Perceiving is believing: a Bayesian approach to explaining the positive symptoms of schizophrenia

The computational relationship between reinforcement learning, social inference, and paranoia

Theoretical accounts suggest heightened uncertainty about the state of the world underpin aberrant belief updates, which in turn increase the risk of developing a persecutory delusion. However, this raises the question as to how an agent's uncertainty may relate to the precise phenomenology of paranoia, as opposed to other qualitatively different forms of belief. We tested whether the same population (n = 693) responded similarly to non-social and social contingency changes in a probabilistic reversal learning task and a modified repeated reversal Dictator game, and the impact of paranoia on both. We fitted computational models that included closely related parameters that quantified the rigidity across contingency reversals and the uncertainty about the environment/partner. Consistent with prior work we show that paranoia was associated with uncertainty around a partner's behavioural policy and rigidity in harmful intent attributions in the social task. In the non-social task we found that pre-existing paranoia was associated with larger decision temperatures and commitment to suboptimal cards. We show relationships between decision temperature in the non-social task and priors over harmful intent attributions and uncertainty over beliefs about partners in the social task. Our results converge across both classes of model, suggesting paranoia is associated with a general uncertainty over the state of the world (and agents within it) that takes longer to resolve, although we demonstrate that this uncertainty is expressed asymmetrically in social contexts. Our model and data allow the representation of sociocognitive mechanisms that explain persecutory delusions and provide testable, phenomenologically relevant predictions for causal experiments.

The promise of layer-specific neuroimaging for testing predictive coding theories of psychosis

Predictive coding potentially provides an explanatory model for understanding the neurocognitive mechanisms of psychosis. It proposes that cognitive processes, such as perception and inference, are implemented by a hierarchical system, with the influence of each level being a function of the estimated precision of beliefs at that level. However, predictive coding models of psychosis are insufficiently constrained-any phenomenon can be explained in multiple ways by postulating different changes to precision at different levels of processing. One reason for the lack of constraint in these models is that the core processes are thought to be implemented by the function of specific cortical layers, and the technology to measure layer specific neural activity in humans has until recently been lacking. As a result, our ability to constrain the models with empirical data has been limited. In this review we provide a brief overview of predictive processing models of psychosis and then describe the potential for newly developed, layer specific neuroimaging techniques to test and thus constrain these models. We conclude by discussing the most promising avenues for this research as well as the technical and conceptual challenges which may limit its application.

The positive dimension of schizotypy is associated with a reduced attenuation and precision of self-generated touch

The brain predicts the sensory consequences of our movements and uses these predictions to attenuate the perception of self-generated sensations. Accordingly, self-generated touch feels weaker than an externally generated touch of identical intensity. In schizophrenia, this somatosensory attenuation is substantially reduced, suggesting that patients with positive symptoms fail to accurately predict and process self-generated touch. If an impaired prediction underlies the positive symptoms of schizophrenia, then a similar impairment should exist in healthy nonclinical individuals with high positive schizotypal traits. One hundred healthy participants (53 female), assessed for schizotypal traits, underwent a well-established psychophysics force discrimination task to quantify how they perceived self-generated and externally generated touch. The perceived intensity of tactile stimuli delivered to their left index finger (magnitude) and the ability to discriminate the stimuli (precision) was measured. We observed that higher positive schizotypal traits were associated with reduced somatosensory attenuation and poorer somatosensory precision of self-generated touch, both when treating schizotypy as a continuous or categorical variable. These effects were specific to positive schizotypy and were not observed for the negative or disorganized dimensions of schizotypy. The results suggest that positive schizotypal traits are associated with a reduced ability to predict and process self-generated touch. Given that the positive dimension of schizotypy represents the analogue of positive psychotic symptoms of schizophrenia, deficits in processing self-generated tactile information could indicate increased liability to schizophrenia.

Postdiction in Visual Awareness in Schizophrenia

Background: The mistiming of predictive thought and real perception leads to postdiction in awareness. Individuals with high delusive thinking confuse prediction and perception, which results in impaired reality testing. The present observational study investigated how antipsychotic medications and cognitive-behavioral therapy (CBT) modulate postdiction in schizophrenia. We hypothesized that treatment reduces postdiction, especially when antipsychotics and CBT are combined. Methods: We enrolled patients with schizophrenia treated in a natural clinical setting and not in a randomized controlled trial. We followed up two schizophrenia groups matched for age, sex, education, and illness duration: patients on antipsychotics (n = 25) or antipsychotics plus CBT (n = 25). The treating clinician assigned the patients to the two groups. Participants completed a postdiction and a temporal discrimination task at weeks 0 and 12. Results: At week 0, postdiction was enhanced in patients relative to controls at a short prediction–perception time interval, which correlated with PANSS positive symptoms and delusional conviction. At week 12, postdiction was reduced in schizophrenia, especially when they received antipsychotics plus CBT. Patients with schizophrenia were also impaired on the temporal discrimination task, which did not change during the treatment. During the 12-week observational period, all PANSS scores were significantly reduced in both clinical groups, but the positive symptoms and emotional distress exhibited a more pronounced response in the antipsychotics plus CBT group. Conclusion: Perceptual postdiction is a putative neurocognitive marker of delusive thinking. Combined treatment with antipsychotics and CBT significantly ameliorates abnormally elevated postdiction in schizophrenia.

Neural network involvement for religious experiences in worship measured by EEG microstate analysis

To date, not much is known about large-scale brain activation patterns in religious states of mind and previous studies have not set an emphasis on experience. The present study investigated the phenomenon of religious experiences through microstate analysis, and it was the first neurocognitive research to tackle the dimension of experience directly. Hence, a total of 60 evangelical Christians participated in an experiment where they were asked to engage in worship and try to connect with God. With a bar slider, people were able to continuously rate how strongly they sensed God's presence at any given moment. A selection of songs was used to help in the induction of the desired experience. With 64 electroencephalography (EEG) electrodes, the brain activity was assessed and analyzed with five clusters of microstate classes. First, we hypothesized that the neural network for multisensory integration was involved in the religious experience. Second, we hypothesized that the same was true for the Default Mode Network (DMN). Our results suggested an association between the auditory network and the religious experience, and an association with the salience network as well as with the DMN. No associations with the network thought to be involved with multisensory integration was detected.

