models of psychosis may provide a holistic framework for understanding psychosis in schizophrenia including heterogeneity in clinical presentations. Particularly, hypothesized alterations at distinct levels of the perceptual-inference hierarchy may explain why hallucinations and delusions tend to cluster together yet sometimes manifest in isolation. To test this, we used a recently developed resting-state fMRI measure of intrinsic neural timescale (INT), which reflects the time window of neural integration and captures hierarchical brain gradients. In analyses examining extended sensory hierarchies that we first validated, we found distinct hierarchical INT alterations for hallucinations versus delusions in the auditory and somatosensory systems, thus providing support for hierarchical perceptual-inference models of psychosis. Simulations using a large-scale biophysical model suggested local elevations of excitation-inhibition ratio at different hierarchical levels as a potential mechanism. More generally, our work highlights the robustness and utility of INT for studying hierarchical processes relevant to basic and clinical neuroscience.

Self-Reported Cognitive Functions Predict the Trajectory of Paranoid Ideation Over a 15-Year Prospective Follow-Up

Background

This study investigated whether self-reported cognitive functions (i.e. task orientation, distractibility, persistence, flexibility, and perseverance) predict the trajectory of paranoid ideation over a 15-year prospective follow-up in adulthood.

Methods

The participants came from the population-based Young Finns study (N = 1210‒1213). Paranoid ideation was assessed with the Paranoid Ideation Scale of the Symptom Checklist-90 Revised (SCL-90R) in 1997, 2001, 2007, and 2012. Self-reported cognitive functions were evaluated in 1997 with the Task orientation, Distractibility, Persistence, and Flexibility scales of the DOTS-R (the Revised Dimensions of Temperament Survey) and the Perseverance scale of the FCB-TI (the Formal Characteristics of Behaviour – Temperament Inventory). The data was analyzed using growth curve models that were adjusted for age, sex, and socioeconomic factors in childhood and adulthood.

Results

Low self-reported task orientation, low persistence, high distractibility, low flexibility, and high perseverance predicted higher level of paranoid ideation over the 15-year follow-up.

Conclusions

Self-reported cognitive functions seem to predict paranoid ideation over a long-term follow-up. Promoting cognitive functions in early interventions may have long-term protective influences against the development of paranoid ideation in non-clinical populations.

Aberrant Salience, Information Processing, and Dopaminergic Signaling in People at Clinical High Risk for Psychosis

The aberrant salience hypothesis proposes that striatal dopamine dysregulation causes misattribution of salience to irrelevant stimuli leading to psychosis. Recently, new lines of preclinical evidence on information coding by subcortical dopamine coupled with computational models of the brain's ability to predict and make inferences about the world (predictive processing) provide a new perspective on this hypothesis. We review these and summarize the evidence for dopamine dysfunction, reward processing, and salience abnormalities in people at clinical high risk of psychosis (CHR) relative to findings in patients with psychosis. This review identifies consistent evidence for dysregulated subcortical dopamine function in people at CHR, but also indicates a number of areas where neurobiological processes are different in CHR subjects relative to patients with psychosis, particularly in reward processing. We then consider how predictive processing models may explain psychotic symptoms in terms of alterations in prediction error and precision signaling using Bayesian approaches. We also review the potential role of environmental risk factors, particularly early adverse life experiences, in influencing the prior expectations that individuals have about their world in terms of computational models of the progression from being at CHR to frank psychosis. We identify a number of key outstanding questions, including the relative roles of prediction error or precision signaling in the development of symptoms and the mechanism underlying dopamine dysfunction. Finally, we discuss how the integration of computational psychiatry with biological investigation may inform the treatment for people at CHR of psychosis.

Sensorimotor Induction of Auditory Misattribution in Early Psychosis

Dysfunction of sensorimotor predictive processing is thought to underlie abnormalities in self-monitoring producing passivity symptoms in psychosis. Experimentally induced sensorimotor conflict can produce a failure in bodily self-monitoring (presence hallucination [PH]), yet it is unclear how this is related to auditory self-monitoring and psychosis symptoms. Here we show that the induction of sensorimotor conflict in early psychosis patients induces PH and impacts auditory-verbal self-monitoring. Participants manipulated a haptic robotic system inducing a bodily sensorimotor conflict. In experiment 1, the PH was measured. In experiment 2, an auditory-verbal self-monitoring task was performed during the conflict. Fifty-one participants (31 early psychosis patients, 20 matched controls) participated in the experiments. The PH was present in all participants. Psychosis patients with passivity experiences (PE+) had reduced accuracy in auditory-verbal self-other discrimination during sensorimotor stimulation, but only when sensorimotor stimulation involved a spatiotemporal conflict (F(2, 44) = 6.68, P = .002). These results show a strong link between robotically controlled alterations in sensorimotor processing and auditory misattribution in psychosis and provide evidence for the role of sensorimotor processes in altered self-monitoring in psychosis.

The role of nicotinic cholinergic neurotransmission in delusional thinking

Delusions are a difficult-to-treat and intellectually fascinating aspect of many psychiatric illnesses. Although scientific progress on this complex topic has been challenging, some recent advances focus on dysfunction in neural circuits, specifically in those involving dopaminergic and glutamatergic neurotransmission. Here we review the role of cholinergic neurotransmission in delusions, with a focus on nicotinic receptors, which are known to play a part in some illnesses where these symptoms appear, including delirium, schizophrenia spectrum disorders, bipolar disorder, Parkinson, Huntington, and Alzheimer diseases. Beginning with what we know about the emergence of delusions in these illnesses, we advance a hypothesis of cholinergic disturbance in the dorsal striatum where nicotinic receptors are operative. Striosomes are proposed to play a central role in the formation of delusions. This hypothesis is consistent with our current knowledge about the mechanism of action of cholinergic drugs and with our abstract models of basic cognitive mechanisms at the molecular and circuit levels. We conclude by pointing out the need for further research both at the clinical and translational levels.

