To demonstrate the effects of a metacognitive reflection and insight therapy (MERIT) in people suffering from psychiatric disorders.

A systematic review was carried out on PubMed, PsychInfo, Psycharticles and Psychological and Behavioral Science Collection from 1980 to 2024.

The review included five randomized controlled studies, four observational group studies and 22 case studies with quantitative measures. Analyses indicated that MERIT significantly increases metacognitive abilities to reflect on oneself and others, as well as mastery of one's strategies. In addition, some studies found an improvement in insight and symptomatology. Most studies included participants with psychotic disorders.

MERIT is an effective therapy for promoting subjective recovery by improving metacognitive abilities in people with psychotic disorders. However, further studies are needed to generalize this result to other psychiatric disorders.

Sensory symptoms are highly prevalent amongst autistic individuals and are now considered in the diagnostic criteria. Whilst evidence suggests a genetic relationship between autism and sensory symptoms, sensory symptoms are neither universal within autism nor unique to autism. One explanation for the heterogeneity within autism and commonality across conditions with respect to sensory symptoms, is that it is alexithymia (a condition associated with difficulties identifying and describing one's own emotions) that has a genetic relationship with sensory symptoms, and that alexithymia commonly co-occurs with autism and with several other conditions. Using parent-reports of symptoms in a sample of adolescent twins, we sought to examine the genetic association between autism, alexithymia and sensory symptoms. Results showed that the genetic correlation between autism and sensory symptoms was not significant after controlling for alexithymia. In contrast, after controlling for variance in alexithymia explained by autism, the genetic correlation between alexithymia and sensory symptoms was significant (and the proportion of variance explained by genetic factors remained consistent after controlling for autism). These results suggest that 1) alexithymia and sensory symptoms share aetiology that is not accounted for by their association with autism and 2) that the genetic association between sensory symptoms and autism may be, in part or wholly, a product of alexithymia. Future research should seek to examine the contribution of alexithymia to sensory symptoms across other conditions.

The clinical symptoms of schizophrenia are highly heterogeneous, with the most striking symptoms being cognitive deficits and perceptual disturbances. Cognitive deficits are typically linked to abnormalities in top-down mechanisms, whereas perceptual disturbances stem from dysfunctions in bottom-up processing. However, it remains unclear whether schizophrenia is primarily driven by top-down control mechanisms, bottom-up perceptual processes, or their interaction. We hypothesized that abnormal top-down and bottom-up interactions constitute the neural mechanisms of schizophrenia. Considering that autoencoders can identify hidden data features and support vector machines are capable of automatically locating the classification hyperplane, we developed an improved stacked autoencoder-support vector machine (ISAE-SVM) model for diagnosing schizophrenia based on resting-state functional magnetic resonance imaging data. A permutation test was used to identify the 213 most discriminative functional connections from the model's output features. Functional connections linking regions of higher cognitive functions and lower perceptual tasks were extracted to further examine their relevance to clinical symptoms. Finally, spectral dynamic causal modeling (sDCM) was used to analyze the dynamic causal interaction between brain regions corresponding to these functional connections. Our results showed that the ISAE-SVM model achieved an average classification accuracy of 82%. Notably, five resting-state functional connections spanning both cognitive and sensory brain areas were significantly correlated with Positive and Negative Syndrome Scale scores. Furthermore, sDCM analysis revealed weakened top-down regulation and enhanced bottom-up signaling in schizophrenia. These findings support our hypothesis that impaired top-down regulation and enhanced bottom-up signaling contribute to the neural mechanisms of schizophrenia.

As the field of consciousness science matures, the research agenda has expanded from an initial focus on the neural correlates of consciousness, to developing and testing theories of consciousness. Several theories have been put forward, each aiming to elucidate the relationship between consciousness and brain function. However, there is an ongoing, intense debate regarding whether these theories examine the same phenomenon. And, despite ongoing research efforts, it seems like the field has so far failed to converge around any single theory, and instead exhibits significant polarization. To advance this discussion, proponents of five prominent theories of consciousness-Global Neuronal Workspace Theory (GNWT), Higher-Order Theories (HOT), Integrated Information Theory (IIT), Recurrent Processing Theory (RPT), and Predictive Processing (PP)-engaged in a public debate in 2022, as part of the annual meeting of the Association for the Scientific Study of Consciousness (ASSC). They were invited to clarify the explananda of their theories, articulate the core mechanisms underpinning the corresponding explanations, and outline their foundational premises. This was followed by an open discussion that delved into the testability of these theories, potential evidence that could refute them, and areas of consensus and disagreement. Most importantly, the debate demonstrated that at this stage, there is more controversy than agreement between the theories, pertaining to the most basic questions of what consciousness is, how to identify conscious states, and what is required from any theory of consciousness. Addressing these core questions is crucial for advancing the field towards a deeper understanding and comparison of competing theories.

We easily distinguish self-touch from the touch of others. This distinction is suggested to arise because the brain predicts the somatosensory consequences of voluntary movements using an efference copy and attenuates the predicted self-touch. However, it remains unclear how these predictions impact somatosensory perception before or after the self-touch occurs. Here, participants discriminated forces applied to their left index finger at different phases of the right hand's reaching movement toward the left hand. We observed that forces felt progressively weaker during the reaching, reached their minimum perceived intensity at the time of self-touch, and recovered after the movement ended. We further demonstrated that this gradual attenuation vanished during similar reaching movements that did not produce expectations of self-touch between the two hands. Our results indicate a temporal tuning of somatosensory perception during movements to self-touch and underscore the role of sensorimotor context in forming predictions that attenuate the self-touch intensity.

According to the aberrant salience proposal, reward processing abnormality, specifically erroneous reward prediction error (RPE) signaling due to stimulus-independent release of dopamine, underlies delusions in schizophrenia. However, no studies to date have examined RPE-associated brain activations in relation to this symptom.

Seventy-eight patients with a DSM-5 diagnosis of schizophrenia/schizoaffective disorder and 43 healthy individuals underwent fMRI while they performed a probabilistic monetary reward task designed to generate a measure of RPE. Ratings of delusions and referentiality were made in the patients.

