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

Aberrant Hierarchical Prediction Errors Are Associated With Transition to Psychosis: A Computational Single-Trial Analysis of the Mismatch Negativity

BACKGROUND

Mismatch negativity reductions are among the most reliable biomarkers for schizophrenia and have been associated with increased risk for conversion to psychosis in individuals who are at clinical high risk for psychosis (CHR-P). Here, we adopted a computational approach to develop a mechanistic model of mismatch negativity reductions in CHR-P individuals and patients early in the course of schizophrenia.

METHODS

Electroencephalography was recorded in 38 CHR-P individuals (15 converters), 19 patients early in the course of schizophrenia (≤5 years), and 44 healthy control participants during three different auditory oddball mismatch negativity paradigms including 10% duration, frequency, or double deviants, respectively. We modeled sensory learning with the hierarchical Gaussian filter and extracted precision-weighted prediction error trajectories from the model to assess how the expression of hierarchical prediction errors modulated electroencephalography amplitudes over sensor space and time.

RESULTS

Both low-level sensory and high-level volatility precision-weighted prediction errors were altered in CHR-P individuals and patients early in the course of schizophrenia compared with healthy control participants. Moreover, low-level precision-weighted prediction errors were significantly different in CHR-P individuals who later converted to psychosis compared with nonconverters.

CONCLUSIONS

Our results implicate altered processing of hierarchical prediction errors as a computational mechanism in early psychosis consistent with predictive coding accounts of psychosis. This computational model seems to capture pathophysiological mechanisms that are relevant to early psychosis and the risk for future psychosis in CHR-P individuals and may serve as predictive biomarkers and mechanistic targets for the development of novel treatments.

The bodily self from psychosis to psychedelics

The sense of self is a foundational element of neurotypical human consciousness. We normally experience the world as embodied agents, with the unified sensation of our selfhood being nested in our body. Critically, the sense of self can be altered in psychiatric conditions such as psychosis and altered states of consciousness induced by psychedelic compounds. The similarity of phenomenological effects across psychosis and psychedelic experiences has given rise to the "psychotomimetic" theory suggesting that psychedelics simulate psychosis-like states. Moreover, psychedelic-induced changes in the sense of self have been related to reported improvements in mental health. Here we investigated the bodily self in psychedelic, psychiatric, and control populations. Using the Moving Rubber Hand Illusion, we tested (N = 75) patients with psychosis, participants with a history of substantial psychedelic experiences, and control participants to see how psychedelic and psychiatric experience impacts the bodily self. Results revealed that psychosis patients had reduced Body Ownership and Sense of Agency during volitional action. The psychedelic group reported subjective long-lasting changes to the sense of self, but no differences between control and psychedelic participants were found. Our results suggest that while psychedelics induce both acute and enduring subjective changes in the sense of self, these are not manifested at the level of the bodily self. Furthermore, our data show that bodily self-processing, related to volitional action, is disrupted in psychosis patients. We discuss these findings in relation to anomalous self-processing across psychedelic and psychotic experiences.

Sensory processing in humans and mice fluctuates between external and internal modes

Perception is known to cycle through periods of enhanced and reduced sensitivity to external information. Here, we asked whether such slow fluctuations arise as a noise-related epiphenomenon of limited processing capacity or, alternatively, represent a structured mechanism of perceptual inference. Using 2 large-scale datasets, we found that humans and mice alternate between externally and internally oriented modes of sensory analysis. During external mode, perception aligns more closely with the external sensory information, whereas internal mode is characterized by enhanced biases toward perceptual history. Computational modeling indicated that dynamic changes in mode are enabled by 2 interlinked factors: (i) the integration of subsequent inputs over time and (ii) slow antiphase oscillations in the impact of external sensory information versus internal predictions that are provided by perceptual history. We propose that between-mode fluctuations generate unambiguous error signals that enable optimal inference in volatile environments.

Introspective inference counteracts perceptual distortion

Introspective agents can recognize the extent to which their internal perceptual experiences deviate from the actual states of the external world. This ability, also known as insight, is critically required for reality testing and is impaired in psychosis, yet little is known about its cognitive underpinnings. We develop a Bayesian modeling framework and a psychophysics paradigm to quantitatively characterize this type of insight while people experience a motion after-effect illusion. People can incorporate knowledge about the illusion into their decisions when judging the actual direction of a motion stimulus, compensating for the illusion (and often overcompensating). Furthermore, confidence, reaction-time, and pupil-dilation data all show signatures consistent with inferential adjustments in the Bayesian insight model. Our results suggest that people can question the veracity of what they see by making insightful inferences that incorporate introspective knowledge about internal distortions.

Resolving the Delusion Paradox

BACKGROUND AND HYPOTHESIS

The neurocomputational framework of predictive processing (PP) provides a promising approach to explaining delusions, a key symptom of psychotic disorders. According to PP, the brain makes inferences about the world by weighing prior beliefs against the available sensory data. Mismatches between prior beliefs and sensory data result in prediction errors that may update the brain's model of the world. Psychosis has been associated with reduced weighting of priors relative to the sensory data. However, delusional beliefs are highly resistant to change, suggesting increased rather than decreased weighting of priors. We propose that this "delusion paradox" can be resolved within a hierarchical PP model: Reduced weighting of prior beliefs at low hierarchical levels may be compensated by an increased influence of higher-order beliefs represented at high hierarchical levels, including delusional beliefs. This may sculpt perceptual processing into conformity with delusions and foster their resistance to contradictory evidence.

STUDY DESIGN

We review several lines of experimental evidence on low- and high-level processes, and their neurocognitive underpinnings in delusion-related phenotypes and link them to predicted processing.

STUDY RESULTS

The reviewed evidence supports the notion of decreased weighting of low-level priors and increased weighting of high-level priors, in both delusional and delusion-prone individuals. Moreover, we highlight the role of prefrontal cortex as a neural basis for the increased weighting of high-level prior beliefs and discuss possible clinical implications of the proposed hierarchical predictive-processing model.

CONCLUSIONS

Our review suggests the delusion paradox can be resolved within a hierarchical PP model.

Altered corollary discharge signaling in the auditory cortex of a mouse model of schizophrenia predisposition

The ability to distinguish sensations that are self-generated from those caused by external events is disrupted in schizophrenia patients. However, the neural circuit abnormalities underlying this sensory impairment and its relationship to the risk factors for the disease is not well understood. To address this, we examined the processing of self-generated sounds in male Df(16)A+/- mice, which model one of the largest genetic risk factors for schizophrenia, the 22q11.2 microdeletion. We find that auditory cortical neurons in Df(16)A+/- mice fail to attenuate their responses to self-generated sounds, recapitulating deficits seen in schizophrenia patients. Notably, the auditory cortex of Df(16)A+/- mice displayed weaker motor-related signals and received fewer inputs from the motor cortex, suggesting an anatomical basis underlying the sensory deficit. These results provide insights into the mechanisms by which a major genetic risk factor for schizophrenia disrupts the top-down processing of sensory information.