Atypical processing of uncertainty in individuals at risk for psychosis

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Humans at psychosis clinical high risk (CHR) over-estimate environmental volatility.

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Low-level prediction error (PE) signals evoke increased frontal activity in CHR.

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Volatility-related PEs are associated with reduced frontal activity in CHR.

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Frontal cortical activation to low-level PEs reflects impaired clinical functioning.

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Atypical PE learning signal representations may promote delusion formation in CHR.

Current theories of psychosis highlight the role of abnormal learning signals, i.e., prediction errors (PEs) and uncertainty, in the formation of delusional beliefs. We employed computational analyses of behaviour and functional magnetic resonance imaging (fMRI) to examine whether such abnormalities are evident in clinical high risk (CHR) individuals.

Non-medicated CHR individuals (n = 13) and control participants (n = 13) performed a probabilistic learning paradigm during fMRI data acquisition. We used a hierarchical Bayesian model to infer subject-specific computations from behaviour – with a focus on PEs and uncertainty (or its inverse, precision) at different levels, including environmental ‘volatility’ – and used these computational quantities for analyses of fMRI data.

Computational modelling of CHR individuals’ behaviour indicated volatility estimates converged to significantly higher levels than in controls. Model-based fMRI demonstrated increased activity in prefrontal and insular regions of CHR individuals in response to precision-weighted low-level outcome PEs, while activations of prefrontal, orbitofrontal and anterior insula cortex by higher-level PEs (that serve to update volatility estimates) were reduced. Additionally, prefrontal cortical activity in response to outcome PEs in CHR was negatively associated with clinical measures of global functioning.

Our results suggest a multi-faceted learning abnormality in CHR individuals under conditions of environmental uncertainty, comprising higher levels of volatility estimates combined with reduced cortical activation, and abnormally high activations in prefrontal and insular areas by precision-weighted outcome PEs. This atypical representation of high- and low-level learning signals might reflect a predisposition to delusion formation.

An integrative framework for perceptual disturbances in psychosis

Perceptual disturbances in psychosis, such as auditory verbal hallucinations, are associated with increased baseline activity in the associative auditory cortex and increased dopamine transmission in the associative striatum. Perceptual disturbances are also associated with perceptual biases that suggest increased reliance on prior expectations. We review theoretical models of perceptual inference and key supporting physiological evidence, as well as the anatomy of associative cortico-striatal loops that may be relevant to auditory perceptual inference. Integrating recent findings, we outline a working framework that bridges neurobiology and the phenomenology of perceptual disturbances via theoretical models of perceptual inference.

Retrospective Inference as a Form of Bounded Rationality, and Its Beneficial Influence on Learning

Probabilistic models of cognition typically assume that agents make inferences about current states by combining new sensory information with fixed beliefs about the past, an approach known as Bayesian filtering. This is computationally parsimonious, but, in general, leads to suboptimal beliefs about past states, since it ignores the fact that new observations typically contain information about the past as well as the present. This is disadvantageous both because knowledge of past states may be intrinsically valuable, and because it impairs learning about fixed or slowly changing parameters of the environment. For these reasons, in offline data analysis it is usual to infer on every set of states using the entire time series of observations, an approach known as (fixed-interval) Bayesian smoothing. Unfortunately, however, this is impractical for real agents, since it requires the maintenance and updating of beliefs about an ever-growing set of states. We propose an intermediate approach, finite retrospective inference (FRI), in which agents perform update beliefs about a limited number of past states (Formally, this represents online fixed-lag smoothing with a sliding window). This can be seen as a form of bounded rationality in which agents seek to optimize the accuracy of their beliefs subject to computational and other resource costs. We show through simulation that this approach has the capacity to significantly increase the accuracy of both inference and learning, using a simple variational scheme applied to both randomly generated Hidden Markov models (HMMs), and a specific application of the HMM, in the form of the widely used probabilistic reversal task. Our proposal thus constitutes a theoretical contribution to normative accounts of bounded rationality, which makes testable empirical predictions that can be explored in future work.

Dopamine transients do not act as model-free prediction errors during associative learning

Dopamine neurons are proposed to signal the reward prediction error in model-free reinforcement learning algorithms. This term represents the unpredicted or 'excess' value of the rewarding event, value that is then added to the intrinsic value of any antecedent cues, contexts or events. To support this proposal, proponents cite evidence that artificially-induced dopamine transients cause lasting changes in behavior. Yet these studies do not generally assess learning under conditions where an endogenous prediction error would occur. Here, to address this, we conducted three experiments where we optogenetically activated dopamine neurons while rats were learning associative relationships, both with and without reward. In each experiment, the antecedent cues failed to acquire value and instead entered into associations with the later events, whether valueless cues or valued rewards. These results show that in learning situations appropriate for the appearance of a prediction error, dopamine transients support associative, rather than model-free, learning.