Using whole-brain, voxel-based analysis, schizophrenia patients showed only minor differences in RPE-associated activation compared to healthy controls. Within the patient group, however, severity of delusions was inversely associated with RPE-associated activation in areas including the caudate nucleus, the thalamus and the left pallidum, as well as the lateral frontal cortex bilaterally, the pre- and postcentral gyrus and supplementary motor area, the middle cingulate gyrus, and parts of the temporal and parietal cortex. A broadly similar pattern of association was seen for referentiality.

According to this study, while patients with schizophrenia as a group do not show marked alterations in RPE signaling, delusions and referentiality are associated with reduced activation in parts of the prefrontal cortex and the basal ganglia, though not specifically the ventral striatum. The direction of the changes is on the face of it contrary to that predicted by aberrant salience theory.

Predictive coding is a theoretical framework that integrates models of brain dysconnectivity and psychopathology in psychosis. Thalamocortical dysconnectivity as well as reduced thalamic volumes have been reported in psychotic disorders. However, the role of the thalamus in predictive coding is not clear. We examined the relationship between magnetic resonance imaging (MRI)- based thalamic nuclei volumes and mismatch negativity (MMN), a purported index of prediction error signaling known to be impaired in psychosis.

We obtained MRI and MMN using a roving paradigm from individuals with SCZ spectrum disorder (SSD, n = 60) or bipolar disorder (BD, n = 69) and HC (n = 252). We segmented volumes of 25 thalamic nuclei bilaterally and tested their associations with MMN amplitude using linear models while covarying for age, sex, diagnosis, and intracranial volumes (ICV).

We did not find group differences in thalamic volumes that could account for differences in MMN, neither did we find significant volume × diagnosis interactions on MMN for any of the 25 nuclei examined. Across the whole sample, significant positive associations were found between MMN amplitude and the volumes of several higher-order thalamic nuclei, including the mediodorsal medial and lateral nuclei, anterior and medial pulvinar, nucleus reuniens, as well as the lateral geniculate nucleus.

The results demonstrate a positive association between MMN amplitude and volumes of thalamic association nuclei in patients with psychotic disorders and HC. These findings may suggest a modulatory role of the thalamus in prediction error signaling.

Sensory attenuation refers to the reduction in sensory intensity resulting from self-initiated actions compared to stimuli initiated externally. A classic example is scratching oneself without feeling itchy. This phenomenon extends across various sensory modalities, including visual, auditory, somatosensory, and nociceptive stimuli. The internal forward model proposes that during voluntary actions, an efferent copy of the action command is sent out to predict sensory feedback. This predicted sensory feedback is then compared with the actual sensory feedback, leading to the suppression or reduction of sensory stimuli originating from self-initiated actions. To further elucidate the neural mechanisms underlying sensory attenuation effect, we conducted an extensive meta-analysis of functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) studies. Utilizing activation likelihood estimation (ALE) analysis, our results revealed significant activations in a prominent cluster encompassing the right superior temporal gyrus (rSTG), right middle temporal gyrus (rMTG), and right insula when comparing external-generated with self-generated conditions. Additionally, significant activation was observed in the right anterior cerebellum when comparing self-generated to external-generated conditions. Further analysis using meta-analytic connectivity modeling (MACM) unveiled distinct brain networks co-activated with the rMTG and right cerebellum, respectively. Based on these findings, we propose that sensory attenuation arises from the suppression of reflexive inputs elicited by self-initiated actions through the internal forward modeling of a cerebellum-centered action prediction network, enabling the "sensory conflict detection" regions to effectively discriminate between inputs resulting from self-induced actions and those originating externally.

Historically, Frith's comparator model has been a seminal account of the sense of agency in thought and bodily action. According to this model, only thoughts and actions that are successfully predicted are experienced as agentive, thus providing a unified account of the sense of agency for mind and body. However, this unified model has since been rejected on the grounds that thinking and bodily action impose different constraints on the experience of agency and conscious prediction. While this is widely accepted, the predictive processing model of the sense of agency offers a new perspective that avoids previous arguments against a unified comparator model and paves the way for its reintroduction.

Belief processing and self-referential processing have been consistently associated with cortical midline structures, and cortical regions such as the vmPFC have been implicated in general belief processing. The neural correlates of self-referential belief are yet to be investigated. In this fMRI study, we presented 120 statements with trait adjectives to N = 27 healthy participants, who subsequently judged whether they believed these trait adjectives applied to themselves, a close person, or a public person. Thereafter, participants rated their certainty in this judgment. Expectedly, self-referential processing evoked a large cluster in the vmPFC, ACC, and dmPFC. For belief, we found a cluster in the vmPFC, ACC, and amPFC during statement presentation, partially overlapping with that for self-referential processing. The cluster for self-belief vs. disbelief was similar in location and size to that for general belief processing. For uncertainty, we found dmPFC activation. We replicated vmPFC involvement in belief processing and found a common neural correlate for belief and self-belief in the vmPFC. Furthermore, we replicated the role of the dmPFC in uncertainty, supporting a dual neural process model of belief and certainty.

Psychotic experiences are thought to emerge from various interrelated patterns of disrupted belief updating, such as overestimating the reliability of sensory information and misjudging task volatility, yet these substrates have never been jointly addressed under one computational framework, and it is not clear to what degree they reflect trait-like computational patterns.

We introduce a novel hierarchical Bayesian model that describes how individuals simultaneously update their beliefs about the task volatility and noise in observation. We applied this model to data from a modified predictive inference task in a test-retest study with healthy volunteers (N = 45, 4 sessions) and examined the relationship between model parameters and schizotypal traits in a larger online sample (N = 437) and in a cohort of patients with schizophrenia (N = 100).

The interclass correlations were moderate to high for model parameters and excellent for averaged belief trajectories and precision-weighted learning rates estimated through hierarchical Bayesian inference. We found that uncertainty about the task volatility was related to schizotypal traits and to positive symptoms in patients, when learning to gain rewards. In contrast, negative symptoms in patients were associated with more rigid beliefs about observational noise, when learning to avoid losses.