Bayesian accounts of perceptual decisions in the nonclinical continuum of psychosis: Greater imprecision in both top-down and bottom-up processes

Neurocomputational accounts of psychosis propose mechanisms for how information is integrated into a predictive model of the world, in attempts to understand the occurrence of altered perceptual experiences. Conflicting Bayesian theories postulate aberrations in either top-down or bottom-up processing. The top-down theory predicts an overreliance on prior beliefs or expectations resulting in aberrant perceptual experiences, whereas the bottom-up theory predicts an overreliance on current sensory information, as aberrant salience is directed towards objectively uninformative stimuli. This study empirically adjudicates between these models. We use a perceptual decision-making task in a neurotypical population with varying degrees of psychotic-like experiences. Bayesian modelling was used to compute individuals' reliance on prior relative to sensory information. Across two datasets (discovery dataset n = 363; independent replication in validation dataset n = 782) we showed that psychotic-like experiences were associated with an overweighting of sensory information relative to prior expectations, which seem to be driven by decreased precision afforded to prior information. However, when prior information was more uncertain, participants with greater psychotic-like experiences encoded sensory information with greater noise. Greater psychotic-like experiences were associated with aberrant precision in the encoding both prior and likelihood information, which we suggest may be related to generally heightened perceptions of task instability. Our study lends empirical support to notions of both weaker bottom-up and weaker (rather than stronger) top-down perceptual processes, as well as aberrancies in belief updating that extend into the non-clinical continuum of psychosis.

The effect of multisensory semantic congruency on unisensory object recognition in schizophrenia

Multisensory, as opposed to unisensory processing of stimuli, has been found to enhance the performance (e.g., reaction time, accuracy, and discrimination) of healthy individuals across various tasks. However, this enhancement is not as pronounced in patients with schizophrenia (SZ), indicating impaired multisensory integration (MSI) in these individuals. To the best of our knowledge, no study has yet investigated the impact of MSI deficits in the context of working memory, a domain highly reliant on multisensory processing and substantially impaired in schizophrenia. To address this research gap, we employed two adopted versions of the continuous object recognition task to investigate the effect of single-trail multisensory encoding on subsequent object recognition in 21 schizophrenia patients and 21 healthy controls (HC). Participants were tasked with discriminating between initial and repeated presentations. For the initial presentations, half of the stimuli were audiovisual pairings, while the other half were presented unimodal. The task-relevant stimuli were then presented a second time in a unisensory manner (either auditory stimuli in the auditory task or visual stimuli in the visual task). To explore the impact of semantic context on multisensory encoding, half of the audiovisual pairings were selected to be semantically congruent, while the remaining pairs were not semantically related to each other. Consistent with prior studies, our findings demonstrated that the impact of single-trial multisensory presentation during encoding remains discernible during subsequent object recognition. This influence could be distinguished based on the semantic congruity between the auditory and visual stimuli presented during the encoding. This effect was more robust in the auditory task. In the auditory task, when congruent multisensory pairings were encoded, both participant groups demonstrated a multisensory facilitation effect. This effect resulted in improved accuracy and RT performance. Regarding incongruent audiovisual encoding, as expected, HC did not demonstrate an evident multisensory facilitation effect on memory performance. In contrast, SZs exhibited an atypically accelerated reaction time during the subsequent auditory object recognition. Based on the predictive coding model we propose that this observed deviations indicate a reduced semantic modulatory effect and anomalous predictive errors signaling, particularly in the context of conflicting cross-modal sensory inputs in SZ.

An Introduction to Predictive Processing Models of Perception and Decision-Making

The predictive processing framework includes a broad set of ideas, which might be articulated and developed in a variety of ways, concerning how the brain may leverage predictive models when implementing perception, cognition, decision-making, and motor control. This article provides an up-to-date introduction to the two most influential theories within this framework: predictive coding and active inference. The first half of the paper (Sections 2-5) reviews the evolution of predictive coding, from early ideas about efficient coding in the visual system to a more general model encompassing perception, cognition, and motor control. The theory is characterized in terms of the claims it makes at Marr's computational, algorithmic, and implementation levels of description, and the conceptual and mathematical connections between predictive coding, Bayesian inference, and variational free energy (a quantity jointly evaluating model accuracy and complexity) are explored. The second half of the paper (Sections 6-8) turns to recent theories of active inference. Like predictive coding, active inference models assume that perceptual and learning processes minimize variational free energy as a means of approximating Bayesian inference in a biologically plausible manner. However, these models focus primarily on planning and decision-making processes that predictive coding models were not developed to address. Under active inference, an agent evaluates potential plans (action sequences) based on their expected free energy (a quantity that combines anticipated reward and information gain). The agent is assumed to represent the world as a partially observable Markov decision process with discrete time and discrete states. Current research applications of active inference models are described, including a range of simulation work, as well as studies fitting models to empirical data. The paper concludes by considering future research directions that will be important for further development of both models.

Local Search and the Evolution of World Models

An open question regarding how people develop their models of the world is how new candidates are generated for consideration out of infinitely many possibilities. We discuss the role that evolutionary mechanisms play in this process. Specifically, we argue that when it comes to developing a global world model, innovation is necessarily incremental, involving the generation and selection among random local mutations and recombinations of (parts of) one's current model. We argue that, by narrowing and guiding exploration, this feature of cognitive search is what allows human learners to discover better theories, without ever grappling directly with the problem of finding a "global optimum," or best possible world model. We suggest this aspect of cognitive processing works analogously to how blind variation and selection mechanisms drive biological evolution. We propose algorithms developed for program synthesis provide candidate mechanisms for how human minds might achieve this. We discuss objections and implications of this perspective, finally suggesting that a better process-level understanding of how humans incrementally explore compositional theory spaces can shed light on how we think, and provide explanatory traction on fundamental cognitive biases, including anchoring, probability matching, and confirmation bias.

Neural networks underlying visual illusions: An activation likelihood estimation meta-analysis

Visual illusions have long been used to study visual perception and contextual integration. Neuroimaging studies employ illusions to identify the brain regions involved in visual perception and how they interact. We conducted an Activation Likelihood Estimation (ALE) meta-analysis and meta-analytic connectivity modeling on fMRI studies using static and motion illusions to reveal the neural signatures of illusory processing and to investigate the degree to which different areas are commonly recruited in perceptual inference. The resulting networks encompass ventral and dorsal regions, including the inferior and middle occipital cortices bilaterally in both types of illusions. The static and motion illusion networks selectively included the right posterior parietal cortex and the ventral premotor cortex respectively. Overall, these results describe a network of areas crucially involved in perceptual inference relying on feed-back and feed-forward interactions between areas of the ventral and dorsal visual pathways. The same network is proposed to be involved in hallucinogenic symptoms characteristic of schizophrenia and other disorders, with crucial implications in the use of illusions as biomarkers.