From representations in predictive processing to degrees of representational features

Whilst the topic of representations is one of the key topics in philosophy of mind, it has only occasionally been noted that representations and representational features may be gradual. Apart from vague allusions, little has been said on what representational gradation amounts to and why it could be explanatorily useful. The aim of this paper is to provide a novel take on gradation of representational features within the neuroscientific framework of predictive processing. More specifically, we provide a gradual account of two features of structural representations: structural similarity and decoupling. We argue that structural similarity can be analysed in terms of two dimensions: number of preserved relations and state space granularity. Both dimensions can take on different values and hence render structural similarity gradual. We further argue that decoupling is gradual in two ways. First, we show that different brain areas are involved in decoupled cognitive processes to a greater or lesser degree depending on the cause (internal or external) of their activity. Second, and more importantly, we show that the degree of decoupling can be further regulated in some brain areas through precision weighting of prediction error. We lastly argue that gradation of decoupling (via precision weighting) and gradation of structural similarity (via state space granularity) are conducive to behavioural success.

Altered regional homogeneity and cognitive impairments in first-episode schizophrenia: A resting-state fMRI study

BACKGROUND

Patients with schizophrenia consistently present pervasive cognitive deficits, but the neurobiological mechanism of cognitive impairments remains unclear. By analyzing regional homogeneity (ReHo) of resting-state functional Magnetic Resonance Imaging, this study aimed to explore the association between brain functional alterations and cognitive deficits in first-episode schizophrenia (FES) with a relatively large sample.

METHODS

A total of 187 patients with FES and 100 healthy controls from 3 independent cohorts underwent resting-state functional magnetic resonance scans. The MATRICS Consensus Cognitive Battery (MCCB) was used to assess cognitive function. Partial correlation analysis was performed between abnormal ReHo values and the severity of symptoms and cognitive deficits.

RESULTS

Compared with healthy controls, ReHo values increased in right superior frontal cortex and decreased in right anterior cingulate cortex (ACC), left middle occipital gyrus (MOG), left cuneus, right posterior cingulate cortex (PCC), and right superior occipital gyrus in schizophrenia patients. ReHo values in ACC, PCC and superior occipital gyrus were correlated with PANSS scores. In addition, ReHo values in ACC and MOG were negatively correlated with working memory; left cuneus was positively correlated with multiple cognitive domains (speed of processing, attention/vigilance and social cognition); PCC was positively correlated with verbal learning; right superior occipital gyrus was positively correlated with speed of processing and social cognition.

CONCLUSION

In conclusion, we found widespread ReHo alterations and cognitive dysfunction in FES. And the pathophysiology mechanism of a wide range of cognitive deficits may be related to abnormal spontaneous brain activity.

I overthink-Therefore I am not: An active inference account of altered sense of self and agency in depersonalisation disorder

This paper considers the phenomenology of depersonalisation disorder, in relation to predictive processing and its associated pathophysiology. To do this, we first establish a few mechanistic tenets of predictive processing that are necessary to talk about phenomenal transparency, mental action, and self as subject. We briefly review the important role of 'predicting precision' and how this affords mental action and the loss of phenomenal transparency. We then turn to sensory attenuation and the phenomenal consequences of (pathophysiological) failures to attenuate or modulate sensory precision. We then consider this failure in the context of depersonalisation disorder. The key idea here is that depersonalisation disorder reflects the remarkable capacity to explain perceptual engagement with the world via the hypothesis that "I am an embodied perceiver, but I am not in control of my perception". We suggest that individuals with depersonalisation may believe that 'another agent' is controlling their thoughts, perceptions or actions, while maintaining full insight that the 'other agent' is 'me' (the self). Finally, we rehearse the predictions of this formal analysis, with a special focus on the psychophysical and physiological abnormalities that may underwrite the phenomenology of depersonalisation.

Cannabinoids, reward processing, and psychosis

BACKGROUND

Evidence suggests that an overlap exists between the neurobiology of psychotic disorders and the effects of cannabinoids on neurocognitive and neurochemical substrates involved in reward processing.

AIMS

We investigate whether the psychotomimetic effects of delta-9-tetrahydrocannabinol (THC) and the antipsychotic potential of cannabidiol (CBD) are underpinned by their effects on the reward system and dopamine.

METHODS

This narrative review focuses on the overlap between altered dopamine signalling and reward processing induced by cannabinoids, pre-clinically and in humans. A systematic search was conducted of acute cannabinoid drug-challenge studies using neuroimaging in healthy subjects and those with psychosis RESULTS: There is evidence of increased striatal presynaptic dopamine synthesis and release in psychosis, as well as abnormal engagement of the striatum during reward processing. Although, acute THC challenges have elicited a modest effect on striatal dopamine, cannabis users generally indicate impaired presynaptic dopaminergic function. Functional MRI studies have identified that a single dose of THC may modulate regions involved in reward and salience processing such as the striatum, midbrain, insular, and anterior cingulate, with some effects correlating with the severity of THC-induced psychotic symptoms. CBD may modulate brain regions involved in reward/salience processing in an opposite direction to that of THC.

CONCLUSIONS

There is evidence to suggest modulation of reward processing and its neural substrates by THC and CBD. Whether such effects underlie the psychotomimetic/antipsychotic effects of these cannabinoids remains unclear. Future research should address these unanswered questions to understand the relationship between endocannabinoid dysfunction, reward processing abnormalities, and psychosis.

Spared performance but increased uncertainty in schizophrenia: Evidence from a probabilistic decision-making task

Aberrant attribution of salience to in fact little informative events might explain the emergence of positive symptoms in schizophrenia and has been linked to belief uncertainty. Uncertainty is thought to be encoded by neuromodulators, including norepinephrine. However, norepinephrinergic encoding of uncertainty, measured as task-related pupil dilation, has rarely been explored in schizophrenia. Here, we addressed this question by comparing individuals with a disorder from the schizophrenia spectrum to a non-psychiatric control group on behavioral and pupillometric measures in a probabilistic prediction task, where different levels of uncertainty were introduced. Behaviorally, patients performed similar to controls, but their belief uncertainty was higher, particularly when instability of the task environment was high, suggesting an increased sensitivity to this instability. Furthermore, while pupil dilation scaled positively with uncertainty, this was less the case for patients, suggesting aberrant neuromodulatory regulation of neural gain, which may hinder the reduction of uncertainty in the long run. Together, the findings point to abnormal uncertainty processing and norepinephrinergic signaling in schizophrenia, potentially informing future development of both psychopharmacological therapies and psychotherapeutic approaches that deal with the processing of uncertain information.

Schizophrenia Genomics: Convergence on Synaptic Development, Adult Synaptic Plasticity, or Both?