These findings suggest that individuals with schizotypal traits across the psychosis continuum are less likely to learn or use higher-order statistical regularities of the environment and showcase the potential of clinically relevant computational phenotypes for differentiating symptom groups in a transdiagnostic manner.

Alterations of mismatch responses (ie, neural activity evoked by unexpected stimuli) are often considered a potential biomarker of schizophrenia. Going beyond establishing the type of observed alterations found in diagnosed patients and related cohorts, computational methods can yield valuable insights into the underlying disruptions of neural mechanisms and cognitive function. Here, we adopt a typology of model-based approaches from computational cognitive neuroscience, providing an overview of the study of mismatch responses and their alterations in schizophrenia from four complementary perspectives: (a) connectivity models, (b) decoding models, (c) neural network models, and (d) cognitive models. Connectivity models aim at inferring the effective connectivity patterns between brain regions that may underlie mismatch responses measured at the sensor level. Decoding models use multivariate spatiotemporal mismatch response patterns to infer the type of sensory violations or to classify participants based on their diagnosis. Neural network models such as deep convolutional neural networks can be used for improved classification performance as well as for a systematic study of various aspects of empirical data. Finally, cognitive models quantify mismatch responses in terms of signaling and updating perceptual predictions over time. In addition to describing the available methodology and reviewing the results of recent computational psychiatry studies, we offer suggestions for future work applying model-based techniques to advance the study of mismatch responses in schizophrenia.

Technological advances in fMRI including ultra-high magnetic fields (≥ 7 T) and acquisition methods that increase spatial specificity have paved the way for studies of the human cortex at the scale of layers and columns. This mesoscopic scale promises an improved mechanistic understanding of human cortical function so far only accessible to invasive animal neurophysiology. In recent years, an increasing number of studies have applied such methods to better understand the cortical function in perception and cognition. This future perspective article asks whether closed-loop fMRI studies could equally benefit from these methods to achieve layer and columnar specificity. We outline potential applications and discuss the conceptual and concrete challenges, including data acquisition and volitional control of mesoscopic brain activity. We anticipate an important role of fMRI with mesoscopic resolution for closed-loop fMRI and neurofeedback, yielding new insights into brain function and potentially clinical applications.This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

Schizophrenia (SZ) is associated with visual processing impairments, which are related to higher-level functional impairments. This study investigated the impact of a novel visual remediation intervention (VisR) targeting low- and mid-level visual processing impairments in SZ. We hypothesized that VisR would lead to greater improvements in contrast processing when compared to an active control condition and explored potential treatment-related changes in symptom severity. SZ participants (N = 47) were randomized into one of four groups: an active control group (cognitive training; AC); Contrast Sensitivity Training + AC (CST + AC); Contour Integration Training + AC (CIT + AC); and CST + CIT. Participants completed 20-40 training sessions. Clinical symptom severity was assessed using the Positive and Negative Syndrome Scale and contrast processing was assessed using steady-state visual evoked potentials to increasing levels of contrast of isolated-check pattern stimuli. A significant Group × Timepoint × Contrast interaction indicated superiority of CST + CIT over AC for improving contrast processing. Furthermore, a large, significant Group × Timepoint interaction indicated that CST + CIT was associated with a greater reduction in positive symptoms compared to AC. In addition, lower severity of positive symptoms at baseline was associated with a greater improvement in contrast processing over the course of treatment. This initial evaluation of VisR demonstrated that it is well tolerated and may produce greater improvements in contrast processing and positive symptoms compared to an intervention targeting only high-level cognitive functions.

Distorted body representations play a major role in the onset and maintenance of Schizophrenia. However, these distortions are difficult to assess because explicit assessments can provoke intense fears about the body and require a good insight. We proposed an implicit motor imagery task to a 14-year-old girl with Early-Onset Schizophrenia. The test consisted of presenting different openings varying in width. For each aperture, the young girl has to say if she could pass through without turning her shoulders. A critical aperture is determined as the first aperture for which she considered she could no longer pass, compared to her shoulders' width. The girl perceived herself as 51 % wider than she was, indicating a significant oversized body schema. The implicit assessments of body schema generate less anxiety and does not require a great level of insight; moreover, those are promising tools for early detection of disease in prodromal phases of Schizophrenia and assistance with differential diagnosis.

It has been long known that people with schizophrenia (SZ) have deficits in perceptual processing, including in the auditory domain. Furthermore, they often experience increased emotional responsivity and dysregulation, which further impacts overall functioning. Increased emotional responsivity to auditory stimuli is also seen in people with misophonia, a condition in which specific sounds elicit robust negative emotional responses. Given the role of emotional reactivity and dysregulation in the pathogenesis of SZ, our study investigated whether misophonia symptoms were elevated in SZ, or if people with SZ have a generalized increase in reactivity to sensory information. To explore the link between emotional reactivity to sound and more general aspects emotional reactivity and salience signaling in SZ, we used the Misophonia Questionnaire, the Sensory Processing Scale (SPS), and Aberrant Salience Inventory (ASI) in 30 people with SZ and 28 demographically-matched healthy volunteers (HVs). We found that people with SZ exhibited more emotional behavior associated with misophonia symptoms (specifically, distress in relation to sound) than HVs (t56 = 4.889, p < 0.001), but did not have elevated rates of misophonia overall. Also, sensory processing abnormalities and heightened emotional responses in people with SZ were not limited to the auditory domain but, rather, extended to all sensory modalities. Our results support the idea that SZ involves dysfunction in salience signaling, regarding auditory stimuli, but that abnormalities in salience signaling in SZ are more domain-general. These results highlight the importance of interventions designed to enhance emotion regulation in patients with SZ regarding stimuli in multiple modalities.

