A new predictive coding model for a more comprehensive account of delusions.

Attempts to understand psychosis-the experience of profoundly altered perceptions and beliefs-raise questions about how the brain models the world. Standard predictive coding approaches suggest that it does so by minimising mismatches between incoming sensory evidence and predictions. By adjusting predictions, we converge iteratively on a best guess of the nature of the reality. Recent arguments have shown that a modified version of this framework-hybrid predictive coding-provides a better model of how healthy agents make inferences about external reality. We suggest that this more comprehensive model gives us a richer understanding of psychosis compared with standard predictive coding accounts. In this Personal View, we briefly describe the hybrid predictive coding model and show how it offers a more comprehensive account of the phenomenology of delusions, thereby providing a potentially powerful new framework for computational psychiatric approaches to psychosis. We also make suggestions for future work that could be important in formalising this novel perspective.

Characterising modulatory effects of high-intensity high frequency transcranial random noise stimulation using the perceptual template model.

Neural noise is an inherent property of all nervous systems. However, our understanding of the mechanisms by which noise influences perception is still limited. To elucidate this relationship, we require techniques that can safely modulate noise in humans. Transcranial random noise stimulation (tRNS) has been proposed to induce noise into cortical processing areas according to the principles of stochastic resonance (SR). Specifically, it has been demonstrated that small to moderate intensities of noise improve performance. To date, however, high intensity tRNS effects on neural noise levels have not been directly quantified, nor have the detrimental effects proposed by SR been demonstrated in early visual function. Here, we applied 3 mA high-frequency tRNS to primary visual cortex during an orientation-discrimination task across increasing external noise levels and used the Perceptual Template Model to quantify the mechanisms by which noise changes perceptual performance in healthy observers. Results show that, at a group level, high-intensity tRNS worsened perceptual performance. Our computational analysis reveals that this change in performance was underpinned by an increased amount of additive noise and a reduced ability to filter external noise compared to sham stimulation. Interestingly, while most observers experienced detrimental effects, a subset of participants demonstrated improved performance. Preliminary evidence suggests that differences in baseline internal noise levels might account for these individual differences. Together, these results refine our understanding of the mechanisms underlying the influence of neural noise on perception and have important implications for the application of tRNS as a research tool.

Knowledge-driven perceptual organization reshapes information sampling via eye movements.

Humans constantly move their eyes to explore the environment. However, how image-computable features and object representations contribute to eye-movement control is an ongoing debate. Recent developments in object perception indicate a complex relationship between features and object representations, where image-independent object knowledge generates objecthood by reconfiguring how feature space is carved up. Here, we adopt this emerging perspective, asking whether object-oriented eye movements result from gaze being guided by image-computable features, or by the fact that these features are bound into an object representation. We recorded eye movements in response to stimuli that initially appear as meaningless patches but are experienced as coherent objects once relevant object knowledge has been acquired. We demonstrate that fixations on identical images are more object-centered, less dispersed, and more consistent across observers once these images are organized into objects. Gaze guidance also showed a shift from exploratory information sampling to exploitation of object-related image areas. These effects were evident from the first fixations onwards. Importantly, eye movements were not fully determined by knowledge-dependent object representations but were best explained by the integration of these representations with image-computable features. Overall, the results show how information sampling via eye movements is guided by a dynamic interaction between image-computable features and knowledge-driven perceptual organization. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

White matter microstructure in face and body networks predicts facial expression and body posture perception across development.

Facial expression and body posture recognition have protracted developmental trajectories. Interactions between face and body perception, such as the influence of body posture on facial expression perception, also change with development. While the brain regions underpinning face and body processing are well-defined, little is known about how white-matter tracts linking these regions relate to perceptual development. Here, we obtained complementary diffusion magnetic resonance imaging (MRI) measures (fractional anisotropy [FA], spherical mean Sµ ), and a quantitative MRI myelin-proxy measure (R1), within white-matter tracts of face- and body-selective networks in children and adolescents and related these to perceptual development. In tracts linking occipital and fusiform face areas, facial expression perception was predicted by age-related maturation, as measured by Sµ and R1, as well as age-independent individual differences in microstructure, captured by FA and R1. Tract microstructure measures linking posterior superior temporal sulcus body region with anterior temporal lobe (ATL) were related to the influence of body on facial expression perception, supporting ATL as a site of face and body network convergence. Overall, our results highlight age-dependent and age-independent constraints that white-matter microstructure poses on perceptual abilities during development and the importance of complementary microstructural measures in linking brain structure and behaviour.