Large-scale genomic studies of schizophrenia have identified hundreds of genetic loci conferring risk to the disorder. This progress offers an important route toward defining the biological basis of the condition and potentially developing new treatments. In this review, we discuss insights from recent genome-wide association study, copy number variant, and exome sequencing analyses of schizophrenia, together with functional genomics data from the pre- and postnatal brain, in relation to synaptic development and function. These data provide strong support for the view that synaptic dysfunction within glutamatergic and GABAergic (gamma-aminobutyric acidergic) neurons of the cerebral cortex, hippocampus, and other limbic structures is a central component of schizophrenia pathophysiology. Implicated genes and functional genomic data suggest that disturbances in synaptic connectivity associated with susceptibility to schizophrenia begin in utero but continue throughout development, with some alleles conferring risk to the disorder through direct effects on synaptic function in adulthood. This model implies that novel interventions for schizophrenia could include broad preventive approaches aimed at enhancing synaptic health during development as well as more targeted treatments aimed at correcting synaptic function in affected adults.

Seeing a Bayesian ghost: Sensorimotor activation leads to an illusory social perception

Based on our prior experiences we form social expectations and anticipate another person’s response. Under certain conditions, these expectations can be so strong that they lead to illusory perception of another person who is actually not there (i.e., seeing a Bayesian ghost). We used EEG to investigate the neural correlates of such illusory social perception. Our results showed that activation of the premotor cortex predicted the occurrence of the Bayesian ghost, whereas its actual appearance was later accompanied by activation in sensorimotor and adjacent parietal regions. These findings confirm that our perception of others is so strongly affected by prior expectations, in such a way they can prompt illusory social perceptions associated with activity change in brain regions relevant for action perception. They also contribute to a better understanding of social interaction in healthy individuals as well as persons with mental illnesses, which can be characterized by illusory perception and social interaction difficulties.

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Expecting a response to a social action can lead to an illusion of another person

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The brain does not merely respond to social signals but anticipates social behavior

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Sensorimotor activity indicates top-down predictions that outweigh sensory input

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Illusory social perception is associated with sensorimotor and parietal activity

Enhanced Instructed Fear Learning in Delusion-Proneness

Psychosis is associated with distorted perceptions and deficient bottom-up learning such as classical fear conditioning. This has been interpreted as reflecting imprecise priors in low-level predictive coding systems. Paradoxically, overly strong beliefs, such as overvalued beliefs and delusions, are also present in psychosis-associated states. In line with this, research has suggested that patients with psychosis and associated phenotypes rely more on high-order priors to interpret perceptual input. In this behavioural and fMRI study we studied two types of fear learning, i.e., instructed fear learning mediated by verbal suggestions about fear contingencies and classical fear conditioning mediated by low level associative learning, in delusion proneness-a trait in healthy individuals linked to psychotic disorders. Subjects were shown four faces out of which two were coupled with an aversive stimulation (CS+) while two were not (CS-) in a fear conditioning procedure. Before the conditioning, subjects were informed about the contingencies for two of the faces of each type, while no information was given for the two other faces. We could thereby study the effect of both classical fear conditioning and instructed fear learning. Our main outcome variable was evaluative rating of the faces. Simultaneously, fMRI-measurements were performed to study underlying mechanisms. We postulated that instructed fear learning, measured with evaluative ratings, is stronger in psychosis-related phenotypes, in contrast to classical fear conditioning that has repeatedly been shown to be weaker in these groups. In line with our hypothesis, we observed significantly larger instructed fear learning on a behavioural level in delusion-prone individuals (n = 20) compared to non-delusion-prone subjects (n = 23; n = 20 in fMRI study). Instructed fear learning was associated with a bilateral activation of lateral orbitofrontal cortex that did not differ significantly between groups. However, delusion-prone subjects showed a stronger functional connectivity between right lateral orbitofrontal cortex and regions processing fear and pain. Our results suggest that psychosis-related states are associated with a strong instructed fear learning in addition to previously reported weak classical fear conditioning. Given the similarity between nocebo paradigms and instructed fear learning, our results also have an impact on understanding why nocebo effects differ between individuals.

Two Means Together? Effects of Response Bias and Sensitivity on Communicative Action Detection

Numerous lines of research suggest that communicative dyadic actions elicit preferential processing and more accurate detection compared to similar but individual actions. However, it is unclear whether the presence of the second agent provides additional cues that allow for more accurate discriminability between communicative and individual intentions or whether it lowers the threshold for perceiving third-party encounters as interactive. We performed a series of studies comparing the recognition of communicative actions from single and dyadic displays in healthy individuals. A decreased response threshold for communicative actions was observed for dyadic vs. single-agent animations across all three studies, providing evidence for the dyadic communicative bias. Furthermore, consistent with the facilitated recognition hypothesis, congruent response to a communicative gesture increased the ability to accurately interpret the actions. In line with dual-process theory, we propose that both mechanisms may be perceived as complementary rather than competitive and affect different stages of stimuli processing.

The shallow cognitive map hypothesis: A hippocampal framework for thought disorder in schizophrenia

Memories are not formed in isolation. They are associated and organized into relational knowledge structures that allow coherent thought. Failure to express such coherent thought is a key hallmark of Schizophrenia. Here we explore the hypothesis that thought disorder arises from disorganized Hippocampal cognitive maps. In doing so, we combine insights from two key lines of investigation, one concerning the neural signatures of cognitive mapping, and another that seeks to understand lower-level cellular mechanisms of cognition within a dynamical systems framework. Specifically, we propose that multiple distinct pathological pathways converge on the shallowing of Hippocampal attractors, giving rise to disorganized Hippocampal cognitive maps and driving conceptual disorganization. We discuss the available evidence at the computational, behavioural, network, and cellular levels. We also outline testable predictions from this framework, including how it could unify major chemical and psychological theories of schizophrenia and how it can provide a rationale for understanding the aetiology and treatment of the disease.

From hallucinations to synaesthesia: A circular inference account of unimodal and multimodal erroneous percepts in clinical and drug-induced psychosis

Psychedelics distort perception and induce visual and multimodal hallucinations as well as synaesthesia. This is in contradiction with the high prevalence of distressing voices in schizophrenia. Here we introduce a unifying account of unimodal and multimodal erroneous percepts based on circular inference. We show that amplification of top-down predictions (descending loops) leads to an excessive reliance on priors and aberrant levels of integration of the sensory representations, resulting in crossmodal percepts and stronger illusions. By contrast, amplification of bottom-up information (ascending loops) results in overinterpretation of unreliable sensory inputs and high levels of segregation between sensory modalities, bringing about unimodal hallucinations and reduced vulnerability to illusions. We delineate a canonical microcircuit in which layer-specific inhibition controls the propagation of information across hierarchical levels: inhibitory interneurons in the deep layers exert control over priors, removing descending loops. Conversely, inhibition in the supragranular layers counterbalances the effects of the ascending loops. Overall, we put forward a multiscale and transnosographic account of erroneous percepts with important theoretical, conceptual and clinical implications.