The degree to which numerous existing models of delusion formation disagree or propose common mechanisms remains unclear. To achieve a comprehensive understanding of delusion aetiology, we summarised 53 theoretical models of delusions extracted from a systematic literature search. We identified central aspects and unique or overarching features of five core perspectives: cognitive (n = 22), associative learning (n = 4), social (n = 6), neurobiological (n = 6), and Bayesian inference (n = 15). These perspectives differ in foci and mechanistic explanations. Whereas some postulate delusions to result from associative and operant learning, others assume a disbalance in the integration of prior beliefs and sensory input or emphasise the relevance of information processing biases. Postulated moderators range from maladaptive generalised beliefs over neurocognitive impairment to dopamine, stress, and affective dysregulation. The models also differ in whether they attempt to explain delusion formation in general or the delusional content (i.e., persecutory). Finally, some models postulate functional aspects of delusions, such as insight relief. Despite their differences, the perspectives converge on the idea that delusions form as an explanation for an experienced ambiguity. Building on this common ground, we propose an integrative framework incorporating essential mechanistic explanations from each perspective and discuss its implications for research and clinical practice.

The computational mechanisms underlying psychiatric disorders are hotly debated. One hypothesis, grounded in the Bayesian predictive coding framework, proposes that patients with schizophrenia have abnormalities in encoding prior beliefs about the environment, resulting in abnormal sensory inference, which can explain core aspects of the psychopathology, such as some of its symptoms.

Here, we tested this hypothesis by identifying oscillatory traveling waves as neural signatures of predictive coding. We analyzed an electroencephalography dataset comprising 146 patients with schizophrenia and 96 age-matched healthy control participants during resting states and a visual backward masking task.

We found that patients with schizophrenia had stronger top-down alpha-band traveling waves compared with healthy control participants during resting state, supposedly reflecting overly precise priors at higher levels of the predictive processing hierarchy. We also found stronger bottom-up alpha-band waves in patients with schizophrenia during a visual task, consistent with the notion of enhanced signaling of sensory precision errors.

Our results yield a novel spatial-based characterization of oscillatory dynamics in schizophrenia, considering brain rhythms as traveling waves and providing a unique framework to study the different components involved in a predictive coding scheme. All together, our findings significantly advance our understanding of the mechanisms involved in fundamental pathophysiological aspects of schizophrenia, promoting a more comprehensive and hypothesis-driven approach to psychiatric disorders.

Psychosis is a hallmark of schizophrenia. It typically emerges in late adolescence and is associated with dopamine abnormalities and aberrant salience. Most genes associated with schizophrenia risk involve ubiquitous targets that may not explain delayed emergence of dopaminergic disruptions. This includes GRIN2A, the gene encoding the GluN2A subunit of the NMDA receptor. Both common and rare variants of GRIN2A are considered genetic risk factors for schizophrenia diagnosis. We find that Grin2a knockout in dopamine neurons during adolescence is sufficient to produce a behavioral phenotype that mirrors aspects of psychosis. These include disruptions in effort optimization, salience attribution, and ability to utilize feedback to guide behavior. We also find a selective effect of this manipulation on dopamine release during prediction error signaling. These data provide mechanistic insight into how variants of GRIN2A may lead to the latent presentation of aberrant salience and abnormalities in dopamine dynamics. This etiologically relevant model may aid future discovery of course altering treatments for schizophrenia.

Individuals with schizophrenia have less priors than controls, meaning they rely less upon their prior experiences to interpret the current stimuli. These differences in priors are expected to show as higher alternation rates in bistable perception tasks like the Structure-from-Motion (SfM) paradigm. In this paradigm, continuously moving dots in two dimensions are perceived subjectively as traveling along a three-dimensional sphere, which results in a direction of motion (left or right) that shifts approximately every few seconds.

Here, we tested healthy controls, patients with schizophrenia, siblings of patients with schizophrenia, and patients with depression with both the intermittent and continuous variants of the SfM paradigm.

In the intermittent variant of the SfM paradigm, depressive patients exhibited the lowest alternation rate, followed by unaffected controls. In contrast, patients with schizophrenia and their unaffected siblings displayed significantly higher alternation rates. In the continuous variant of the SfM paradigm, patients with schizophrenia showed the lowest mean percept durations, while there were no differences between the other three groups.

The intermittent SfM paradigm is a candidate endophenotype for schizophrenia. The aberrant processing in the patients may stem from alterations in adaptation and/or cross-inhibition mechanisms leading to changes in priors, as suggested by current models in the field. The intermittent SfM paradigm is, hence, a trait marker that offers the great opportunity to investigate perceptual abnormalities across the psychiatry spectrum, ranging from depression to psychosis.

Mental illnesses arise from dysfunction in the brain. Although numerous extraneural factors influence these illnesses, ultimately, it is the science of the brain that will lead to novel therapies. Meanwhile, our understanding of this complex organ is incomplete, leading to the oft-repeated trope that neuroscience has yet to make significant contributions to the care of individuals with mental illnesses. This review seeks to counter this narrative, using specific examples of how neuroscientific advances have contributed to progress in mental health care in the past and how current achievements set the stage for further progress in the future.

A complex interaction among sensory, social and epigenetic determinants in psychiatric conditions was described across all age strata. The high prevalence of mental disorders in individuals with sensory deficits might be attributed to the interaction among social isolation, cognitive functioning and sensory processing. The epigenetic implications of such interactions were examined: environmental and social factors can affect gene expression and impact the pathogenesis of psychiatric disorders also through sensory processing. This article discussed the role of social determinants, in other words, social isolation, loneliness and chronic stress, in promoting psychiatric disorders and, in a vicious circle, sensory deficits (vision, hearing, olfaction and somatosensation). We emphasized the importance of integrating social, sensory and epigenetic factors to target different treatments for psychiatric conditions.