Taking another's perspective promotes right parieto-frontal activity that reflects open-minded thought

Critical thinking (CT) is important for consensus building. Although the practice of CT using debate is widely used to improve open-minded thought, the cognitive processes underlying this improvement remain poorly understood. Here, functional magnetic resonance imaging (fMRI) was employed to assess how neural responses while considering another's opinion are changed by CT practice and to determine whether the cortical network showing activation changes related to personality traits is relevant to consensus building. A total of 52 healthy participants were divided into three groups for an intervention; the participants read another's reasoning regarding a controversial issue and judged whether this person's viewpoint was affirmative during fMRI measurements. The intervention required them to prepare speech texts from a designated viewpoint based on both themselves and others. Compared to the control group, the group who took another's perspective showed enhanced activation of the right parieto-frontal network, that has been implicated in belief update, cognitive reappraisal of emotion, and self-perspective inhibition. Additionally, activation of the orbitofrontal cortex was negatively correlated with a stubbornness index. The results provide the first neural evidence of the effects of CT practice and support the notion that open-minded thought underlies the benefits of this practice.

Blindness, Psychosis, and the Visual Construction of the World

The relationship between visual loss and psychosis is complex: congenital visual loss appears to be protective against the development of a psychotic disorder, particularly schizophrenia. In later life, however, visual deprivation or visual loss can give rise to hallucinosis, disorders of visual insight such as blindsight or Anton syndrome, or, in the context of neurodegenerative disorders, more complex psychotic presentations. We draw on a computational psychiatric approach to consider the foundational role of vision in the construction of representations of the world and the effects of visual loss at different developmental stages. Using a Bayesian prediction error minimization model, we describe how congenital visual loss may be protective against the development of the kind of computational deficits postulated to underlie schizophrenia, by increasing the precision (and consequent stability) of higher-level (including supramodal) priors, focusing on visual loss-induced changes in NMDA receptor structure and function as a possible mechanistic substrate. In simple terms, we argue that when people cannot see from birth, they rely more heavily on the context they extract from the other senses, and the resulting model of the world is more impervious to the false inferences, made in the face of inevitably noisy perceptual input, that characterize schizophrenia. We show how a Bayesian prediction error minimization framework can also explain the relationship between later visual loss and other psychotic symptoms, as well as the effects of visual deprivation and hallucinogenic drugs, and outline experimentally testable hypotheses generated by this approach.

Towards a Unifying Cognitive, Neurophysiological, and Computational Neuroscience Account of Schizophrenia

Psychotic experiences may be understood as altered information processing due to aberrant neural computations. A prominent example of such neural computations is the computation of prediction errors (PEs), which signal the difference between expected and experienced events. Among other areas showing PE coding, hippocampal-prefrontal-striatal neurocircuits play a prominent role in information processing. Dysregulation of dopaminergic signaling, often secondary to psychosocial stress, is thought to interfere with the processing of biologically important events (such as reward prediction errors) and result in the aberrant attribution of salience to irrelevant sensory stimuli and internal representations. Bayesian hierarchical predictive coding offers a promising framework for the identification of dysfunctional neurocomputational processes and the development of a mechanistic understanding of psychotic experience. According to this framework, mismatches between prior beliefs encoded at higher levels of the cortical hierarchy and lower-level (sensory) information can also be thought of as PEs, with important consequences for belief updating. Low levels of precision in the representation of prior beliefs relative to sensory data, as well as dysfunctional interactions between prior beliefs and sensory data in an ever-changing environment, have been suggested as a general mechanism underlying psychotic experiences. Translating the promise of the Bayesian hierarchical predictive coding into patient benefit will come from integrating this framework with existing knowledge of the etiology and pathophysiology of psychosis, especially regarding hippocampal-prefrontal-striatal network function and neural mechanisms of information processing and belief updating.

Significant repetition probability effects in schizophrenia

BACKGROUND

A growing body of evidence suggests that the comparison of expected and incoming sensory stimuli (the prediction-error (ε) processing) is impaired in schizophrenia patients (SZ). For example, in studies of mismatch negativity, an ERP component that signals ε, SZ patients show deficits in the auditory and visual modalities. To test the role of impaired ε processing further in SZ, using neuroimaging methods, we applied a repetition-suppression (RS) paradigm.

METHODS

Patients diagnosed with SZ (n = 17) as well as age- and sex- matched healthy control subjects (HC, n = 17) were presented with pairs of faces, which could either repeat or alternate. Additionally, the likelihood of repetition/alternation trials was modulated in individual blocks of fMRI recordings, testing the effects of repetition probability (P(rep)) on RS.

RESULTS

We found a significant RS in the fusiform and occipital face areas as well as in the lateral occipital cortex that was similar in healthy controls and SZ patients SZ. More importantly, we observed similar P(rep) effects (larger RS in blocks with high frequency of repetitions than in blocks with low repetition likelihood) in both the control and the patient group.

CONCLUSION

Our findings suggest that repetition_probability modulations affect the neural responses in schizophrenia patients and healthy participants similarly. This suggests that the neural mechanisms determining perceptual inferences based on stimulus probabilities remain unimpaired in schizophrenia.