The interpersonal computational psychiatry of social coordination in schizophrenia

Impairments in social coordination form a core dimension of various psychiatric disorders, including schizophrenia. Advances in interpersonal and computational psychiatry support a major change in studying social coordination in schizophrenia. Although these developments provided novel perspectives to study how interpersonal activities shape coordination and to examine computational mechanisms, direct attempts to integrate the two methodologies have been sparse. Here, we propose an interpersonal computational framework that (1) leverages the active inference framework to model aberrant social coordination processes in schizophrenia and (2) incorporates dynamical system models to dissect intrapersonal and interpersonal synchronisation to inform a statistical model based on active inference. We discuss how this interpersonal computational psychiatry framework can elucidate the aberrant processes leading to psychopathology, with schizophrenia as an example, and highlight how it might aid clinical intervention and practice. Finally, we discuss challenges and opportunities for using the framework in studying social coordination impairments.

Molecularly targetable cell types in mouse visual cortex have distinguishable prediction error responses

Predictive processing postulates the existence of prediction error neurons in cortex. Neurons with both negative and positive prediction error response properties have been identified in layer 2/3 of visual cortex, but whether they correspond to transcriptionally defined subpopulations is unclear. Here we used the activity-dependent, photoconvertible marker CaMPARI2 to tag neurons in layer 2/3 of mouse visual cortex during stimuli and behaviors designed to evoke prediction errors. We performed single-cell RNA-sequencing on these populations and found that previously annotated Adamts2 and Rrad layer 2/3 transcriptional cell types were enriched when photolabeling during stimuli that drive negative or positive prediction error responses, respectively. Finally, we validated these results functionally by designing artificial promoters for use in AAV vectors to express genetically encoded calcium indicators. Thus, transcriptionally distinct cell types in layer 2/3 that can be targeted using AAV vectors exhibit distinguishable negative and positive prediction error responses.

Experimental validation of the free-energy principle with in vitro neural networks

Empirical applications of the free-energy principle are not straightforward because they entail a commitment to a particular process theory, especially at the cellular and synaptic levels. Using a recently established reverse engineering technique, we confirm the quantitative predictions of the free-energy principle using in vitro networks of rat cortical neurons that perform causal inference. Upon receiving electrical stimuli-generated by mixing two hidden sources-neurons self-organised to selectively encode the two sources. Pharmacological up- and downregulation of network excitability disrupted the ensuing inference, consistent with changes in prior beliefs about hidden sources. As predicted, changes in effective synaptic connectivity reduced variational free energy, where the connection strengths encoded parameters of the generative model. In short, we show that variational free energy minimisation can quantitatively predict the self-organisation of neuronal networks, in terms of their responses and plasticity. These results demonstrate the applicability of the free-energy principle to in vitro neural networks and establish its predictive validity in this setting.

Visual Perception Is Highly Flexible and Context Dependent in Young Infants: A Case of Top-Down-Modulated Motion Perception

Top-down modulation is an essential cognitive component in human perception. Despite mounting evidence of top-down perceptual modulation in adults, it is largely unknown whether infants can engage in this cognitive function. Here, we examined top-down modulation of motion perception in 6- to 8-month-old infants (recruited in North America) via their smooth-pursuit eye movements. In four experiments, we demonstrated that infants' perception of motion direction can be flexibly shaped by briefly learned predictive cues when no coherent motion is available. The current findings present a novel insight into infant perception and its development: Infant perceptual systems respond to predictive signals engendered from higher-level learning systems, leading to a flexible and context-dependent modulation of perception. This work also suggests that the infant brain is sophisticated, interconnected, and active when placed in a context in which it can learn and predict.

Trust and psychosis: a systematic review and meta-analysis

BACKGROUND

Impaired trust in other humans is commonly seen in psychosis and it leads to poor societal functioning. However, examining trust behavior in an experimental setting is challenging. Investigators have used the trust game, a neuro-economic game to assess trust behavior in psychosis. However, the findings are inconsistent. Hence, we systematically reviewed the existing literature and conducted a meta-analysis to examine trust behavior in patients with psychosis, their relatives, and those at high risk for psychosis.

METHODS

We searched electronic databases for studies that have examined trust game in patients with psychosis, published up to November 2021. The primary outcome measure was the baseline trust in a trust game by patients and controls. The meta-analysis was performed if at least three data sets of control and patient groups were available for that measure/design. We conducted meta-analyses with a random-effects model. The results were described narratively wherever meta-analysis was not possible due to paucity of studies.

RESULTS

The searches across the databases including cross-references yielded 465 publications of which 10 studies were included in the final analysis. Baseline trust in the trust game was significantly lower in patients with psychosis compared to controls (SMD 0.39, 95% CI -0.14 to 0.64, p -0.002). However, a similar decrease in baseline trust was not present in relatives of patients (SMD 0.08, 95% CI -0.20 to 0.36, p -0.58).

CONCLUSIONS

The current meta-analysis suggests significant trust deficits in patients with psychosis. Future studies with a bigger sample size are required to understand the nature of trust deficits and factors affecting this impairment.

Integrative Brain Network and Salience Models of Psychopathology and Cognitive Dysfunction in Schizophrenia

Brain network models of cognitive control are central to advancing our understanding of psychopathology and cognitive dysfunction in schizophrenia. This review examines the role of large-scale brain organization in schizophrenia, with a particular focus on a triple-network model of cognitive control and its role in aberrant salience processing. First, we provide an overview of the triple network involving the salience, frontoparietal, and default mode networks and highlight the central role of the insula-anchored salience network in the aberrant mapping of salient external and internal events in schizophrenia. We summarize the extensive evidence that has emerged from structural, neurochemical, and functional brain imaging studies for aberrancies in these networks and their dynamic temporal interactions in schizophrenia. Next, we consider the hypothesis that atypical striatal dopamine release results in misattribution of salience to irrelevant external stimuli and self-referential mental events. We propose an integrated triple-network salience-based model incorporating striatal dysfunction and sensitivity to perceptual and cognitive prediction errors in the insula node of the salience network and postulate that dysregulated dopamine modulation of salience network-centered processes contributes to the core clinical phenotype of schizophrenia. Thus, a powerful paradigm to characterize the neurobiology of schizophrenia emerges when we combine conceptual models of salience with large-scale cognitive control networks in a unified manner. We conclude by discussing potential therapeutic leads on restoring brain network dysfunction in schizophrenia.

Touching and being touched: where knowing and feeling meet

Philosophers maintain that touch confers a sense of reality or grounding to perceptual experience. In touching oneself, one is simultaneously both subject and object of touch, a template for experiencing oneself as subject and object of intentions, feelings, and motivations, or intersubjectivity. Here, I explore a form of self-touch carefully documented by Winnicott in observing how the infant engages the transitional object. I compare the processes of self-loss in transitional states, including absorption in art, empathic immersion, drug-induced ego dissolution, and depersonalization. I use examples drawn from Rodin, Dante, and the Beatles; research correlating neurophysiological findings with aspects of self-representation; predictive processing-based models; Hohwy's concepts of minimal and narrative self; Clark's notion of the extended mind; and phenomenological perspectives on touch, to postulate a role for self-touch in the pre-reflective sense of mine-ness, or grounding, in transitional states.

Progressive trajectories of schizophrenia across symptoms, genes, and the brain

BACKGROUND

Schizophrenia is characterized by complex psychiatric symptoms and unclear pathological mechanisms. Most previous studies have focused on the morphological changes that occur over the development of the disease; however, the corresponding functional trajectories remain unclear. In the present study, we aimed to explore the progressive trajectories of patterns of dysfunction after diagnosis.