Distinguishing reality from hallucinations requires efficient monitoring of agency. It has been hypothesized that a copy of motor signals, termed efference copy (EC) or corollary discharge (CD), suppresses sensory responses to yield a sense of agency; impairment of the inhibitory function leads to hallucinations. However, how can the sole absence of inhibition yield positive symptoms of hallucinations? We hypothesize that selective impairments in functionally distinct signals of CD and EC during motor-to-sensory transformation cause the positive symptoms of hallucinations. In an electroencephalography (EEG) experiment with a delayed articulation paradigm in schizophrenic patients with (AVHs) and without auditory verbal hallucinations (non-AVHs), we found that preparing to speak without knowing the contents (general preparation) did not suppress auditory responses in both patient groups, suggesting the absent of inhibitory function of CD. Whereas, preparing to speak a syllable (specific preparation) enhanced the auditory responses to the prepared syllable in non-AVHs, whereas AVHs showed enhancement in responses to unprepared syllables, opposite to the observations in the normal population, suggesting that the enhancement function of EC is not precise in AVHs. A computational model with a virtual lesion of an inhibitory inter-neuron and disproportional sensitization of auditory cortices fitted the empirical data and further quantified the distinct impairments in motor-to-sensory transformation in AVHs. These results suggest that "broken" CD plus "noisy" EC causes erroneous monitoring of the imprecise generation of internal auditory representation and yields auditory hallucinations. Specific impairments in functional granularity of motor-to-sensory transformation mediate positivity symptoms of agency abnormality in mental disorders.

The sense of agency refers to the feeling of initiating and controlling one's actions and their resulting effects on the external environment. Previous studies have uncovered behavioral evidence of excessive self-attribution and, conversely, a reduction in the sense of agency in patients with schizophrenia. We hypothesize that this apparent paradox is likely to result from impairment in lower-level processes underlying the sense of agency, combined with a higher-level compensational bias. The present study employed three behavioral tasks utilizing the same stimuli and experimental design to systematically evaluate multiple factors that influence the sense of agency, including motor control, sensorimotor processing, and self-attribution. Participants' real-time mouse movements were combined with prerecorded motions of others in ratios of 30/70, 55/45, or 80/20, with an additional angular bias of either 0° or 90°. Twenty-six patients with schizophrenia and 27 health control volunteers participated in the three tasks. Patients with schizophrenia performed significantly worse in the reaching and control detection tasks than healthy controls. However, their self-attribution in the control judgment task was comparable to that of the healthy controls. Patients with schizophrenia were impaired in motor control components and in the detection of control using sensorimotor information, but their evaluation of agency remained relatively less affected. This underscores the importance of distinguishing between different subcomponents when addressing the abnormal sense of agency in patients with schizophrenia. Subsequent cluster analysis revealed that the combined task performance accurately distinguished between the patients and healthy control participants.

Many decisions entail the updating of beliefs about the state of the environment by accumulating noisy sensory evidence. This form of probabilistic reasoning may go awry in psychosis. Computational theory shows that optimal belief updating in environments subject to hidden changes in their state requires a dynamic modulation of the evidence accumulation process. Recent empirical findings implicate transient responses of pupil-linked central arousal systems to individual evidence samples in this modulation. Here, we analyzed behavior and pupil responses during evidence accumulation in a changing environment in a community sample of human participants. We also assessed their subclinical psychotic experiences (psychosis proneness). Participants most prone to psychosis showed overall less flexible belief updating profiles, with diminished behavioral impact of evidence samples occurring late during decision formation. These same individuals also exhibited overall smaller pupil responses and less reliable pupil encoding of computational variables governing the dynamic belief updating. Our findings provide insights into the cognitive and physiological bases of psychosis proneness and open paths to unraveling the pathophysiology of psychotic disorders.

Active inference describes (Bayes-optimal) behaviour as being motivated by the minimisation of surprise of one's sensory observations, through the optimisation of a generative model (of the hidden causes of one's sensory data) in the brain. One of active inference's key appeals is its conceptualisation of precision as biasing neuronal communication and, thus, inference within generative models. The importance of precision in perceptual inference is evident-many studies have demonstrated the importance of ensuring precision estimates are correct for normal (healthy) sensation and perception. Here, we highlight the many roles precision plays in action, i.e., the key processes that rely on adequate estimates of precision, from decision making and action planning to the initiation and control of muscle movement itself. Thereby, we focus on the recent development of hierarchical, "mixed" models-generative models spanning multiple levels of discrete and continuous inference. These kinds of models open up new perspectives on the unified description of hierarchical computation, and its implementation, in action. Here, we highlight how these models reflect the many roles of precision in action-from planning to execution-and the associated pathologies if precision estimation goes wrong. We also discuss the potential biological implementation of the associated message passing, focusing on the role of neuromodulatory systems in mediating different kinds of precision.

The war in Syria has displaced over 6.8 million people, more than any other conflict since the Second World War. As a result, Syrian asylum seekers and refugees have experienced several life-changing events, resulting in high rates of anxiety, depression, posttraumatic stress disorder, and suicidal ideation (SI). To address the treatment gap and reduce the burden of help-seeking, a web-based intervention to reduce SI developed for general populations was culturally adapted for and with Syrian asylum seekers and refugees in the United Kingdom. The study revealed the importance of understanding their lived experience with migration and the acculturative process in providing treatment for SI. This study will now assess the feasibility and acceptability of the culturally adapted intervention for this population.

The first phase of the study will include recruiting participants and delivering the web-based intervention (1) to assess the feasibility of meeting recruitment goals and recruitment rates and (2) to assess the feasibility of outcome measures. The second phase of the study will include one-to-one semistructured interviews (1) to assess the suitability of the culturally adapted intervention in terms of recruitment and adherence rates and barriers and facilitators to engagement and (2) to assess the acceptability of the intervention in terms of its cultural relevance and appropriateness.

This is a protocol for a single-group, noncontrolled, mixed methods feasibility and acceptability study of a culturally adapted web-based intervention to reduce SI for Syrian asylum seekers and refugees in the United Kingdom. The study will assess the feasibility of recruitment goals, recruitment rates, adherence rates, and outcome measures using individual participant tracking forms, which will be analyzed quantitatively. The suitability and acceptability of the intervention will be assessed using one-to-one semistructured interviews with 12 participants who completed the intervention, which will be analyzed qualitatively.

Recruitment began in February 2024 and will run until 30 participants are recruited to the study or until the end of July 2024. Thus far, 19 participants have provided informed consent, 16 were eligible and enrolled, and 12 have completed a postintervention interview. No data have been analyzed. The study, including the write-up period, is expected to end in December 2024.