A neurobiological perspective on social influence: Serotonin and social adaptation

Humans are inherently social beings. Being suggestible to each other's expectations enables pro-social skills that are crucial for social learning and adaptation. Despite its high relevance for psychiatry, the neurobiological mechanisms underlying social adaptation are still not well understood. This review therefore provides a conceptual framework covering various distinct mechanisms underlying social adaptation and explores the neuropharmacology - in particular the role of the serotonin (5-HT) system - modulating these mechanisms. This article therefore reviews empirical results on social influence processing and reconciles them with recent findings from psychedelic research on social processing to elucidate neurobiological and neuropharmacological underpinnings of social adaptation. Various computational, neurobiological, and neurochemical processes are involved in distinct mechanisms underlying social adaptation such as the multisensory process of social information integration that is crucial for the forming of self-representation and representations of social norms. This is again associated with self- and other-perception during social interactions as well as value-based decision making that guides our behaviour in daily interactions. We highlight the critical role of 5-HT in these processes and suggest that 5-HT can facilitate social learning and may represent an important target for treating psychiatric disorders characterized by impairments in social functioning. This framework also has important implications for psychedelic-assisted therapy as well as for the development of novel treatment approaches and future research directions.

Symptom Structure in Schizophrenia: Implications of Latent Variable Modeling vs Network Analysis

The structure of schizophrenia symptoms has a substantial impact on the development of pharmacological and psychosocial interventions. Typically, reflective latent variable models (eg, confirmatory factor analysis) or formative latent variable models (eg, principal component analysis) have been used to examine the structure of schizophrenia symptoms. More recently, network analysis is appearing as a method to examine symptom structure. However, latent variable modeling and network analysis results can lead to different inferences about the nature of symptoms. Given the critical role of correctly identifying symptom structure in schizophrenia treatment and research, we present an introduction to latent variable modeling and network analysis, along with their distinctions and implications for examining the structure of schizophrenia symptoms. We also provide a simulation demonstration highlighting the statistical equivalence between these models and the subsequent importance of an a priori rationale that should help guide model selection.

Atypical meta-memory evaluation strategy in schizophrenia patients

BACKGROUND

Previous research has reported that patients with schizophrenia would regard false memories with higher confidence, and this meta-memory deficit was suggested as a neurocognitive marker of schizophrenia. However, how schizophrenia patients determine their memory decision confidence has received scant consideration. This study, therefore, aimed to characterize the extent to which meta-memory evaluation strategy differs between schizophrenia patients and healthy individuals, and how such difference contributes to the patients' meta-memory performance.

METHODS

27 schizophrenia patients and 28 matched healthy controls performed a temporal-order judgement (TOJ) task, in which they judged which movie frame occurred earlier in an encoded video, and then made retrospective confidence rating. Mixed effect regression models were performed to assess the between-group metacognitive evaluation strategy difference and its relationship to clinical symptoms.

RESULTS

Compared to the control group, the patients' confidence ratings were correlated more with the recent confidence history and less with the TOJ-related evidence. The degree of dependence on recent history of confidence was negatively correlated with the severity of positive symptoms. Furthermore, by controlling for the first-order TOJ performance, we observed that the patients discriminated correct memory decisions from the incorrect ones as accurately as the controls.

CONCLUSION

The present investigation revealed that schizophrenia patients tend to use more heuristics in making meta-memory evaluations, and such atypical strategy is related to their clinical symptoms. This study provides new insights into how schizophrenia patients perform meta-memory processes. Future research could consider examining such metacognitive deficits in light of other cognitive domains in psychosis.

Thinking about hallucinations: why philosophy matters

Introduction: Hallucinations research is increasingly incorporating philosophy or the work of philosophically trained individuals. We present three different ways in which this is successfully implemented to the enhancement of knowledge and understanding of hallucinations and related phenomena.Method: We review contributions from phenomenology, philosophy of cognitive science, and philosophy of science and psychiatry.Results: We demonstrate that these areas of philosophy make significant contributions to hallucinations research. Phenomenology gives us a sophisticated and critical understanding of the lived experience of hallucinations. Philosophy of cognitive science enables big-picture theorising and synthesis of ideas, as well as a critical engagement with new paradigms. Philosophy of science and psychiatry raises valuable and theoretically informed questions about diagnosis and categorisation.Conclusions: These contributions reflect both the methodological variety within philosophy and its relevance to the hallucinations researcher.

Parsing neural circuits of fear learning and extinction across basic and clinical neuroscience: Towards better translation

Over the past decades, studies of fear learning and extinction have advanced our understanding of the neurobiology of threat and safety learning. Animal studies can provide mechanistic/causal insights into human brain regions and their functional connectivity involved in fear learning and extinction. Findings in humans, conversely, may further enrich our understanding of neural circuits in animals by providing macroscopic insights at the level of brain-wide networks. Nevertheless, there is still much room for improvement in translation between basic and clinical research on fear learning and extinction. Through the lens of neural circuits, in this article, we aim to review the current knowledge of fear learning and extinction in both animals and humans, and to propose strategies to fill in the current knowledge gap for the purpose of enhancing clinical benefits.

Agency Deficits in a Human Genetic Model of Schizophrenia: Insights From 22q11DS Patients

Schizophrenia is a chronic and disabling mental illness characterized by a disordered sense of self. Current theories suggest that deficiencies in the sense of control over one's actions (Sense of Agency, SoA) may underlie some of the symptoms of schizophrenia. However, it is not clear if agency deficits are a precursor or a result of psychosis. Here, we investigated full body agency using virtual reality in a cohort of 22q11 deletion syndrome participants with a genetic propensity for schizophrenia. In two experiments employing virtual reality, full body motion tracking, and online feedback, we investigated SoA in two separate domains. Our results show that participants with 22q11DS had a considerable deficit in monitoring their actions, compared to age-matched controls in both the temporal and spatial domain. This was coupled with a bias toward erroneous attribution of actions to the self. These results indicate that nonpsychotic 22q11DS participants have a domain general deficit in the conscious sensorimotor mechanisms underlying the bodily self. Our data reveal an abnormality in the SoA in a cohort with a genetic predisposition for schizophrenia, but without psychosis, providing evidence that deficits in delineation of the self may be a precursor rather than a result of the psychotic state.