METHODS

Eighty-six patients with schizophrenia and 120 healthy controls were recruited as the discovery dataset. Based on multiple functional indicators of resting-state brain functional magnetic resonance imaging, we conducted a duration-sliding dynamic analysis framework to investigate trajectories in association with disease progression. Neuroimaging findings were associated with clinical symptoms and gene expression data from the Allen Human Brain Atlas database. A replication cohort of patients with schizophrenia from the University of California, Los Angeles, was used as the replication dataset for the validation analysis.

RESULTS

Five stage-specific phenotypes were identified. A symptom trajectory was characterized by positive-dominated, negative ascendant, negative-dominated, positive ascendant, and negative surpassed stages. Dysfunctional trajectories from primary and subcortical regions to higher-order cortices were recognized; these are associated with abnormal external sensory gating and a disrupted internal excitation-inhibition equilibrium. From stage 1 to stage 5, the importance of neuroimaging features associated with behaviors gradually shifted from primary to higher-order cortices and subcortical regions. Genetic enrichment analysis identified that neurodevelopmental and neurodegenerative factors may be relevant as schizophrenia progresses and highlighted multiple synaptic systems.

CONCLUSIONS

Our convergent results indicate that progressive symptoms and functional neuroimaging phenotypes are associated with genetic factors in schizophrenia. Furthermore, the identification of functional trajectories complements previous findings of structural abnormalities and provides potential targets for drug and non-drug interventions in different stages of schizophrenia.

The moderating effect of cognitive impairment on the relationship between inner speech and auditory verbal hallucinations among chronic patients with schizophrenia

BACKGROUND

Even though there is an increasing amount of evidence from behavioral and neuroimaging studies to suggest that pathological inner speech plays a role in the emergence of auditory verbal hallucinations (AVH), studies investigating the mechanisms underlying this relationship are rather scarce. Examining moderators might inform the development of new treatment options for AVH. We sought to extend the existing knowledge by testing the moderating role of cognitive impairment in the association between inner speech and hallucinations in a sample of Lebanese patients with schizophrenia.

METHODS

A cross-sectional study was conducted from May till August 2022, enrolling 189 chronic patients.

RESULTS

Moderation analysis revealed that, after controlling for delusions, the interaction of experiencing voices of other people in inner speech by cognitive performance was significantly associated with AVH. In people having low (Beta = 0.69; t = 5.048; p < .001) and moderate (Beta = 0.45; t = 4.096; p < .001) cognitive performance, the presence of voices of other people in inner speech was significantly associated with more hallucinations. This association was not significant in patients with high cognitive function (Beta = 0.21; t = 1.417; p = .158).

CONCLUSION

This preliminarily study suggests that interventions aiming at improving cognitive performance may also have a beneficial effect in reducing hallucinations in schizophrenia.

Visual illusions in young people reporting psychotic-like experiences

BACKGROUND AND OBJECTIVES

A disruption in the co-ordination of bottom-up and top-down processing is thought to underlie anomalous perceptual experiences in psychosis. Visual illusions represent a valuable methodology in exploring this disruption. Here, we examined visual illusions in a group of young people having psychotic-like experiences. We also examined the relationship between illusion susceptibility and appraisal of psychotic-like experiences as well as depression, anxiety and stress levels.

METHOD

25 young people reporting psychotic-like experiences and 53 healthy participants performed an adjustment task that measured susceptibility to a battery of 13 visual illusions. Levels of depression, anxiety and stress were quantified in both groups. The clinical group also completed measures examining frequency, appraisals and emotional responses to psychotic-like experiences.

RESULTS

A general increase of illusion susceptibility was found in the clinical group compared to the control group. However, when depression, anxiety and stress levels were controlled for, this difference disappeared. Stress turned out to be the best predictor of illusion susceptibility in the clinical group, whereas anomalous experiences, depression and anxiety were unrelated to overall illusion strength.

LIMITATIONS

This study is limited to young participants reporting significant mental health difficulties and psychotic-like experiences. Findings should be replicated in an Ultra High Risk (prodromal) group.

CONCLUSIONS

Increased levels of stress explained the enhanced vulnerability to illusions in the clinical group. This increased susceptibility suggests a perceptual style that relies too heavily on prior expectations at the expense of the true sensory evidence, potentially leading to an altered perceptual experience of the world.

A computational model for learning from repeated traumatic experiences under uncertainty

Traumatic events can lead to lifelong, inflexible adaptations in threat perception and behavior, which characterize posttraumatic stress disorder (PTSD). This process involves associations between sensory cues and internal states of threat and then generalization of the threat responses to previously neutral cues. However, most formulations neglect adaptations to threat that are not specific to those associations. To incorporate nonassociative responses to threat, we propose a computational theory of PTSD based on adaptation to the frequency of traumatic events by using a reinforcement learning momentum model. Recent threat prediction errors generate momentum that influences subsequent threat perception in novel contexts. This model fits primary data acquired from a mouse model of PTSD, in which unpredictable footshocks in one context accelerate threat learning in a novel context. The theory is consistent with epidemiological data that show that PTSD incidence increases with the number of traumatic events, as well as the disproportionate impact of early life trauma. Because the theory proposes that PTSD relates to the average of recent threat prediction errors rather than the strength of a specific association, it makes novel predictions for the treatment of PTSD.

Impaired perception of temporal contiguity between action and effect is associated with disorders of agency in schizophrenia

Delusions of control in schizophrenia are characterized by the striking feeling that one's actions are controlled by external forces. We here tested qualitative predictions inspired by Bayesian causal inference models, which suggest that such misattributions of agency should lead to decreased intentional binding. Intentional binding refers to the phenomenon that subjects perceive a compression of time between their intentional actions and consequent sensory events. We demonstrate that patients with delusions of control perceived less self-agency in our intentional binding task. This effect was accompanied by significant reductions of intentional binding as compared to healthy controls and patients without delusions. Furthermore, the strength of delusions of control tightly correlated with decreases in intentional binding. Our study validated a critical prediction of Bayesian accounts of intentional binding, namely that a pathological reduction of the prior likelihood of a causal relation between one's actions and consequent sensory events-here captured by delusions of control-should lead to lesser intentional binding. Moreover, our study highlights the import of an intact perception of temporal contiguity between actions and their effects for the sense of agency.

Computational mechanisms of belief updating in relation to psychotic-like experiences

Introduction

Psychotic-like experiences (PLEs) may occur due to changes in weighting prior beliefs and new evidence in the belief updating process. It is still unclear whether the acquisition or integration of stable beliefs is altered, and whether such alteration depends on the level of environmental and belief precision, which reflects the associated uncertainty. This motivated us to investigate uncertainty-related dynamics of belief updating in relation to PLEs using an online study design.

Methods

We selected a sample (n = 300) of participants who performed a belief updating task with sudden change points and provided self-report questionnaires for PLEs. The task required participants to observe bags dropping from a hidden helicopter, infer its position, and dynamically update their belief about the helicopter's position. Participants could optimize performance by adjusting learning rates according to inferred belief uncertainty (inverse prior precision) and the probability of environmental change points. We used a normative learning model to examine the relationship between adherence to specific model parameters and PLEs.