Despite experiencing several stressors related to forced displacement and high rates of mental health issues, access to treatment is still limited for Syrian asylum seekers and refugees in the United Kingdom. To address the treatment gap and reduce the burden of help-seeking, a web-based intervention to reduce SI was culturally adapted in collaboration with Syrian asylum seekers and refugees in the United Kingdom. This study will now assess the feasibility and acceptability of the intervention and culturally appropriate recruitment strategies.

ISRCTN ISRCTN11417025; https://www.isrctn.com/ISRCTN11417025.

PRR1-10.2196/56957.

Dysregulated prediction error-signalling may explain auditory hallucinations in schizophrenia (SZ-AH). Roving mismatch negativity (rMMN) is an event-related potential (ERP) index where the deviant tone becomes the new standard with repetitions. Longer repetitions of standard stimuli yield a more positive sensory-adaptation response (Repetition Positivity-RP), elicit a stronger deviance-detection when interrupted (deviant negativity-DN), and the difference waveform between them reflects the strength of prediction-error signalling (mismatch negativity-MMN).

Twenty-three SZ-AH patients and twenty-three healthy controls (HC) underwent rMMN assessment. Various standard stimuli were repeated in sets of 3, 8 and 33 yielding three components for RP (RP3, RP8, RP33), DN (DN3, DN8, DN33), and MMN (MMN3, MMN8, MMN33). Amplitudes and latencies were compared across groups. Correlation between (a) rMMN amplitudes and latencies, and clinical variables in SZ-AH, and (b) the RP-DN amplitude pair for all three repetition sets (3, 8, 33) were also examined.

All DN and MMN33 amplitudes were significantly suppressed in SZ-AH, while RP amplitudes were not. MMN33 latency was significantly longer in SZ-AH than HC. A few amplitudes and latencies significantly correlated with the frequency of AH. HC showed a significant positive correlation between RP-DN amplitude pairs for sets of 3 and 8 but not for 33; SZ-AH group's correlation profile was opposite to this.

The link between repetition-dependent sensory-adaptation and deviance-detection is perturbed in SZ-AH. The unimpaired RP profile in SZ-AH is due to potential interference of AH with auditory information processing, and does not indicate a preserved short-term plasticity of the echoic memory trace.

Hallucinations and perceptual abnormalities in psychosis are thought to arise from imbalanced integration of prior information and sensory inputs. We combined psychophysics, Bayesian modeling, and electroencephalography (EEG) to investigate potential changes in perceptual and causal inference in response to audiovisual flash-beep sequences in medicated individuals with schizophrenia who exhibited limited psychotic symptoms. Seventeen participants with schizophrenia and 23 healthy controls reported either the number of flashes or the number of beeps of audiovisual sequences that varied in their audiovisual numeric disparity across trials. Both groups balanced sensory integration and segregation in line with Bayesian causal inference rather than resorting to simpler heuristics. Both also showed comparable weighting of prior information regarding the signals' causal structure, although the schizophrenia group slightly overweighted prior information about the number of flashes or beeps. At the neural level, both groups computed Bayesian causal inference through dynamic encoding of independent estimates of the flash and beep counts, followed by estimates that flexibly combine audiovisual inputs. Our results demonstrate that the core neurocomputational mechanisms for audiovisual perceptual and causal inference in number estimation tasks are largely preserved in our limited sample of medicated post-acute individuals with schizophrenia. Future research should explore whether these findings generalize to unmedicated patients with acute psychotic symptoms.

In recent decades, hypnosis has increasingly moved into the mainstream of scientific inquiry. Hypnotic suggestions are frequently implemented in behavioral, neurocognitive, and clinical investigations and interventions. Despite abundant reports about the effectiveness of suggestions in altering behavior, perception, cognition, and agency, no consensus exists regarding the mechanisms driving these changes. This article reviews competing theoretical accounts that address the genesis of subjective, behavioral, and neurophysiological responses to hypnotic suggestions. We systematically analyze the broad landscape of hypnosis theories that best represent our estimation of the current status and future avenues of scientific thinking. We start with procedural descriptions of hypnosis, suggestions, and hypnotizability, followed by a comparative analysis of systematically selected theories. Considering that prominent theoretical perspectives emphasize different aspects of hypnosis, our review reveals that each perspective possesses salient strengths, limitations, and heuristic values. We highlight the necessity of revisiting extant theories and formulating novel evidence-based accounts of hypnosis.

Predictive processing is a computational framework that aims to explain how the brain processes sensory information by making predictions about the environment and minimizing prediction errors. It can also be used to explain some of the key symptoms of psychotic disorders such as schizophrenia. In recent years, substantial advances have been made in our understanding of the neuronal circuitry that underlies predictive processing in cortex. In this review, we summarize these findings and how they might relate to psychosis and to observed cell type-specific effects of antipsychotic drugs. We argue that quantifying the effects of antipsychotic drugs on specific neuronal circuit elements is a promising approach to understanding not only the mechanism of action of antipsychotic drugs but also psychosis. Finally, we outline some of the key experiments that should be done. The aims of this review are to provide an overview of the current circuit-based approaches to psychosis and to encourage further research in this direction.

The phenomenon of "hearing voices" can be found not only in psychotic disorders, but also in the general population, with individuals across cultures reporting auditory perceptions of supernatural beings. In our preregistered study, we investigated a possible mechanism of such experiences, grounded in the predictive processing model of agency detection. We predicted that in a signal detection task, expecting less or more voices than actually present would drive the response bias toward a more conservative and liberal response strategy, respectively. Moreover, we hypothesized that including sensory noise would enhance these expectancy effects. In line with our predictions, the findings show that detection of voices relies on expectations and that this effect is especially pronounced in the case of unreliable sensory data. As such, the study contributes to our understanding of the predictive processes in hearing and the building blocks of voice hearing experiences.