A distinct inferential mechanism for delusions in schizophrenia

Delusions, a core symptom of psychosis, are false beliefs that are rigidly held with strong conviction despite contradictory evidence. Alterations in inferential processes have long been proposed to underlie delusional pathology, but previous attempts to show this have failed to yield compelling evidence for a specific relationship between inferential abnormalities and delusional severity in schizophrenia. Using a novel, incentivized information-sampling task (a modified version of the beads task), alongside well-characterized decision-making tasks, we sought a mechanistic understanding of delusions in a sample of medicated and unmedicated patients with schizophrenia who exhibited a wide range of delusion severity. In this novel task, participants chose whether to draw beads from one of two hidden jars or to guess the identity of the hidden jar, in order to minimize financial loss from a monetary endowment, and concurrently reported their probability estimates for the hidden jar. We found that patients with higher delusion severity exhibited increased information seeking (i.e. increased draws-to-decision behaviour). This increase was highly specific to delusion severity as compared to the severity of other psychotic symptoms, working-memory capacity, and other clinical and socio-demographic characteristics. Delusion-related increases in information seeking were present in unmedicated patients, indicating that they were unlikely due to antipsychotic medication. In addition, after adjusting for delusion severity, patients as a whole exhibited decreased information seeking relative to healthy individuals, a decrease that correlated with lower socioeconomic status. Computational analyses of reported probability estimates further showed that more delusional patients exhibited abnormal belief updating characterized by stronger reliance on prior beliefs formed early in the inferential process, a feature that correlated with increased information seeking in patients. Other decision-making parameters that could have theoretically explained the delusion effects, such as those related to subjective valuation, were uncorrelated with both delusional severity and information seeking among the patients. In turn, we found some preliminary evidence that subjective valuation (rather than belief updating) may explain group differences in information seeking unrelated to delusions. Together, these results suggest that abnormalities in belief updating, characterized by stronger reliance on prior beliefs formed by incorporating information presented earlier in the inferential process, may be a core computational mechanism of delusional ideation in psychosis. Our results thus provide direct empirical support for an inferential mechanism that naturally captures the characteristic rigidity associated with delusional beliefs.

Measles, magic and misidentifications: a defence of the two-factor theory of delusions

Corlett (Corlett, P. (this issue). Factor one, familiarity and frontal cortex: A challenge to the two-factor theory of delusions. Cognitive Neuropsychiatry) provides a robust critique of the two-factor theory of delusions. The heart of his critique is two challenges he derives from a paper by Tranel and Damasio (Tranel, D., & Damasio, H. (1994). Neuroanatomical correlates of electrodermal skin conductance responses. Psychophysiology, 31(5), 427-438), who illuminate the autonomic responses and brain damage of four patients often cited in support of the two-factor theory of Capgras delusion. I defend the two-factor theory against Corlett's two key challenges, arguing that his first challenge has been previously addressed, and that his second challenge is overstated. In my view, these challenges do not negate the two-factor account. Nevertheless, two-factor theorists - and computational psychiatrists - should continue to devise and test falsifiable predictions of their respective theories.

A network-based response to the two-factor theory of delusion formation

In response to Dr. Corlett's paper regarding the two factor theory of delusional misidentifications, I discuss further evidence that VMPFC damaged patients do not have an isolated factor 1 defect. I then discuss more broadly the limitations in the modular view of brain function that leads to the 2-factor theory. Finally, I propose a connectionist based interpretation of delusional misidentifications that better fits with the clinical data from patients with focal brain lesions showing how these lesion locations relate to complex brain networks.

Factor one, familiarity and frontal cortex: a challenge to the two-factor theory of delusions

INTRODUCTION

Two-factor theory suggests delusions require two neuropsychological impairments, one in perception (which furnishes content), and a second in belief evaluation (that augers formation and maintenance). Capgras delusion; the belief that one's loved one has been replaced by an imposter, then entails two independent processes; first a lack of skin conductance response to familiar faces so the loved one feels different. This has been demonstrated in four patients with damage to the ventromedial prefrontal cortex (vmPFC) but who do not have delusions. Thus two-factor theorists demand a second factor: a change in belief evaluation, which is associated with damage to the right dorsolateral prefrontal cortex (rDLPFC).

METHODS

Literature review of foundational and related papers on the cognitive neuropsychology of delusions, perception and belief.

RESULTS

The four vmPFC patients appear together in another publication, uncited by two-factor theorists, in which the full extent of their damage is documented. These four cases not only lack skin responses to familiar faces, but lack responses to salient psychological stimuli more generally, which challenges factor one. They also have damage outside vmPFC, including damage to rDLPFC, which challenges factor two.

CONCLUSION

Two-factor theory is found lacking and should be reappraised.

Comparison of emotional processing assessed with fear conditioning by interpersonal conflicts in patients with depression and schizophrenia

AIM

While emotional processing is implicated in various psychiatric illnesses, its differences among diagnoses are unclear. We compared associative learning of social values in patients with depression and schizophrenia by measuring skin conductance response to interpersonal stimuli.

METHODS

We included 20 female outpatients each with depression and schizophrenia. They underwent Pavlovian conditioning experiments in response to a classical aversive sound, and an interpersonal stimulus that was designed to cause aversive social conditioning with actors' faces coupled with negative verbal messages. Multiple regression analysis was performed to examine the associations between the degree of conditioned response and the clinical characteristics of the participants.

RESULTS

Conditioned responses during the acquisition phase in both conditions were higher in depression compared to schizophrenia. Patients with depression successfully showed fear conditioning in both conditions, and they exhibited slower extinction in the interpersonal condition. The conditioned response during the extinction phase showed a positive association with Emotion Regulation Questionnaire Expressive Suppression score, and a negative association with the Emotion Regulation Questionnaire Cognitive Reappraisal score and the use of antidepressants. Patients with schizophrenia did not become conditioned in either of the conditions. The Positive and Negative Syndrome Scale Negative Syndrome score was negatively associated with the degree of conditioned response during the acquisition phase in the interpersonal condition.

CONCLUSION

Female patients with schizophrenia, especially those who prominently demonstrated negative symptoms, suggested their intrinsic impairments in the associative learning of social context. Antidepressants and adaptive emotional regulation strategy may enhance the extinction learning of aversive social conditioning in depression.