Results

PLEs were linked to lower accuracy in tracking the outcome (helicopter location) (β = 0.26 ± 0.11, p = 0.018) and to a smaller increase of belief precision across observations after a change point (β = -0.003 ± 0.0007, p < 0.001). PLEs were related to slower belief updating when participants encountered large prediction errors (β = -0.03 ± 0.009, p = 0.001). Computational modeling suggested that PLEs were associated with reduced overall belief updating in response to prediction errors (βPE = -1.00 ± 0.45, p = 0.028) and reduced modulation of updating at inferred environmental change points (βCPP = -0.84 ± 0.38, p = 0.023).

Discussion

We conclude that PLEs are associated with altered dynamics of belief updating. These findings support the idea that the process of balancing prior belief and new evidence, as a function of environmental uncertainty, is altered in PLEs, which may contribute to the development of delusions. Specifically, slower learning after large prediction errors in people with high PLEs may result in rigid beliefs. Disregarding environmental change points may limit the flexibility to establish new beliefs in the face of contradictory evidence. The present study fosters a deeper understanding of inferential belief updating mechanisms underlying PLEs.

Understanding visual hallucinations: a new synthesis

Despite decades of research, we do not definitively know how people sometimes see things that are not there. Eight models of complex visual hallucinations have been published since 2000, including Deafferentation, Reality Monitoring, Perception and Attention Deficit, Activation, Input, and Modulation, Hodological, Attentional Networks, Active inference, and Thalamocortical Dysrhythmia Default Mode Network Decoupling. Each was derived from different understandings of brain organisation. To reduce this variability, representatives from each research group agreed an integrated Visual Hallucination Framework that is consistent with current theories of veridical and hallucinatory vision. The Framework delineates cognitive systems relevant to hallucinations. It allows a systematic, consistent, investigation of relationships between the phenomenology of visual hallucinations and changes in underpinning cognitive structures. The episodic nature of hallucinations highlights separate factors associated with the onset, persistence, and end of specific hallucinations suggesting a complex relationship between state and trait markers of hallucination risk. In addition to a harmonised interpretation of existing evidence, the Framework highlights new avenues of research, and potentially, new approaches to treating distressing hallucinations.

[Mother brain: Bayesian theory of maternal interoception during pregnancy and postpartum]

The perinatal period, including pregnancy and postpartum, causes major morphological, endocrinal, and thermal transitions in women. As the fetus grows, abdominal muscle fibers stretch, internal organs such as the bladder or colon move, and the uterine anatomy changes. Many of these changes involve interoception, the perception of internal body signals such as muscle and visceral sensations. Despite the importance of these interoceptive signals, few studies have explored perinatal interoception. We propose an innovative theory of maternal interoception based on recent findings in neuroscience. We show that interoceptive signals processing during pregnancy is crucial for understanding perinatal phenomenology and psychopathology, such as maternal perception of fetal movements, maternal-infant bonding, denial of pregnancy, phantom fetal movements after childbirth, pseudocyesis or even puerperal delusion. Knowing the importance of these interoceptive mechanisms, clinicians in obstetrics, gynecology and mental health should be particularly vigilant to maternal interoception during the perinatal period.

Aberrant uncertainty processing is linked to psychotic-like experiences, autistic traits, and is reflected in pupil dilation during probabilistic learning

Aberrant belief updating due to misestimation of uncertainty and an increased perception of the world as volatile (i.e., unstable) has been found in autism and psychotic disorders. Pupil dilation tracks events that warrant belief updating, likely reflecting the adjustment of neural gain. However, whether subclinical autistic or psychotic symptoms affect this adjustment and how they relate to learning in volatile environments remains to be unraveled. We investigated the relationship between behavioral and pupillometric markers of subjective volatility (i.e., experience of the world as unstable), autistic traits, and psychotic-like experiences in 52 neurotypical adults with a probabilistic reversal learning task. Computational modeling revealed that participants with higher psychotic-like experience scores overestimated volatility in low-volatile task periods. This was not the case for participants scoring high on autistic-like traits, who instead showed a diminished adaptation of choice-switching behavior in response to risk. Pupillometric data indicated that individuals with higher autistic- or psychotic-like trait and experience scores differentiated less between events that warrant belief updating and those that do not when volatility was high. These findings are in line with misestimation of uncertainty accounts of psychosis and autism spectrum disorders and indicate that aberrancies are already present at the subclinical level.

Using dimensionality-reduction techniques to understand the organization of psychotic symptoms in persistent psychotic illness and first episode psychosis

Psychotic disorders are highly heterogeneous. Understanding relationships between symptoms will be relevant to their underlying pathophysiology. We apply dimensionality-reduction methods across two unique samples to characterize the patterns of symptom organization. We analyzed publicly-available data from 153 participants diagnosed with schizophrenia or schizoaffective disorder (fBIRN Data Repository and the Consortium for Neuropsychiatric Phenomics), as well as 636 first-episode psychosis (FEP) participants from the Prevention and Early Intervention Program for Psychosis (PEPP-Montreal). In all participants, the Scale for the Assessment of Positive Symptoms (SAPS) and Scale for the Assessment of Negative Symptoms (SANS) were collected. Multidimensional scaling (MDS) combined with cluster analysis was applied to SAPS and SANS scores across these two groups of participants. MDS revealed relationships between items of SAPS and SANS. Our application of cluster analysis to these results identified: 1 cluster of disorganization symptoms, 2 clusters of hallucinations/delusions, and 2 SANS clusters (asocial and apathy, speech and affect). Those reality distortion items which were furthest from auditory hallucinations had very weak to no relationship with hallucination severity. Despite being at an earlier stage of illness, symptoms in FEP presentations were similarly organized. While hallucinations and delusions commonly co-occur, we found that their specific themes and content sometimes travel together and sometimes do not. This has important implications, not only for treatment, but also for research-particularly efforts to understand the neurocomputational and pathophysiological mechanism underlying delusions and hallucinations.

Individual differences in computational psychiatry: a review of current challenges

Bringing precision to the understanding and treatment of mental disorders requires instruments for studying clinically relevant individual differences. One promising approach is the development of computational assays: integrating computational models with cognitive tasks to infer latent patient-specific disease processes in brain computations. While recent years have seen many methodological advancements in computational modelling and many cross-sectional patient studies, much less attention has been paid to basic psychometric properties (reliability and construct validity) of the computational measures provided by the assays. In this review, we assess the extent of this issue by examining emerging empirical evidence. We find that many computational measures suffer from poor psychometric properties, which poses a risk of invalidating previous findings and undermining ongoing research efforts using computational assays to study individual (and even group) differences. We provide recommendations for how to address these problems and, crucially, embed them within a broader perspective on key developments that are needed for translating computational assays to clinical practice.