We used a probabilistic reversal learning task to examine prediction error-driven belief updating in three clinical groups with psychosis or psychosis-like symptoms. Study 1 compared people with at-risk mental state and first episode psychosis (FEP) to matched controls. Study 2 compared people diagnosed with treatment-resistant schizophrenia (TRS) to matched controls. The design replicated our previous work showing ketamine-related perturbations in how meta-level confidence maintained behavioural policy. We applied the same computational modelling analysis here, in order to compare the pharmacological model to three groups at different stages of psychosis. Accuracy was reduced in FEP, reflecting increased tendencies to shift strategy following probabilistic errors. The TRS group also showed a greater tendency to shift choice strategies though accuracy levels were not significantly reduced. Applying the previously-used computational modelling approach, we observed that only the TRS group showed altered confidence-based modulation of responding, previously observed under ketamine administration. Overall, our behavioural findings demonstrated resemblance between clinical groups (FEP and TRS) and ketamine in terms of a reduction in stabilisation of responding in a noisy environment. The computational analysis suggested that TRS, but not FEP, replicates ketamine effects but we consider the computational findings preliminary given limitations in performance of the model.

Although humans can recognize their body movements in point-light displays, self-recognition ability varies substantially across action types and participants. Are these variations primarily due to an awareness of visually distinct movement patterns, or to underlying factors related to motoric planning and/or individual differences? To address this question, we conducted a large-scale study in self-action recognition (N = 101). We motion captured whole-body movements of participants who performed 27 different actions across action goals and degree of motor planning. After a long delay period (~ 1 month), participants were tested in a self-recognition task: identifying their point-light action amongst three other point-light actors performing identical actions. We report a self-advantage effect from point-light actions, consistent with prior work in self-action recognition. Further, we found that self-recognition was modulated by the action complexity (associated with the degree of motor planning in performed actions) and individual differences linked to motor imagery and subclinical autism and schizotypy. Using dynamic time warping, we found sparse evidence in support of visual distinctiveness as a primary contributor to self-recognition, though speed distinctiveness negatively influenced self-recognition performance. Together, our results reveal that self-action recognition involves more than an awareness of visually distinct movements, with important implications for how the motor system may be involved.

Despite different etiologies, people with schizophrenia (SCZ) or with traumatic brain injury (TBI) both show aberrant neuroplasticity. One neuroplastic mechanism that may be affected is prediction error coding. We used a roving mismatch negativity (rMMN) paradigm which uses different lengths of standard tone trains and is optimized to assess predictive coding. Twenty-five SCZ, 22 TBI (mild to moderate), and 25 healthy controls were assessed. We used a frequency-deviant rMMN in which the number of standards preceding the deviant was either 2, 6, or 36. We evaluated repetition positivity to the standard tone immediately preceding a deviant tone (repetition positivity [RP], to assess formation of the memory trace), deviant negativity to the deviant stimulus (deviant negativity [DN], which reflects signaling of a prediction error), and the difference wave between the 2 (the MMN). We found that SCZ showed reduced DN and MMN compared with healthy controls and with people with mild to moderate TBI. We did not detect impairments in any index (RP, DN, or MMN) in people with TBI compared to controls. Our findings suggest that prediction error coding assessed with rMMN is aberrant in SCZ but intact in TBI, though there is a suggestion that severity of head injury results in poorer prediction error coding.

For a long time, it was proposed that schizophrenia (SCZ) patients rely more on sensory input and less on prior information, potentially leading to reduced serial dependence-ie, a reduced influence of prior stimuli in perceptual tasks. However, existing evidence is constrained to a few paradigms, and whether reduced serial dependence reflects a general characteristic of the disease remains unclear.

We investigated serial dependence in 26 SCZ patients and 27 healthy controls (CNT) to evaluate the influence of prior stimuli in a classic visual orientation adjustment task, a paradigm not previously tested in this context.

As expected, the CNT group exhibited clear serial dependence, with systematic biases toward the orientation of stimuli shown in the preceding trials. Serial dependence in SCZ patients was largely comparable to that in the CNT group.

These findings challenge the prevailing notion of reduced serial dependence in SCZ, suggesting that observed differences between healthy CNT and patients may depend on aspects of perceptual or cognitive processing that are currently not understood.

The human need to find meaning in life and the human need for connection may be two sides of the same coin, a coin forged in the developmental crucible of attachment. Our need for meaningfulness can be traced to our developmental need for connection in the attachment relationship. The free energy principle dictates that in order to resist a natural tendency towards disorder self-organizing systems must generate models that predict the hidden causes of phenomenal experience. In other words, they must make sense of things. In both an evolutionary and ontogenetic sense, the narrative self develops as a model that makes sense of experience. However, the self-model skews the interpretation of experience towards that which is predictable, or already "known." One may say it causes us to "take things personally." Meaning is felt more acutely when defenses are compromised, when the narrative self is offline. This enables meaning-making that is less egocentrically motivated. Dreams, psychosis, and psychedelic states offer glimpses of how we make sense of things absent a coherent narrative self. This has implications for the way we understand such states, and lays bare the powerful reach of attachment in shaping what we experience as meaningful.

Hypnosis is an effective intervention with proven efficacy that is employed in clinical settings and for investigating various cognitive processes. Despite their practical success, no consensus exists regarding the mechanisms underlying well-established hypnotic phenomena. Here, we suggest a new framework called the Simulation-Adaptation Theory of Hypnosis (SATH). SATH expands the predictive coding framework by focusing on (a) redundancy elimination in generative models using intrinsically generated prediction errors, (b) adaptation due to amplified or prolonged neural activity, and (c) using internally generated predictions as a venue for learning new associations. The core of our treatise is that simulating proprioceptive, interoceptive, and exteroceptive signals, along with the top-down attenuation of the precision of sensory prediction errors due to neural adaptation, can explain objective and subjective hypnotic phenomena. Based on these postulations, we offer mechanistic explanations for critical categories of direct verbal suggestions, including (1) direct-ideomotor, (2) challenge-ideomotor, (3) perceptual, and (4) cognitive suggestions. Notably, we argue that besides explaining objective responses, SATH accounts for the subjective effects of suggestions, i.e., the change in the sense of agency and reality. Finally, we discuss individual differences in hypnotizability and how SATH accommodates them. We believe that SATH is exhaustive and parsimonious in its scope, can explain a wide range of hypnotic phenomena without contradiction, and provides a host of testable predictions for future research.