AI ethics in computational psychiatry: From the neuroscience of consciousness to the ethics of consciousness

Methods used in artificial intelligence (AI) overlap with methods used in computational psychiatry (CP). Hence, considerations from AI ethics are also relevant to ethical discussions of CP. Ethical issues include, among others, fairness and data ownership and protection. Apart from this, morally relevant issues also include potential transformative effects of applications of AI-for instance, with respect to how we conceive of autonomy and privacy. Similarly, successful applications of CP may have transformative effects on how we categorise and classify mental disorders and mental health. Since many mental disorders go along with disturbed conscious experiences, it is desirable that successful applications of CP improve our understanding of disorders involving disruptions in conscious experience. Here, we discuss prospects and pitfalls of transformative effects that CP may have on our understanding of mental disorders. In particular, we examine the concern that even successful applications of CP may fail to take all aspects of disordered conscious experiences into account.

Factors governing the assignment of visual consequence to the corresponding action

To achieve fast feedback control of voluntary movements, the visual consequences of our motor commands need to be quickly identified and analyzed by the motor control processes in the brain. These processes work remarkably well even in complex visual environments and in the face of discrepancies between physical actuator and visually perceived effect, e.g. when moving a computer mouse on a visually crowded screen. Here we use an ambiguous situation in which a single cursor could be controlled by either the left or the right hand to determine the visual and cognitive factors that determine the assignment of a visual stimulus to the corresponding motor command. Our results demonstrate that the visuomotor system is exquisitely sensitive to the spatio-temporal correlation between cursor and hands, learning the appropriate mapping implicitly within several minutes. In contrast, spatial proximity between end effector and visual consequence has an immediate but only transient effect on the assignment process. Finally, an explicit instruction about which hand controls the cursor only has a minor influence when the instruction is presented first. These findings provide insight into the relative importance of the factors that determine the binding of visual information to the corresponding motor structures to enable fast feedback control.

Evidence From Imaging Resilience Genetics for a Protective Mechanism Against Schizophrenia in the Ventral Visual Pathway

INTRODUCTION

Illuminating neurobiological mechanisms underlying the protective effect of recently discovered common genetic resilience variants for schizophrenia is crucial for more effective prevention efforts. Current models implicate adaptive neuroplastic changes in the visual system and their pro-cognitive effects as a schizophrenia resilience mechanism. We investigated whether common genetic resilience variants might affect brain structure in similar neural circuits.

METHOD

Using structural magnetic resonance imaging, we measured the impact of an established schizophrenia polygenic resilience score (PRSResilience) on cortical volume, thickness, and surface area in 101 healthy subjects and in a replication sample of 33 224 healthy subjects (UK Biobank).

FINDING

We observed a significant positive whole-brain correlation between PRSResilience and cortical volume in the right fusiform gyrus (FFG) (r = 0.35; P = .0004). Post-hoc analyses in this cluster revealed an impact of PRSResilience on cortical surface area. The replication sample showed a positive correlation between PRSResilience and global cortical volume and surface area in the left FFG.

CONCLUSION

Our findings represent the first evidence of a neurobiological correlate of a genetic resilience factor for schizophrenia. They support the view that schizophrenia resilience emerges from strengthening neural circuits in the ventral visual pathway and an increased capacity for the disambiguation of social and nonsocial visual information. This may aid psychosocial functioning, ameliorate the detrimental effects of subtle perceptual and cognitive disturbances in at-risk individuals, and facilitate coping with the cognitive and psychosocial consequences of stressors. Our results thus provide a novel link between visual cognition, the vulnerability-stress concept, and schizophrenia resilience models.

Perceptual reality monitoring: Neural mechanisms dissociating imagination from reality

There is increasing evidence that imagination relies on similar neural mechanisms as externally triggered perception. This overlap presents a challenge for perceptual reality monitoring: deciding what is real and what is imagined. Here, we explore how perceptual reality monitoring might be implemented in the brain. We first describe sensory and cognitive factors that could dissociate imagery and perception and conclude that no single factor unambiguously signals whether an experience is internally or externally generated. We suggest that reality monitoring is implemented by higher-level cortical circuits that evaluate first-order sensory and cognitive factors to determine the source of sensory signals. According to this interpretation, perceptual reality monitoring shares core computations with metacognition. This multi-level architecture might explain several types of source confusion as well as dissociations between simply knowing whether something is real and actually experiencing it as real. We discuss avenues for future research to further our understanding of perceptual reality monitoring, an endeavour that has important implications for our understanding of clinical symptoms as well as general cognitive function.

Susceptibility to auditory hallucinations is associated with spontaneous but not directed modulation of top-down expectations for speech

Auditory verbal hallucinations (AVHs)-or hearing voices-occur in clinical and non-clinical populations, but their mechanisms remain unclear. Predictive processing models of psychosis have proposed that hallucinations arise from an over-weighting of prior expectations in perception. It is unknown, however, whether this reflects (i) a sensitivity to explicit modulation of prior knowledge or (ii) a pre-existing tendency to spontaneously use such knowledge in ambiguous contexts. Four experiments were conducted to examine this question in healthy participants listening to ambiguous speech stimuli. In experiments 1a (n = 60) and 1b (n = 60), participants discriminated intelligible and unintelligible sine-wave speech before and after exposure to the original language templates (i.e. a modulation of expectation). No relationship was observed between top-down modulation and two common measures of hallucination-proneness. Experiment 2 (n = 99) confirmed this pattern with a different stimulus-sine-vocoded speech (SVS)-that was designed to minimize ceiling effects in discrimination and more closely model previous top-down effects reported in psychosis. In Experiment 3 (n = 134), participants were exposed to SVS without prior knowledge that it contained speech (i.e. naïve listening). AVH-proneness significantly predicted both pre-exposure identification of speech and successful recall for words hidden in SVS, indicating that participants could actually decode the hidden signal spontaneously. Altogether, these findings support a pre-existing tendency to spontaneously draw upon prior knowledge in healthy people prone to AVH, rather than a sensitivity to temporary modulations of expectation. We propose a model of clinical and non-clinical hallucinations, across auditory and visual modalities, with testable predictions for future research.

Association Between Failures in Perceptual Updating and the Severity of Psychosis in Schizophrenia

IMPORTANCE

Recent accounts suggest that delusions and hallucinations may result from alterations in how prior knowledge is integrated with new information, but experimental evidence supporting this idea has been complex and inconsistent. Evidence from a simpler perceptual task would make clear whether psychotic symptoms are associated with overreliance on prior information and impaired updating.

OBJECTIVE

To investigate whether individuals with schizophrenia or schizoaffective disorder (PSZ) and healthy control individuals (HCs) differ in the ability to update their beliefs based on evidence in a relatively simple perceptual paradigm.