Cross-Modality Evidence for Reduced Choice History Biases in Psychosis-Prone Individuals

OBJECTIVES

Predictive processing posits that perception emerges from inferential processes within a hierarchical cortical system. Alterations of these processes may result in psychotic experiences, such as hallucinations and delusions. Central to the predictive processing account of psychosis is the notion of aberrant weights attributed to prior information and sensory input. Based on the notion that previous perceptual choices represent a relevant source of prior information, we here asked whether the propensity towards psychotic experiences may be related to altered choice history biases in perceptual decision-making.

METHODS

We investigated the relationship between choice history biases in perceptual decision-making and psychosis proneness in the general population. Choice history biases and their adaptation to experimentally induced changes in stimulus serial dependencies were investigated in decision-making tasks with auditory (experiment 1) and visual (experiment 2) stimuli. We further explored a potential compensatory mechanism for reduced choice history biases by reliance on predictive cross-modal cues.

RESULTS

In line with our preregistered hypothesis, psychosis proneness was associated with decreased choice history biases in both experiments. This association is generalized across conditions with and without stimulus serial dependencies. We did not find consistent evidence for a compensatory reliance on cue information in psychosis-prone individuals across experiments.

CONCLUSIONS

Our results show reduced choice history biases in psychosis proneness. A compensatory mechanism between implicit choice history effects and explicit cue information is not supported unequivocally by our data.

Maladaptive explore/exploit trade-offs in schizophrenia

Schizophrenia is a complex disorder that remains poorly understood, particularly at the systems level. In this opinion article we argue that the explore/exploit trade-off concept provides a holistic and ecologically valid framework to resolve some of the apparent paradoxes that have emerged within schizophrenia research. We review recent evidence suggesting that fundamental explore/exploit behaviors may be maladaptive in schizophrenia during physical, visual, and cognitive foraging. We also describe how theories from the broader optimal foraging literature, such as the marginal value theorem (MVT), could provide valuable insight into how aberrant processing of reward, context, and cost/effort evaluations interact to produce maladaptive responses.

Associations among psychosis, mood, anxiety, and posttraumatic stress symptoms: A network analysis

The associations among psychotic experiences (i.e., hallucinations and delusions), trauma exposure, and posttraumatic stress symptoms are complex and multidirectional. Using network analysis to understand how psychotic experiences and symptoms of posttraumatic stress disorder (PTSD) relate to one another may identify new interventional targets to treat comorbidity and its underlying pathological processes. This study aimed to use network analysis to examine the associations among psychotic experiences; negative symptoms of psychosis; and symptoms of PTSD, anxiety, and depression. In this population-based cohort study, 4,472 participants (36.7% male) were assessed for psychotic experiences, negative symptoms of psychosis, PTSD, anxiety, and depression at age 23 (M = 23.86 years, SD = 0.520) or 24 years (M = 24.03, SD = 0.848). Associations among symptoms were assessed via network analysis. Exploratory graph analysis identified three clusters of densely connected symptoms within the overall network: psychotic experiences; PTSD symptoms; and depressive and anxiety symptoms and negative symptoms of psychosis. Psychotic experiences had the strongest associations with other symptoms in the network, and symptoms of anxiety played a key role in bridging psychotic experiences, symptoms of PTSD, and depressive symptoms. Consistent with the stress reactivity and affective models for psychotic experiences, the results suggest that symptoms of anxiety and emotional distress (e.g., hyperarousal, panic) may have a key role in the development and maintenance of psychotic experiences and symptoms of PTSD. Targeting these symptoms may ameliorate symptom burden transdiagnostically.

Reward disturbances in antipsychotic-naïve patients with first-episode psychosis and their association to glutamate levels

BACKGROUND

Aberrant anticipation of motivational salient events and processing of outcome evaluation in striatal and prefrontal regions have been suggested to underlie psychosis. Altered glutamate levels have likewise been linked to schizophrenia. Glutamatergic abnormalities may affect the processing of motivational salience and outcome evaluation. It remains unresolved, whether glutamatergic dysfunction is associated with the coding of motivational salience and outcome evaluation in antipsychotic-naïve patients with first-episode psychosis.

METHODS

Fifty-one antipsychotic-naïve patients with first-episode psychosis (22 ± 5.2 years, female/male: 31/20) and 52 healthy controls (HC) matched on age, sex, and parental education underwent functional magnetic resonance imaging and magnetic resonance spectroscopy (3T) in one session. Brain responses to motivational salience and negative outcome evaluation (NOE) were examined using a monetary incentive delay task. Glutamate levels were estimated in the left thalamus and anterior cingulate cortex using LCModel.

RESULTS

Patients displayed a positive signal change to NOE in the caudate (p = 0.001) and dorsolateral prefrontal cortex (DLPFC; p = 0.003) compared to HC. No group difference was observed in motivational salience or in levels of glutamate. There was a different association between NOE signal in the caudate and DLPFC and thalamic glutamate levels in patients and HC due to a negative correlation in patients (caudate: p = 0.004, DLPFC: p = 0.005) that was not seen in HC.

CONCLUSIONS

Our findings confirm prior findings of abnormal outcome evaluation as a part of the pathophysiology of schizophrenia. The results also suggest a possible link between thalamic glutamate and NOE signaling in patients with first-episode psychosis.

Sense of agency predicts severity of moral judgments

Sense of Agency (SoA) refers to the awareness of being the agent of our own actions. A key feature of SoA relies on the perceived temporal compression between our own actions and their sensory consequences, a phenomenon known as "Intentional Binding." Prior studies have linked SoA to the sense of responsibility for our own actions. However, it is unclear whether SoA predicts the way we judge the actions of others - including judgments of morally wrong actions like harming others. To address this issue, we ran an on-line pilot experiment where participants underwent two different tasks designed to tap into SoA and moral cognition. SoA was measured using the Intentional Binding task which allowed us to obtain both implicit (Intentional Binding) and explicit (Agency Rating) measures of SoA. Moral cognition was assessed by asking the same participants to evaluate videoclips where an agent could deliberately or inadvertently cause suffering to a victim (Intentional vs. Accidental Harm) compared with Neutral scenarios. Results showed a significant relation between both implicit and explicit measures of SoA and moral evaluation of the Accidental Harm scenarios, with stronger SoA predicting stricter moral judgments. These findings suggest that our capacity to feel in control of our actions predicts the way we judge others' actions, with stronger feelings of responsibility over our own actions predicting the severity of our moral evaluations of other actions. This was particularly true in ambiguous scenarios characterized by an incongruency between an apparently innocent intention and a negative action outcome.

Aberrant memory and delusional ideation: A pernicious partnership?

Delusions can be conceptualized as beliefs that are both at odds with consensus reality and espoused with high conviction. While delusions represent a cardinal symptom of schizophrenia, delusion-like beliefs can be found in the general population. Do similar cognitive mechanisms support delusionality across this spectrum? If so, what are they? Here, we examine evidence for a mechanistic role of the (associative) memory system in the formation and maintenance of delusions and delusion-like beliefs. While general neurocognitive metrics do not tend to associate with delusionality, our scoping review of the clinical and subclinical literature reveals several subdomains of memory function that do. These include a propensity to commit errors of commission (i.e., false alarms and intrusions), source memory biases, and metamemory impairment. We discuss how several of these effects may stem from aberrant associative memory function and offer recommendations for future research. Further, we propose a state/trait interaction model in which underlying traits (i.e., impaired associative and metamemory function) may become coupled with delusionality during states of acute psychosis, when memory function is particularly challenged by aberrant salience attribution and noisy perceptual input. According to this model, delusions may arise as explanations to high-salience (but low-source) mnemonic content that is endorsed with high confidence.