A multicenter study of ketamine effects on functional connectivity: Large scale network relationships, hubs and symptom mechanisms

Ketamine is an uncompetitive N-methyl-d-aspartate (NMDA) glutamate receptor antagonist. It induces effects in healthy individuals that mimic symptoms associated with schizophrenia. We sought to root these experiences in altered brain function, specifically aberrant resting state functional connectivity (rsfMRI). In the present study, we acquired rsfMRI data under ketamine and placebo in a between-subjects design and analyzed seed-based measures of rsfMRI using large-scale networks, dorsolateral prefrontal cortex (DLPFC) and sub-nuclei of the thalamus. We found ketamine-induced alterations in rsfMRI connectivity similar to those seen in patients with schizophrenia, some changes that may be more comparable to early stages of schizophrenia, and other connectivity signatures seen in patients that ketamine did not recreate. We do not find any circuits from our regions of interest that correlates with positive symptoms of schizophrenia in our sample, although we find that DLPFC connectivity with ACC does correlate with a mood measure. These results provide support for ketamine's use as a model of certain biomarkers of schizophrenia, particularly for early or at-risk patients.

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Ketamine altered connectivity in default mode network, thalamus and DLPFC at rest.

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Similar patterns of altered connectivity are seen with ketamine as in psychotic patients.

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Mood symptoms correlated with DLPFC connectivity with ACC and frontal orbital cortex.

Enhanced Global-Brain Functional Connectivity in the Left Superior Frontal Gyrus as a Possible Endophenotype for Schizophrenia

The notion of dysconnectivity in schizophrenia has been put forward for many years and results in substantial attempts to explore altered functional connectivity (FC) within different networks with inconsistent results. Clinical, demographical, and methodological heterogeneity may contribute to the inconsistency. Forty-four patients with first-episode, drug-naive schizophrenia, 42 unaffected siblings of schizophrenia patients and 44 healthy controls took part in this study. Global-brain FC (GFC) was employed to analyze the imaging data. Compared with healthy controls, patients with schizophrenia and unaffected siblings shared enhanced GFC in the left superior frontal gyrus (SFG). In addition, patients had increased GFC mainly in the thalamo-cortical network, including the bilateral thalamus, bilateral posterior cingulate cortex (PCC)/precuneus, left superior medial prefrontal cortex (MPFC), right angular gyrus, and right SFG/middle frontal gyrus and decreased GFC in the left ITG/cerebellum Crus I. No other altered GFC values were observed in the siblings group relative to the control group. Further ROC analysis showed that increased GFC in the left SFG could separate the patients or the siblings from the controls with acceptable sensitivities. Our findings suggest that increased GFC in the left SFG may serve as a potential endophenotype for schizophrenia.

Supervised machine learning to decipher the complex associations between neuro-immune biomarkers and quality of life in schizophrenia

Stable phase schizophrenia is characterized by altered patterning in tryptophan catabolites (TRYCATs) and memory impairments, which are associated with PHEMN (psychosis, hostility, excitation, mannerism and negative) and DAPS (depression, anxiety and physio-somatic) symptoms. This study was carried out to examine the association between TRYCAT patterning, memory impairments, psychopathological features and health-related quality of life (HR-QoL) in schizophrenia. The World Health Organization (WHO) QoL instrument-Abbreviated version (WHO-QoL-BREF), IgA/IgM responses to TRYCATs, cognitive tests, Scale for the Assessment of Negative Symptoms (SANS), Hamilton and Depression (HAMD) and Anxiety (HAMA) Rating Scales and the Fibromyalgia and Chronic Fatigue Syndrome Rating Scale (FF) were measured in 80 schizophrenia patients and 40 controls. Neural Network analysis shows that the total HR-Qol score is best predicted by (in descending order) HAMA, FF, HAMD, and psychosis. Partial least Squares (PLS) analysis shows that 56.7% of the variance in the WHO-QoL scores is explained by PHEMN / DAPS symptoms, while 64.3% of the variance in those symptoms is explained by TRYCAT patterning and episodic/semantic memory impairments. IgA responses to picolinic acid, xanthurenic acid and 3-hydroxy-kynurenine (all negatively) and anthranilic acid (positively) have highly significant indirect effects on WHO-QoL scores, which are completely mediated by cognitive impairments and PHEMN / DAPS symptoms. The results show that lowered HR-Qol in schizophrenia is strongly associated with noxious TRYCATs and that these effects are mediated by impairments in episodic / semantic memory and schizophrenia phenomenology, especially physio-somatic and anxiety symptoms. Mucosal activation of the TRYCAT pathway combined with a deficit in natural IgM isotype antibodies to TRYCATs determine cognitive impairments and DAPS/PHEMN symptoms, which together determine to a large extent lowered HR-QoL in schizophrenia.

Exploring resting state connectivity in patients with psychotic depression

Background

Severe depression is associated with high morbidity and mortality. Neural network dysfunction may contribute to disease mechanisms underlying different clinical subtypes. Here, we apply resting-state functional magnetic resonance imaging based measures of brain connectivity to investigate network dysfunction in severely depressed in-patients with and without psychotic symptoms.

Methods

A cohort study was performed at two sites. Older patients with major depressive disorder with or without psychotic symptoms were included (n = 23 at site one, n = 26 at site two). Resting state 3-Tesla functional MRI scans, with eyes closed, were obtained and Montgomery-Åsberg Depression Rating Scales were completed. We denoised data and calculated resting state networks in the two groups separately. We selected five networks of interest (1. bilateral frontoparietal, 2.left lateralized frontoparietal, 3.right lateralized frontoparietal, 4.default mode network (DMN) and 5.bilateral basal ganglia and insula network) and performed regression analyses with severity of depression, as well as presence or absence of psychotic symptoms.