DESIGN, SETTING, AND PARTICIPANTS

This case-control study included individuals who met DSM-IV criteria for PSZ and matched HC participants in 2 independent samples. The PSZ group was recruited from the Maryland Psychiatric Research Center, Yale University, and community clinics, and the HC group was recruited from the community. To test perceptual updating, a random dot kinematogram paradigm was implemented in which dots moving coherently in a single direction were mixed with randomly moving dots. On 50% of trials, the direction of coherent motion changed by 90° midway through the trial. Participants were asked to report the direction perceived at the end of the trial. The Peters Delusions Inventory and Brief Psychiatric Rating Scale (BPRS) were used to quantify the severity of positive symptoms. Data were collected from September 2018 to March 2020 and were analyzed from approximately March 2020 to March 2021.

MAIN OUTCOMES AND MEASURES

Critical measures included the proportion of responses centered around the initial direction vs the subsequent changed direction and the overall precision of motion perception and reaction times.

RESULTS

A total of 48 participants were included in the PSZ group (31 [65%] male; mean [SD] age, 36.56 [9.76] years) and 36 in the HC group (22 [61%] male; mean [SD] age, 35.67 [10.74] years) in the original sample. An independent replication sample included 42 participants in the PSZ group (29 [69%] male; mean [SD] age, 33.98 [11.03] years) and 34 in the HC group (20 [59%] male; mean [SD] age, 34.29 [10.44] years). In line with previous research, patients with PSZ were less precise and had slower reaction times overall. The key finding was that patients with PSZ were significantly more likely (original sample: mean, 27.88 [95% CI, 24.19-31.57]; replication sample: mean, 26.70 [95% CI, 23.53-29.87]) than HC participants (original sample: mean, 18.86 [95% CI, 16.56-21.16]; replication sample: mean, 15.67 [95% CI, 12.61-18.73]) to report the initial motion direction rather than the final one. Moreover, the tendency to report the direction of initial motion correlated with the degree of conviction on the Peters Delusions Inventory (original sample: r = 0.32 [P = .05]; replication sample: r = 0.30 [P = .05]) and the Brief Psychiatric Rating Scale Reality Distortion score (original sample: r = 0.55 [P = .001]; replication sample: r = 0.35 [P = .03]) and severity of hallucinations (original sample: r = 0.39 [P = .02]; replication sample: r = 0.30 [P = .05]).

CONCLUSIONS AND RELEVANCE

The findings of this case-control study suggest that the severity of psychotic symptoms is associated with a tendency to overweight initial information over incoming sensory evidence. These results are consistent with predictive coding accounts of the origins of positive symptoms and suggest that deficits in very elementary perceptual updating may be a critical mechanism in psychosis.

Schizophrenia

Schizophrenia, characterised by psychotic symptoms and in many cases social and occupational decline, remains an aetiological and therapeutic challenge. Contrary to popular belief, the disorder is modestly more common in men than in women. Nor is the outcome uniformly poor. A division of symptoms into positive, negative, and disorganisation syndromes is supported by factor analysis. Catatonic symptoms are not specific to schizophrenia and so-called first rank symptoms are no longer considered diagnostically important. Cognitive impairment is now recognised as a further clinical feature of the disorder. Lateral ventricular enlargement and brain volume reductions of around 2% are established findings. Brain functional changes occur in different subregions of the frontal cortex and might ultimately be understandable in terms of disturbed interaction among large-scale brain networks. Neurochemical disturbance, involving dopamine function and glutamatergic N-methyl-D-aspartate receptor function, is supported by indirect and direct evidence. The genetic contribution to schizophrenia is now recognised to be largely polygenic. Birth and early life factors also have an important aetiological role. The mainstay of treatment remains dopamine receptor-blocking drugs; a psychological intervention, cognitive behavioural therapy, has relatively small effects on symptoms. The idea that schizophrenia is better regarded as the extreme end of a continuum of psychotic symptoms is currently influential. Other areas of debate include cannabis and childhood adversity as causative factors, whether there is progressive brain change after onset, and the long-term success of early intervention initiatives.

Reward Processing as an Indicator of Vulnerability or Compensatory Resilience in Psychoses? Results From a Twin Study

Background

Findings of reward disturbances in unaffected relatives of patients with schizophrenia suggest reward disturbances as an endophenotype for schizophrenia. Twin studies, where 1 twin has been diagnosed with a schizophrenia spectrum disorder, can further explore this.

Methods

We used Danish registries to identify twin pairs with at least 1 twin having a schizophrenia spectrum disorder diagnosis and control twin pairs matched on age, sex, and zygosity. The analyses included data from 34 unaffected co-twins (16 females), 42 probands with schizophrenia spectrum disorder (17 females), and 83 control twins (42 females). Participants performed a modified incentive delay task during functional magnetic resonance imaging. Whole-brain group differences were analyzed by performing comparisons between co-twins and control twins. Correlations with cognitive flexibility were tested.

Results

Compared with control twins, co-twins showed no differences in striatal regions, but increased signal in the dorsolateral prefrontal cortex (DLPFC) during missed target contrast was observed. In co-twins, increased DLPFC signal was associated with lower intra-extra dimensional set-shifting scores indicative of higher cognitive flexibility.

Conclusions

Unaffected co-twins did not have decreased striatal activity during anticipation as previously reported for patients with schizophrenia. Instead, they showed increased activity in the DLPFC during evaluation of missed target contrast, which correlated with their level of cognitive flexibility. Unaffected co-twins had no diagnosis at a mean age of 40 years. This could indicate that greater cognitive flexibility and increased activity in the right DLPFC during processing of unexpected negative outcome represents a compensatory resilience mechanism in predisposed twins.

Judgments of agency are affected by sensory noise without recruiting metacognitive processing

Acting in the world is accompanied by a sense of agency, or experience of control over our actions and their outcomes. As humans, we can report on this experience through judgments of agency. These judgments often occur under noisy conditions. We examined the computations underlying judgments of agency, in particular under the influence of sensory noise. Building on previous literature, we studied whether judgments of agency incorporate uncertainty in the same way that confidence judgments do, which would imply that the former share computational mechanisms with metacognitive judgments. In two tasks, participants rated agency, or confidence in a decision about their agency, over a virtual hand that tracked their movements, either synchronously or with a delay and either under high or low noise. We compared the predictions of two computational models to participants' ratings and found that agency ratings, unlike confidence, were best explained by a model involving no estimates of sensory noise. We propose that agency judgments reflect first-order measures of the internal signal, without involving metacognitive computations, challenging the assumed link between the two cognitive processes.