Bayes' Theorem in Neurocritical Care: Principles and Practice

Patients with critical neurological illness are diverse. As a result of the heterogeneity of this patient population, standardized approaches to patient management might not confer benefit. A precision medicine approach to neurocritical care is therefore urgently needed to improve our understanding of neurocritical illness and the care provided to this vulnerable cohort. Research designs and approaches based on Bayesian models have the potential to meet this need, as they are specifically designed to evolve with emerging evidence. This adaptability provides a benefit over the popular frequentist statistical approach, as it provides a way of adjusting hypotheses and trial procedures to maximize efficacy. This review summarizes the current state of knowledge on Bayes' theorem, and its potential applications to the field of neurocritical care. We review the basic principles underlying Bayes' theorem, compare the use of Bayesian versus frequentist statistics in medicine, and discuss the relevance of Bayesian statistics to the field of neuroscience and to clinical research. Finally, we explore the potential benefits of employing Bayesian methods within the field of neurocritical care as a steppingstone toward implementing precision medicine approaches to improve patient outcomes for complex, heterogeneous disorders.

Perceptual Functioning

Perceptual disorders are not part of the diagnosis criteria for schizophrenia. Yet, a considerable amount of work has been conducted, especially on visual perception abnormalities, and there is little doubt that visual perception is altered in patients. There are several reasons why such perturbations are of interest in this pathology. They are observed during the prodromal phase of psychosis, they are related to the pathophysiology (clinical disorganization, disorders of the sense of self), and they are associated with neuronal connectivity disorders. Perturbations occur at different levels of processing and likely affect how patients interact and adapt to their surroundings. The literature has become very large, and here we try to summarize different models that have guided the exploration of perception in patients. We also illustrate several lines of research by showing how perception has been investigated and by discussing the interpretation of the results. In addition to discussing domains such as contrast sensitivity, masking, and visual grouping, we develop more recent fields like processing at the level of the retina, and the timing of perception.

Memory-Based Prediction Deficits and Dorsolateral Prefrontal Dysfunction in Schizophrenia

BACKGROUND

Theories suggest that people with schizophrenia (SZ) have problems generating predictions based on past experiences. The dorsolateral prefrontal cortex (DLPFC) and hippocampus participate in memory-based prediction. We used functional magnetic resonance imaging to investigate DLPFC and hippocampal function in healthy control (HC) subjects and people with SZ during memory-based prediction.

METHODS

Prior to scanning, HC subjects (n = 54) and people with SZ (n = 31) learned 5-object sequences presented in fixed or random orders on each repetition. During scanning, participants made semantic decisions (e.g., "Can this object fit in a shoebox?") on a continuous stream of objects from fixed and random sequences. Sequence prediction was demonstrated by faster semantic decisions for objects in fixed versus random sequences because memory could be used to anticipate and more efficiently process semantic information about upcoming objects in fixed sequences. Representational similarity analyses were used to determine how each sequence type was represented in the posterior hippocampus and DLPFC.

RESULTS

Sequence predictions were reduced in individuals with SZ relative to HC subjects. Representational similarity analyses revealed stronger memory-based predictions in the DLPFC of HC subjects than people with SZ, and DLPFC representations correlated with more successful predictions in HC subjects only. For the posterior hippocampus, voxel pattern similarity was increased for fixed versus random sequences in HC subjects only, but no significant between-group differences or correlations with prediction success were observed.

CONCLUSIONS

Individuals with SZ are capable of learning temporal sequences; however, they are impaired using memory to predict upcoming events as efficiently as HC subjects. This deficit appears related to disrupted neural representation of sequence information in the DLPFC.

Disrupted auditory N1, theta power and coherence suppression to willed speech in people with schizophrenia

The phenomenon of sensory self-suppression - also known as sensory attenuation - occurs when a person generates a perceptible stimulus (such as a sound) by performing an action (such as speaking). The sensorimotor control system is thought to actively predict and then suppress the vocal sound in the course of speaking, resulting in lowered cortical responsiveness when speaking than when passively listening to an identical sound. It has been hypothesized that auditory hallucinations in schizophrenia result from a reduction in self-suppression due to a disruption of predictive mechanisms required to anticipate and suppress a specific, self-generated sound. It has further been hypothesized that this suppression is evident primarily in theta band activity. Fifty-one people, half of whom had a diagnosis of schizophrenia, were asked to repeatedly utter a single syllable, which was played back to them concurrently over headphones while EEG was continuously recorded. In other conditions, recordings of the same spoken syllables were played back to participants while they passively listened, or were played back with their onsets preceded by a visual cue. All participants experienced these conditions with their voice artificially shifted in pitch and also with their unaltered voice. Suppression was measured using event-related potentials (N1 component), theta phase coherence and power. We found that suppression was generally reduced on all metrics in the patient sample, and when voice alteration was applied. We additionally observed reduced theta coherence and power in the patient sample across all conditions. Visual cueing affected theta coherence only. In aggregate, the results suggest that sensory self-suppression of theta power and coherence is disrupted in schizophrenia.

A seven-year longitudinal study of the association between neurocognitive function and basic self-disorders in schizophrenia

Introduction

Basic self-disorders (SDs) and neurocognitive impairments are fundamental trait-like aspects of schizophrenia spectrum disorders. There has been little research on the association between SDs and neurocognitive impairments in schizophrenia, and no longitudinal studies have investigated if they are related. The aim of this study was to investigate the association between SDs and neurocognitive function in a follow-up study of patients with schizophrenia.

Methods

SDs and neurocognition were examined in 35 patients with schizophrenia during their first treatment and 7 years later (mean 7.1, SD 0.42). SDs were examined with the Examination of Anomalous Self-Experience (EASE) instrument. The neurocognitive examination included assessments of psychomotor speed, executive- and memory functions.

Results

Poorer executive functions at baseline were significantly associated with more SDs 7 years later and smaller reductions in SDs over time. There were no significant associations between other neurocognitive functions and SDs.

Discussion

Executive functions are important for self-regulation, and impairments in these functions in everyday life may have an impact on the development and/or persistence of SDs.