Results

The functional connectivity (FC) patterns did not correlate with severity of depression. Depressed patients with psychotic symptoms (n = 14, 61%) compared with patients without psychotic symptoms (n = 9, 39%) from site one showed significantly decreased FC in the right part of the bilateral frontoparietal network (p = 0.002). This result was not replicated when comparing patients with (n = 9, 35%) and without (n = 17, 65%) psychotic symptoms from site two.

Conclusion

Psychotic depression may be associated with decreased FC of the frontoparietal network, which is involved in cognitive control processes, such as attention and emotion regulation. These findings suggest that FC in the frontoparietal network may be related to the subtype of depression, i.e. presence of psychotic symptoms, rather than severity of depression. Since the findings could not be replicated in the 2^nd sample, replication is needed before drawing definite conclusions.

Models of persecutory delusions: a mechanistic insight into the early stages of psychosis

Identifying robust markers for predicting the onset of psychosis has been a key challenge for early detection research. Persecutory delusions are core symptoms of psychosis, and social cognition is particularly impaired in first-episode psychosis patients and individuals at risk for developing psychosis. Here, we propose new avenues for translation provided by hierarchical Bayesian models of behaviour and neuroimaging data applied in the context of social learning to target persecutory delusions. As it comprises a mechanistic model embedded in neurophysiology, the findings of this approach may shed light onto inference and neurobiological causes of transition to psychosis.

Ventral Tegmental Dopamine Neurons Participate in Reward Identity Predictions

Dopamine (DA) neurons in the ventral tegmental area (VTA) and substantia nigra (SNc) encode reward prediction errors (RPEs) and are proposed to mediate error-driven learning. However, the learning strategy engaged by DA-RPEs remains controversial. RPEs might imbue predictive cues with pure value, independently of representations of their associated outcome. Alternatively, RPEs might promote learning about the sensory features (the identity) of the rewarding outcome. Here, we show that, although both VTA and SNc DA neuron activation reinforces instrumental responding, only VTA DA neuron activation during consumption of expected sucrose reward restores error-driven learning and promotes formation of a new cue→sucrose association. Critically, expression of VTA DA-dependent Pavlovian associations is abolished following sucrose devaluation, a signature of identity-based learning. These findings reveal that activation of VTA- or SNc-DA neurons engages largely dissociable learning processes with VTA-DA neurons capable of participating in outcome-specific predictive learning, and the role of SNc-DA neurons appears limited to reinforcement of instrumental responses.

Activation of the motivation-related ventral striatum during delusional experience

Delusion is the most characteristic symptom of psychosis, occurring in almost all first-episode psychosis patients. The motivational salience hypothesis suggests delusion to originate from the experience of abnormal motivational salience. Whether the motivation-related brain circuitries are activated during the actual delusional experience remains, however, unknown. We used a forced-choice answering tree at random intervals during functional magnetic resonance imaging to capture delusional and non-delusional spontaneous experiences in patients with first-episode psychosis (n = 31) or clinical high-risk state (n = 7). The motivation-related brain regions were identified by an automated meta-analysis of 149 studies. Thirteen first-episode patients reported both delusional and non-delusional spontaneous experiences. In these patients, delusional experiences were related to stronger activation of the ventral striatum in both hemispheres. This activation overlapped with the most strongly motivation-related brain regions. These findings provide an empirical link between the actual delusional experience and the motivational salience hypothesis. Further use and development of the present methods in localizing the neurobiological basis of the most characteristic symptoms may be useful in the search for etiopathogenic pathways that result in psychotic disorders.

Differential neural reward mechanisms in treatment-responsive and treatment-resistant schizophrenia

BACKGROUND

The significant proportion of schizophrenia patients refractory to treatment, primarily directed at the dopamine system, suggests that multiple mechanisms may underlie psychotic symptoms. Reinforcement learning tasks have been employed in schizophrenia to assess dopaminergic functioning and reward processing, but these have not directly compared groups of treatment-refractory and non-refractory patients.

METHODS

In the current functional magnetic resonance imaging study, 21 patients with treatment-resistant schizophrenia (TRS), 21 patients with non-treatment-resistant schizophrenia (NTR), and 24 healthy controls (HC) performed a probabilistic reinforcement learning task, utilizing emotionally valenced face stimuli which elicit a social bias toward happy faces. Behavior was characterized with a reinforcement learning model. Trial-wise reward prediction error (RPE)-related neural activation and the differential impact of emotional bias on these reward signals were compared between groups.

RESULTS

Patients showed impaired reinforcement learning relative to controls, while all groups demonstrated an emotional bias favoring happy faces. The pattern of RPE signaling was similar in the HC and TRS groups, whereas NTR patients showed significant attenuation of RPE-related activation in striatal, thalamic, precentral, parietal, and cerebellar regions. TRS patients, but not NTR patients, showed a positive relationship between emotional bias and RPE signal during negative feedback in bilateral thalamus and caudate.

CONCLUSION

TRS can be dissociated from NTR on the basis of a different neural mechanism underlying reinforcement learning. The data support the hypothesis that a favorable response to antipsychotic treatment is contingent on dopaminergic dysfunction, characterized by aberrant RPE signaling, whereas treatment resistance may be characterized by an abnormality of a non-dopaminergic mechanism - a glutamatergic mechanism would be a possible candidate.