Flow has been described as a state of optimal performance, experienced universally across a broad range of domains: from art to athletics, gaming to writing. However, its phenomenal characteristics can, at first glance, be puzzling. Firstly, individuals in flow supposedly report a loss of self-awareness, even though they perform in a manner which seems to evince their agency and skill. Secondly, flow states are felt to be effortless, despite the prerequisite complexity of the tasks that engender them. In this paper, we unpick these features of flow, as well as others, through the active inference framework, which posits that action and perception are forms of active Bayesian inference directed at sustained self-organisation; i.e., the minimisation of variational free energy. We propose that the phenomenology of flow is rooted in the deployment of high precision weight over (i) the expected sensory consequences of action and (ii) beliefs about how action will sequentially unfold. This computational mechanism thus draws the embodied cognitive system to minimise the ensuing (i.e., expected) free energy through the exploitation of the pragmatic affordances at hand. Furthermore, given the challenging dynamics the flow-inducing situation presents, attention must be wholly focussed on the unfolding task whilst counterfactual planning is restricted, leading to the attested loss of the sense of self-as-object. This involves the inhibition of both the sense of self as a temporally extended object and higher-order, meta-cognitive forms of self-conceptualisation. Nevertheless, we stress that self-awareness is not entirely lost in flow. Rather, it is pre-reflective and bodily. Our approach to bodily-action-centred phenomenology can be applied to similar facets of seemingly agentive experience beyond canonical flow states, providing insights into the mechanisms of so-called selfless experiences, embodied expertise and wellbeing.

Mismatch negativity (MMN) is an event-related potential component automatically elicited by events that violate predictions based on prior events. To elicit this component, researchers use stimulus repetition to induce predictions, and the MMN is obtained by subtracting the brain response to rare or unpredicted stimuli from that of frequent stimuli. Under the Predictive Processing framework, one increasingly popular interpretation of the mismatch response postulates that MMN represents a prediction error. In this context, the reduced MMN amplitude to auditory stimuli has been considered a potential biomarker of Schizophrenia, representing a reduced prediction error and the inability to update the mental model of the world based on the sensory signals. It is unclear, however, whether this amplitude reduction is specific for auditory events or if the visual MMN reveals a similar pattern in schizophrenia spectrum disorder. This review and meta-analysis aimed to summarise the available literature on the vMMN in schizophrenia. A systematic literature search resulted in 10 eligible studies that resulted in a combined effect size of g = -.63, CI [-.86, -.41], reflecting lower vMMN amplitudes in patients. These results are in line with the findings in the auditory domain. This component offers certain advantages, such as less susceptibility to overlap with components generated by attentional demands. Future studies should use vMMN to explore abnormalities in the Predictive Processing framework in different stages and groups of the SSD and increase the knowledge in the search for biomarkers in schizophrenia.

Previous longitudinal magnetic resonance imaging studies have shown progressive gray matter (GM) reduction during the earliest phases of schizophrenia. It is unknown whether these progressive processes are homogeneous in all groups of patients. One way to obtain more valid findings is to focus on the symptoms. Auditory hallucinations (AHs) are frequent and reliable symptoms of psychosis. The present study aims to analyze whether longitudinal changes in structural abnormalities in cortical regions are related to the presence of AHs and the intensity of psychotic symptoms in a large sample.

A Magnetic Resonance (MR) voxel-based morphometry analysis was applied to a group of 128 first episodes psychosis (FEP) patients (63 patients with AHs and 65 patients without AHs) and 78 matched healthy controls at baseline and at a 2-year follow-up.

At baseline, FEP patients exhibited significant GM volume reductions in the temporal, frontal and precentral regions. At follow-up, FEP patients exhibited GM volume changes in the temporal, Rolandic, frontal, precentral and insula regions. At baseline, no significant differences were found between FEP patients with and without AHs. At follow-up, while FEP patients with AHs showed less GM volume in temporal and frontal lobes, non-AH FEP patients showed reductions in the frontal, precentral and fusiform areas. PANSS scores showed statistically significant correlations with GM volume reductions at baseline and follow-up.

Brain cortical loss in the early phases of psychosis is not associated with potentially transitory AHs; however, brain structural changes may emerge as AHs appear in chronic patients.

Slower perceptual alternations, a notable perceptual effect observed in psychiatric disorders, can be alleviated by antidepressant therapies that affect serotonin levels in the brain. While these phenomena have been well documented, the underlying neurocognitive mechanisms remain to be elucidated. Our study bridges this gap by employing a computational cognitive approach within a Bayesian predictive coding framework to explore these mechanisms in depression. We fitted a prediction error (PE) model to behavioral data from a binocular rivalry task, uncovering that significantly higher initial prior precision and lower PE led to a slower switch rate in patients with depression. Furthermore, serotonin-targeting antidepressant treatments significantly decreased the prior precision and increased PE, both of which were predictive of improvements in the perceptual alternation rate of depression patients. These findings indicated that the substantially slower perception switch rate in patients with depression was caused by the greater reliance on top-down priors and that serotonin treatment's efficacy was in its recalibration of these priors and enhancement of PE. Our study not only elucidates the cognitive underpinnings of depression, but also suggests computational modeling as a potent tool for integrating cognitive science with clinical psychology, advancing our understanding and treatment of cognitive impairments in depression.

The N400 event-related component has been widely used to investigate the neural mechanisms underlying real-time language comprehension. However, despite decades of research, there is still no unifying theory that can explain both its temporal dynamics and functional properties. In this work, we show that predictive coding - a biologically plausible algorithm for approximating Bayesian inference - offers a promising framework for characterizing the N400. Using an implemented predictive coding computational model, we demonstrate how the N400 can be formalized as the lexico-semantic prediction error produced as the brain infers meaning from the linguistic form of incoming words. We show that the magnitude of lexico-semantic prediction error mirrors the functional sensitivity of the N400 to various lexical variables, priming, contextual effects, as well as their higher-order interactions. We further show that the dynamics of the predictive coding algorithm provides a natural explanation for the temporal dynamics of the N400, and a biologically plausible link to neural activity. Together, these findings directly situate the N400 within the broader context of predictive coding research. More generally, they raise the possibility that the brain may use the same computational mechanism for inference across linguistic and non-linguistic domains.