State anxiety alters the neural oscillatory correlates of predictions and prediction errors during reward-based learning

Anxiety influences how the brain estimates and responds to uncertainty. The consequences of these processes on behaviour have been described in theoretical and empirical studies, yet the associated neural correlates remain unclear. Rhythm-based accounts of Bayesian predictive coding propose that predictions in generative models of perception are represented in alpha (8-12 Hz) and beta oscillations (13-30 Hz). Updates to predictions are driven by prediction errors weighted by precision (inverse variance) encoded in gamma oscillations (>30 Hz) and associated with the suppression of beta activity. We tested whether state anxiety alters the neural oscillatory activity associated with predictions and precision-weighted prediction errors (pwPE) during learning. Healthy human participants performed a probabilistic reward-based learning task in a volatile environment. In our previous work, we described learning behaviour in this task using a hierarchical Bayesian model, revealing more precise (biased) beliefs about the tendency of the reward contingency in state anxiety, consistent with reduced learning in this group. The model provided trajectories of predictions and pwPEs for the current study, allowing us to assess their parametric effects on the time-frequency representations of EEG data. Using convolution modelling for oscillatory responses, we found that, relative to a control group, state anxiety increased beta activity in frontal and sensorimotor regions during processing of pwPE, and in fronto-parietal regions during encoding of predictions. No effects of state anxiety on gamma modulation were found. Our findings expand prior evidence on the oscillatory representations of predictions and pwPEs into the reward-based learning domain. The results suggest that state anxiety modulates beta-band oscillatory correlates of pwPE and predictions in generative models, providing insights into the neural processes associated with biased belief updating and poorer learning.

Resistance to Extinction of Evaluative Fear Conditioning in Delusion Proneness

Delusional beliefs consist of strong priors characterized by resistance to change even when evidence supporting another view is overwhelming. Such bias against disconfirmatory evidence (BADE) has been experimentally demonstrated in patients with psychosis as well as in delusion proneness. In this fMRI-study, we tested for similar resistance to change and associated brain processes in extinction of fear learning, involving a well-described mechanism dependent of evidence updating. A social fear conditioning paradigm was used in which four faces had either been coupled to an unconditioned aversive stimulus (CS+) or not (CS-). For two of the faces, instructions had been given about the fear contingencies (iCS+/iCS-) while for two other faces no such instructions had been given (niCS+/niCS-). Interaction analysis suggested that individuals who score high on delusion-proneness (hDP; n = 20) displayed less extinction of evaluative fear compared to those with low delusion proneness (lDP; n = 23; n = 19 in fMRI-analysis) for non-instructed faces (F = 5.469, P = .024). The resistance to extinction was supported by a difference in extinction related activity between the two groups in medial prefrontal cortex and its connectivity with amygdala, as well as in a cortical network supporting fear processing. For instructed faces no extinction was noted, but there was a larger evaluative fear (F = 5.048, P = 0.03) and an increased functional connectivity between lateral orbitofrontal cortex and fear processing regions for hDP than lDP. Our study links previous explored BADE-effects in delusion associated phenotypes to fear extinction, and suggest that effects of instructions on evaluative fear learning are more pronounced in delusion prone subjects.

Models of Dynamic Belief Updating in Psychosis-A Review Across Different Computational Approaches

To understand the dysfunctional mechanisms underlying maladaptive reasoning of psychosis, computational models of decision making have widely been applied over the past decade. Thereby, a particular focus has been on the degree to which beliefs are updated based on new evidence, expressed by the learning rate in computational models. Higher order beliefs about the stability of the environment can determine the attribution of meaningfulness to events that deviate from existing beliefs by interpreting these either as noise or as true systematic changes (volatility). Both, the inappropriate downplaying of important changes as noise (belief update too low) as well as the overly flexible adaptation to random events (belief update too high) were theoretically and empirically linked to symptoms of psychosis. Whereas models with fixed learning rates fail to adjust learning in reaction to dynamic changes, increasingly complex learning models have been adopted in samples with clinical and subclinical psychosis lately. These ranged from advanced reinforcement learning models, over fully Bayesian belief updating models to approximations of fully Bayesian models with hierarchical learning or change point detection algorithms. It remains difficult to draw comparisons across findings of learning alterations in psychosis modeled by different approaches e.g., the Hierarchical Gaussian Filter and change point detection. Therefore, this review aims to summarize and compare computational definitions and findings of dynamic belief updating without perceptual ambiguity in (sub)clinical psychosis across these different mathematical approaches. There was strong heterogeneity in tasks and samples. Overall, individuals with schizophrenia and delusion-proneness showed lower behavioral performance linked to failed differentiation between uninformative noise and environmental change. This was indicated by increased belief updating and an overestimation of volatility, which was associated with cognitive deficits. Correlational evidence for computational mechanisms and positive symptoms is still sparse and might diverge from the group finding of instable beliefs. Based on the reviewed studies, we highlight some aspects to be considered to advance the field with regard to task design, modeling approach, and inclusion of participants across the psychosis spectrum. Taken together, our review shows that computational psychiatry offers powerful tools to advance our mechanistic insights into the cognitive anatomy of psychotic experiences.

Linking Salience Signaling With Early Adversity and Affective Distress in Individuals at Clinical High Risk for Psychosis: Results From an Event-Related fMRI Study

Evidence suggests dysregulation of the salience network in individuals with psychosis, but few studies have examined the intersection of stress exposure and affective distress with prediction error (PE) signals among youth at clinical high-risk (CHR). Here, 26 individuals at CHR and 19 healthy volunteers (HVs) completed a monetary incentive delay task in conjunction with fMRI. We compared these groups on the amplitudes of neural responses to surprising outcomes-PEs without respect to their valence-across the whole brain and in two regions of interest, the anterior insula and amygdala. We then examined relations of these signals to the severity of depression, anxiety, and trauma histories in the CHR group. Relative to HV, youth at CHR presented with aberrant PE-evoked activation of the temporoparietal junction and weaker deactivation of the precentral gyrus, posterior insula, and associative striatum. No between-group differences were observed in the amygdala or anterior insula. Among youth at CHR, greater trauma histories were correlated with stronger PE-evoked amygdala activation. No associations were found between affective symptoms and the neural responses to PE. Our results suggest that unvalenced PE signals may provide unique information about the neurobiology of CHR syndromes and that early adversity exposure may contribute to neurobiological heterogeneity in this group. Longitudinal studies of young people with a range of risk syndromes are needed to further disentangle the contributions of distinct aspects of salience signaling to the development of psychopathology.