Brain responses to different types of salience in antipsychotic naïve first episode psychosis: An fMRI study

Abnormal salience processing has been suggested to contribute to the formation of positive psychotic symptoms in schizophrenia and related conditions. Previous research utilising reward learning or anticipation paradigms has demonstrated cortical and subcortical abnormalities in people with psychosis, specifically in the prefrontal cortex, the dopaminergic midbrain and the striatum. In these paradigms, reward prediction errors attribute motivational salience to stimuli. However, little is known about possible abnormalities across different forms of salience processing in psychosis patients, and whether any such abnormalities involve the dopaminergic midbrain. The aim of our study was, therefore, to investigate possible alterations in psychosis in neural activity in response to various forms of salience: novelty, negative emotion, targetness (task-driven salience) and rareness/deviance. We studied 14 antipsychotic naïve participants with first episode psychosis, and 37 healthy volunteers. During fMRI scanning, participants performed a visual oddball task containing these four forms of salience. Psychosis patients showed abnormally reduced signalling in the substantia nigra/ventral tegmental area (SN/VTA) for novelty, negative emotional salience and targetness; reduced striatal and occipital (lingual gyrus) signalling to novelty and negative emotional salience, reduced signalling in the amygdala, anterior cingulate cortex and parahippocamal gyrus to negative emotional salience, and reduced cerebellar signalling to novelty and negative emotional salience. Our results indicate alterations of several forms of salience processing in patients with psychosis in the midbrain SN/VTA, with additional subcortical and cortical regions also showing alterations in salience signalling, the exact pattern of alterations depending on the form of salience in question.

Unique Molecular Regulation of Higher-Order Prefrontal Cortical Circuits: Insights into the Neurobiology of Schizophrenia

Schizophrenia is associated with core deficits in cognitive abilities and impaired functioning of the newly evolved prefrontal association cortex (PFC). In particular, neuropathological studies of schizophrenia have found selective atrophy of the pyramidal cell microcircuits in deep layer III of the dorsolateral PFC (dlPFC) and compensatory weakening of related GABAergic interneurons. Studies in monkeys have shown that recurrent excitation in these layer III microcircuits generates the precisely patterned, persistent firing needed for working memory and abstract thought. Importantly, excitatory synapses on layer III spines are uniquely regulated at the molecular level in ways that may render them particularly vulnerable to genetic and/or environmental insults. Glutamate actions are remarkably dependent on cholinergic stimulation, and there are inherent mechanisms to rapidly weaken connectivity, e.g. during stress. In particular, feedforward cyclic adenosine monophosphate (cAMP)-calcium signaling rapidly weakens network connectivity and neuronal firing by opening nearby potassium channels. Many mechanisms that regulate this process are altered in schizophrenia and/or associated with genetic insults. Current data suggest that there are "dual hits" to layer III dlPFC circuits: initial insults to connectivity during the perinatal period due to genetic errors and/or inflammatory insults that predispose the cortex to atrophy, followed by a second wave of cortical loss during adolescence, e.g. driven by stress, at the descent into illness. The unique molecular regulation of layer III circuits may provide a nexus where inflammation disinhibits the neuronal response to stress. Understanding these mechanisms may help to illuminate dlPFC susceptibility in schizophrenia and provide insights for novel therapeutic targets.

Deficits in context-dependent adaptive coding in early psychosis and healthy individuals with schizotypal personality traits

Adaptive coding of information is a fundamental principle of brain functioning. It allows for efficient representation over a large range of inputs and thereby alleviates the limited coding range of neurons. In the present study, we investigated for the first time potential alterations in context-dependent reward adaptation and its association with symptom dimensions in the schizophrenia spectrum. We studied 27 patients with first-episode psychosis, 26 individuals with schizotypal personality traits and 25 healthy controls. We used functional MRI in combination with a variant of the monetary incentive delay task and assessed adaptive reward coding in two reward conditions with different reward ranges. Compared to healthy controls, patients with first-episode psychosis and healthy individuals with schizotypal personality traits showed a deficit in increasing the blood oxygen level-dependent response slope in the right caudate for the low reward range compared to the high reward range. In other words, the two groups showed inefficient neural adaptation to the current reward context. In addition, we found impaired adaptive coding of reward in the caudate nucleus and putamen to be associated with total symptom severity across the schizophrenia spectrum. Symptom severity was more strongly associated with neural deficits in adaptive coding than with the neural coding of absolute reward outcomes. Deficits in adaptive coding were prominent across the schizophrenia spectrum and even detectable in unmedicated (healthy) individuals with schizotypal personality traits. Furthermore, the association between total symptom severity and impaired adaptive coding in the right caudate and putamen suggests a dimensional mechanism underlying imprecise neural adaptation. Our findings support the idea that impaired adaptive coding may be a general information-processing deficit explaining disturbances within the schizophrenia spectrum over and above a simple model of blunted absolute reward signals.

Eotaxin, an Endogenous Cognitive Deteriorating Chemokine (ECDC), Is a Major Contributor to Cognitive Decline in Normal People and to Executive, Memory, and Sustained Attention Deficits, Formal Thought Disorders, and Psychopathology in Schizophrenia Patients