A unified model of ketamine's dissociative and psychedelic properties

Ketamine is an N-methyl-d-aspartate antagonist which is increasingly being researched and used as a treatment for depression. In low doses, it can cause a transitory modification in consciousness which was classically labelled as 'dissociation'. However, ketamine is also commonly classified as an atypical psychedelic and it has been recently reported that ego dissolution experiences during ketamine administration are associated with greater antidepressant response. Neuroimaging studies have highlighted several similarities between the effects of ketamine and those of serotonergic psychedelics in the brain; however, no unified account has been proposed for ketamine's multi-level effects - from molecular to network and psychological levels. Here, we propose that the fast, albeit transient, antidepressant effects observed after ketamine infusions are mainly driven by its acute modulation of reward circuits and sub-acute increase in neuroplasticity, while its dissociative and psychedelic properties are driven by dose- and context-dependent disruption of large-scale functional networks. Computationally, as nodes of the salience network (SN) represent high-level priors about the body ('minimal' self) and nodes of the default-mode network (DMN) represent the highest-level priors about narrative self-experience ('biographical' self), we propose that transitory SN desegregation and disintegration accounts for ketamine's 'dissociative' state, while transitory DMN desegregation and disintegration accounts for ketamine's 'psychedelic' state. In psychedelic-assisted psychotherapy, a relaxation of the highest-level beliefs with psychotherapeutic support may allow a revision of pathological self-representation models, for which neuroplasticity plays a permissive role. Our account provides a multi-level rationale for using the psychedelic properties of ketamine to increase its long-term benefits.

Computational psychiatry: from synapses to sentience

This review considers computational psychiatry from a particular viewpoint: namely, a commitment to explaining psychopathology in terms of pathophysiology. It rests on the notion of a generative model as underwriting (i) sentient processing in the brain, and (ii) the scientific process in psychiatry. The story starts with a view of the brain-from cognitive and computational neuroscience-as an organ of inference and prediction. This offers a formal description of neuronal message passing, distributed processing and belief propagation in neuronal networks; and how certain kinds of dysconnection lead to aberrant belief updating and false inference. The dysconnections in question can be read as a pernicious synaptopathy that fits comfortably with formal notions of how we-or our brains-encode uncertainty or its complement, precision. It then considers how the ensuing process theories are tested empirically, with an emphasis on the computational modelling of neuronal circuits and synaptic gain control that mediates attentional set, active inference, learning and planning. The opportunities afforded by this sort of modelling are considered in light of in silico experiments; namely, computational neuropsychology, computational phenotyping and the promises of a computational nosology for psychiatry. The resulting survey of computational approaches is not scholarly or exhaustive. Rather, its aim is to review a theoretical narrative that is emerging across subdisciplines within psychiatry and empirical scales of investigation. These range from epilepsy research to neurodegenerative disorders; from post-traumatic stress disorder to the management of chronic pain, from schizophrenia to functional medical symptoms.

Antipsychotics-induced improvement of cool executive function in individuals living with schizophrenia

Cool executive dysfunction is a crucial feature in people living with schizophrenia which is related to cognition impairment and the severity of the clinical symptoms. Based on electroencephalogram (EEG), our current study explored the change of brain network under the cool executive tasks in individuals living with schizophrenia before and after atypical antipsychotic treatment (before_TR vs. after_TR). 21 patients with schizophrenia and 24 healthy controls completed the cool executive tasks, involving the Tower of Hanoi Task (THT) and Trail-Marking Test A-B (TMT A-B). The results of this study uncovered that the reaction time of the after_TR group was much shorter than that of the before_TR group in the TMT-A and TMT-B. And the after_TR group showed fewer error numbers in the TMT-B than those of the before_TR group. Concerning the functional network, stronger DMN-like linkages were found in the before_TR group compared to the control group. Finally, we adopted a multiple linear regression model based on the change network properties to predict the patient's PANSS change ratio. Together, the findings deepened our understanding of cool executive function in individuals living with schizophrenia and might provide physiological information to reliably predict the clinical efficacy of schizophrenia after atypical antipsychotic treatment.

Probing top-down information in neocortical layer 1

Accurate perception of the environment is a constructive process that requires integration of external bottom-up sensory signals with internally generated top-down information. Decades of work have elucidated how sensory neocortex processes physical stimulus features. By contrast, examining how top-down information is encoded and integrated with bottom-up signals has been challenging using traditional neuroscience methods. Recent technological advances in functional imaging of brain-wide afferents in behaving mice have enabled the direct measurement of top-down information. Here, we review the emerging literature on encoding of these internally generated signals by different projection systems enriched in neocortical layer 1 during defined brain functions, including memory, attention, and predictive coding. Moreover, we identify gaps in current knowledge and highlight future directions for this rapidly advancing field.

Occurrence and phenomenology of hallucinations in the general population: A large online survey

Although epidemiological studies report that hallucinations occur in 6–15% of the general population, little is known about their phenomenology. To overcome this paucity, this study investigates the phenomenological characteristics of hallucinations in the general population, by using a nationally promoted online survey to assess hallucination phenomenology in four sensory modalities, through a self-report version of the Questionnaire for Psychotic Experiences (QPE), in 10,448 participants (aged 14–88 years). The phenomenology of hallucinations was assessed if hallucinations reportedly occurred in the past month. In the past month, auditory hallucinations were reported most frequently (29.5%), followed by visual (21.5%), tactile (19.9%), and olfactory hallucinations (17.3%); hallucinations in two or more modalities were reported by 47.6%. Substantial numbers of participants rated their hallucinations as severe, due to negative content (16.0–31.6%), previous bothersome experiences (14.8–20.2%), ensuing distress (10.5–16.8%), and/or ensuing disfunctioning (12.7–17.3%). Decreased insight was found in 10.2–11.4%. Hypnagogia was reported by 9.0–10.6%, and bereavement hallucinations by 2.8%. Despite a low prevalence of delusions (7.0%), these phenomena were significantly associated with recent hallucinations, observed in up to 13.4% of the participants with hallucinations during the past week (p < 0.001). Our results indicate a wide variety of the phenomenology of hallucinations in the general population and support the existence of a phenomenological continuum.

Neuroscience robotics for controlled induction and real-time assessment of hallucinations

Although hallucinations are important and frequent symptoms in major psychiatric and neurological diseases, little is known about their brain mechanisms. Hallucinations are unpredictable and private experiences, making their investigation, quantification and assessment highly challenging. A major shortcoming in hallucination research is the absence of methods able to induce specific and short-lasting hallucinations, which resemble clinical hallucinations, can be elicited repeatedly and vary across experimental conditions. By integrating clinical observations and recent advances in cognitive neuroscience with robotics, we have designed a novel device and sensorimotor method able to repeatedly induce a specific, clinically relevant hallucination: presence hallucination. Presence hallucinations are induced by applying specific conflicting (spatiotemporal) sensorimotor stimulation including an upper extremity and the torso of the participant. Another, MRI-compatible, robotic device using similar sensorimotor stimulation permitted the identification of the brain mechanisms of these hallucinations. Enabling the identification of behavioral and a frontotemporal neural biomarkers of hallucinations, under fully controlled experimental conditions and in real-time, this method can be applied in healthy participants as well as patients with schizophrenia, neurodegenerative disease or other hallucinations. The execution of these protocols requires intermediate-level skills in cognitive neuroscience and MRI processing, as well as minimal coding experience to control the robotic device. These protocols take ~3 h to be completed.

Subjective experiences as nodes within mental disorder networks

What are the functional roles of subjective experiences? Answering this question amounts to charting a course for the cognitive science of consciousness, where mental processes can be described in terms of their functions. If we strategically focus on mental disorders, preliminary answers may be in sight within 25 years.