A computational lens on menopause-associated psychosis

Psychotic episodes are debilitating disease states that can cause extreme distress and impair functioning. There are sex differences that drive the onset of these episodes. One difference is that, in addition to a risk period in adolescence and early adulthood, women approaching the menopause transition experience a second period of risk for new-onset psychosis. One leading hypothesis explaining this menopause-associated psychosis (MAP) is that estrogen decline in menopause removes a protective factor against processes that contribute to psychotic symptoms. However, the neural mechanisms connecting estrogen decline to these symptoms are still not well understood. Using the tools of computational psychiatry, links have been proposed between symptom presentation and potential algorithmic and biological correlates. These models connect changes in signaling with symptom formation by evaluating changes in information processing that are not easily observable (latent states). In this manuscript, we contextualize the observed effects of estrogen (decline) on neural pathways implicated in psychosis. We then propose how estrogen could drive changes in latent states giving rise to cognitive and psychotic symptoms associated with psychosis. Using computational frameworks to inform research in MAP may provide a systematic method for identifying patient-specific pathways driving symptoms and simultaneously refine models describing the pathogenesis of psychosis across all age groups.

Delusional Perception Revisited

Delusional perception designates a sudden, idiosyncratic, and often self-referential delusion triggered by a neutral perceptual content. In classical psychopathology, delusional perception was considered almost pathognomonic for schizophrenia. Since delusional perception has been erased from ICD-11 and always been absent in DSM, it risks slipping out of clinical awareness. In this article, we explore the clinical roots of delusional perception, elucidate the psychopathological phenomenon, and discuss its two predominant conceptualizations, i.e., Schneider's well-known two-link model and Matussek's lesser known one-link model. The two-link model posits that delusional perception amounts to an abnormal interpretation of an intact perception, whereas the one-link model posits that the delusional meaning is contained within a changed perception. Despite their differences, both models stress that delusional perception is a primary delusion that takes place within an altered experiential framework that is characteristic of the psychopathological Gestalt of schizophrenia. We discuss the role of delusional perception in future psychopathological and diagnostic assessment and argue that such assessments must be conducted in comprehensive manner, eliciting the psychopathological context within which symptoms and signs are embedded. Finally, we discuss the compatibility of the two models of delusional perception with contemporary cognitive models on delusion and cognitive psychotherapeutic approaches.

The Predictive Dynamics of Happiness and Well-Being

We offer an account of mental health and well-being using the predictive processing framework (PPF). According to this framework, the difference between mental health and psychopathology can be located in the goodness of the predictive model as a regulator of action. What is crucial for avoiding the rigid patterns of thinking, feeling and acting associated with psychopathology is the regulation of action based on the valence of affective states. In PPF, valence is modelled as error dynamics—the change in prediction errors over time . Our aim in this paper is to show how error dynamics can account for both momentary happiness and longer term well-being. What will emerge is a new neurocomputational framework for making sense of human flourishing.

Robotically-induced hallucination triggers subtle changes in brain network transitions

The perception that someone is nearby, although nobody can be seen or heard, is called presence hallucination (PH). Being a frequent hallucination in patients with Parkinson's disease, it has been argued to be indicative of a more severe and rapidly advancing form of the disease, associated with psychosis and cognitive decline. PH may also occur in healthy individuals and has recently been experimentally induced, in a controlled manner during fMRI, using MR-compatible robotics and sensorimotor stimulation. Previous neuroimaging correlates of such robot-induced PH, based on conventional time-averaged fMRI analysis, identified altered activity in the posterior superior temporal sulcus and inferior frontal gyrus in healthy individuals. However, no link with the strength of the robot-induced PH was observed, and such activations were also associated with other sensations induced by robotic stimulation. Here we leverage recent advances in dynamic functional connectivity, which have been applied to different psychiatric conditions, to decompose fMRI data during PH-induction into a set of co-activation patterns that are tracked over time, as to characterize their occupancies, durations, and transitions. Our results reveal that, when PH is induced, the identified brain patterns significantly and selectively increase their transition probabilities towards a specific brain pattern, centred on the posterior superior temporal sulcus, angular gyrus, dorso-lateral prefrontal cortex, and middle prefrontal cortex. This change is not observed in any other control conditions, nor is it observed in association with other sensations induced by robotic stimulation. The present findings describe the neural mechanisms of PH in healthy individuals and identify a specific disruption of the dynamics of network interactions, extending previously reported network dysfunctions in psychotic patients with hallucinations to an induced robot-controlled specific hallucination in healthy individuals.

Active inference leads to Bayesian neurophysiology

The neuronal substrates that implement the free-energy principle and ensuing active inference at the neuron and synapse level have not been fully elucidated. This Review considers possible neuronal substrates underlying the principle. First, the foundations of the free-energy principle are introduced, and then its ability to empirically explain various brain functions and psychological and biological phenomena in terms of Bayesian inference is described. Mathematically, the dynamics of neural activity and plasticity that minimise a cost function can be cast as performing Bayesian inference that minimises variational free energy. This equivalence licenses the adoption of the free-energy principle as a universal characterisation of neural networks. Further, the neural network structure itself represents a generative model under which an agent operates. A virtue of this perspective is that it enables the formal association of neural network properties with prior beliefs that regulate inference and learning. The possible neuronal substrates that implement prior beliefs and how to empirically examine the theory are discussed. This perspective renders brain activity explainable, leading to a deeper understanding of the neuronal mechanisms underlying basic psychology and psychiatric disorders in terms of an implicit generative model.

Progress in sensorimotor neuroscience of schizophrenia spectrum disorders: Lessons learned and future directions

The number of neuroimaging studies on movement disorders, sensorimotor, and psychomotor functioning in schizophrenia spectrum disorders (SSD) has steadily increased over the last two decades. Accelerated by the addition of the "sensorimotor domain" to the Research Domain Criteria (RDoC) framework in January 2019, neuroscience research on the role of sensorimotor dysfunction in SSD has gained greater scientific and clinical relevance. To draw attention to recent rapid progress in the field, we performed a triennial systematic review (PubMed search from January 1st^, 2018 through December 31st^, 2020), in which we highlight recent neuroimaging findings and discuss methodological pitfalls as well as challenges for future research. The identified magnetic resonance imaging (MRI) studies suggest that sensorimotor abnormalities in SSD are related to cerebello-thalamo-cortico-cerebellar network dysfunction. Longitudinal and interventional studies highlight the translational potential of the sensorimotor domain as putative biomarkers for treatment response and as targets for non-invasive neurostimulation techniques in SSD.