Eotaxin is increased in neurodegenerative disorders and schizophrenia, and preclinical studies indicate that eotaxin may induce cognitive deficits. This study aims to examine whether peripheral levels of eotaxin impact cognitive functioning in healthy volunteers and formal thought disorder (FTD) and psychopathology in schizophrenia patients. Serum levels of eotaxin were assayed and cognitive tests were performed on a sample of 40 healthy participants and 80 schizophrenia patients. Among healthy participants, eotaxin levels were significantly associated with episodic/semantic memory, executive functions, Mini Mental State Examination, emotion recognition, and sustained attention. In addition, age-related effects on these cognitive measures were partly mediated by eotaxin. The super-variable "age-eotaxin" predicted a large part of the variance in cognitive functions among healthy participants, and hence, eotaxin may act as an "accelerated brain aging chemokine" (ABAC). In schizophrenia, eotaxin levels had a strong impact on formal thought disorders and psychopathology. In schizophrenia, increased eotaxin strongly impacts memory and sustained attention, which together to a large extent determine FTD. FTD together with memory deficits predicts around 92.5% of the variance in psychopathology. Moreover, the effects of eotaxin are partially mediated by executive functioning, while the effects of male sex on FTD and psychopathology are mediated by eotaxin. In healthy subjects, eotaxin strongly impacts executive functioning and multiple cognitive domains. In schizophrenia, peripheral levels of eotaxin strongly impact both negative symptoms and psychosis (hallucinations and delusions), and these eotaxin effects are mediated by impairments in frontal functioning, memory, sustained attention, and FTD. Eotaxin is an endogenous cognitive deteriorating chemokine (ECDC) and a novel therapeutic target for age-related cognitive decline and schizophrenia as well.

Abnormal reward prediction-error signalling in antipsychotic naive individuals with first-episode psychosis or clinical risk for psychosis

Ongoing research suggests preliminary, though not entirely consistent, evidence of neural abnormalities in signalling prediction errors in schizophrenia. Supporting theories suggest mechanistic links between the disruption of these processes and the generation of psychotic symptoms. However, it is unknown at what stage in the pathogenesis of psychosis these impairments in prediction-error signalling develop. One major confound in prior studies is the use of medicated patients with strongly varying disease durations. Our study aims to investigate the involvement of the meso-cortico-striatal circuitry during reward prediction-error signalling in earliest stages of psychosis. We studied patients with first-episode psychosis (FEP) and help-seeking individuals at-risk for psychosis due to sub-threshold prodromal psychotic symptoms. Patients with either FEP (n = 14), or at-risk for developing psychosis (n = 30), and healthy volunteers (n = 39) performed a reinforcement learning task during fMRI scanning. ANOVA revealed significant (p < 0.05 family-wise error corrected) prediction-error signalling differences between groups in the dopaminergic midbrain and right middle frontal gyrus (dorsolateral prefrontal cortex, DLPFC). FEP patients showed disrupted reward prediction-error signalling compared to controls in both regions. At-risk patients showed intermediate activation in the midbrain that significantly differed from controls and from FEP patients, but DLPFC activation that did not differ from controls. Our study confirms that FEP patients have abnormal meso-cortical signalling of reward-prediction errors, whereas reward-prediction-error dysfunction in the at-risk patients appears to show a more nuanced pattern of activation with a degree of midbrain impairment but preserved cortical function.

Emotional context restores cortical prediction error responses in schizophrenia

The mismatch negativity (MMN) deficit in schizophrenia is a consistently replicated finding and is considered a potential biomarker. From the cognitive neuroscience perspective, MMN represents a cortical correlate of the prediction error, a fundamental computational operator that may be at the core of various cognitive and clinical deficits observed in schizophrenia. The impact of emotion on cognitive processes in schizophrenia is insufficiently understood, and its impact on basic operators of cortical computation is largely unknown. In the visual domain, the facial expression mismatch negativity (EMMN) offers an opportunity to investigate basic computational operators in purely cognitive and in emotional contexts. In this study, we asked whether emotional context enhances cortical prediction error responses in patients with schizophrenia, as is the case in normal subjects. Therefore, seventeen patients with schizophrenia and eighteen controls completed a visual sequence oddball task, which allows for directly comparing MMN components evoked by deviants with high, intermediate and low emotional engagement. Interestingly, patients with schizophrenia showed pronounced deficits in response to neutral stimuli, but almost normal responses to emotional stimuli. The dissociation between impaired MMN and normal EMMN suggests that emotional context not only enhances, but restores cortical prediction error responses in patients with schizophrenia to near-normal levels. Our results show that emotional processing in schizophrenia is not necessarily defect; more likely, emotional processing heterogeneously impacts on cognition in schizophrenia. In fact, this study suggests that emotional context may even compensate for cognitive deficits in schizophrenia that are, in a different sensory domain, discussed as biomarkers.

Organic psychosis: The pathobiology and treatment of delusions

Organic or secondary psychosis can be seen in diverse conditions such as toxic/metabolic disorders, neurodegenerative disease, and stroke. Poststroke psychosis is a rare phenomenon, but its study has significantly contributed to the understanding of delusion formation. The evidence from case studies of patients with focal strokes shows that delusions develop following unilateral damage of the right hemisphere. The majority of patients with right hemisphere stroke do not develop delusions however, and advanced neuroimaging analysis has elucidated why this symptom develops in only a small proportion. Lesions of the right lateral prefrontal cortex or lesions with connectivity to this area correlate with delusional beliefs in this subgroup. Studies of patients with primary psychosis, for example schizophrenia, or under the influence of the psychotogenic drug ketamine, also show abnormal function of this area in relation to the severity of their abnormal beliefs. The conclusion of these studies is that the right lateral prefrontal cortex is 1 hub in a neural network which includes the basal ganglia and limbic system and receives inputs from midbrain dopamine neurones. In patients with schizophrenia, or at risk of psychosis, dopamine is dysregulated and evidence suggests that faulty dopamine signaling is the precursor of delusion formation. It is therefore likely that the mechanism of delusion formation is the same in both primary and secondary psychosis. This is consistent with the mainstay of treatment of both conditions being antipsychotic medication. However, antipsychotic medication in people with cerebrovascular disease should be avoided if at all possible. This is because epidemiological studies have found that antipsychotic use is associated with an increased risk of stroke and will thus compound the possibility of a further cerebrovascular accident.