Semantic object-scene inconsistencies affect eye movements, but not in the way predicted by contextualized meaning maps.

Semantic information is important in eye movement control. An important semantic influence on gaze guidance relates to object-scene relationships: objects that are semantically inconsistent with the scene attract more fixations than consistent objects. One interpretation of this effect is that fixations are driven toward inconsistent objects because they are semantically more informative. We tested this explanation using contextualized meaning maps, a method that is based on crowd-sourced ratings to quantify the spatial distribution of context-sensitive "meaning" in images. In Experiment 1, we compared gaze data and contextualized meaning maps for images, in which objects-scene consistency was manipulated. Observers fixated more on inconsistent versus consistent objects. However, contextualized meaning maps did not assign higher meaning to image regions that contained semantic inconsistencies. In Experiment 2, a large number of raters evaluated image-regions, which were deliberately selected for their content and expected meaningfulness. The results suggest that the same scene locations were experienced as slightly less meaningful when they contained inconsistent compared to consistent objects. In summary, we demonstrated that - in the context of our rating task - semantically inconsistent objects are experienced as less meaningful than their consistent counterparts and that contextualized meaning maps do not capture prototypical influences of image meaning on gaze guidance.

A Computational Analysis of Abnormal Belief Updating Processes and Their Association With Psychotic Experiences and Childhood Trauma in a UK Birth Cohort.

BACKGROUND: Psychotic experiences emerge from abnormalities in perception and belief formation and occur more commonly in those experiencing childhood trauma. However, which precise aspects of belief formation are atypical in psychosis is not well understood. We used a computational modeling approach to characterize belief updating in young adults in the general population, examine their relationship with psychotic outcomes and trauma, and determine the extent to which they mediate the trauma-psychosis relationship. METHODS: We used data from 3360 individuals from the Avon Longitudinal Study of Parents and Children birth cohort who completed assessments for psychotic outcomes, depression, anxiety, and two belief updating tasks at age 24 and had data available on traumatic events assessed from birth to late adolescence. Unadjusted and adjusted regression and counterfactual mediation methods were used for the analyses. RESULTS: Basic behavioral measures of belief updating (draws-to-decision and disconfirmatory updating) were not associated with psychotic experiences. However, computational modeling revealed an association between increased decision noise with both psychotic experiences and trauma exposure, although <3% of the trauma-psychotic experience association was mediated by decision noise. Belief updating measures were also associated with intelligence and sociodemographic characteristics, confounding most of the associations with psychotic experiences. There was little evidence that belief updating parameters were differentially associated with delusions compared with hallucinations or that they were differentially associated with psychotic outcomes compared with depression or anxiety. CONCLUSIONS: These findings challenge the hypothesis that atypical belief updating mechanisms (as indexed by the computational models and behavioral measures we used) underlie the development of psychotic phenomena.

There is no evidence that meaning maps capture semantic information relevant to gaze guidance: Reply to Henderson, Hayes, Peacock, and Rehrig (2021).

The concerns raised by Henderson, Hayes, Peacock, and Rehrig (2021) are based on misconceptions of our work. We show that Meaning Maps (MMs) do not predict gaze guidance better than a state-of-the-art saliency model that is based on semantically-neutral, high-level features. We argue that there is therefore no evidence to date that MMs index anything beyond these features. Furthermore, we show that although alterations in meaning cause changes in gaze guidance, MMs fail to capture these alterations. We agree that semantic information is important in the guidance of eye-movements, but the contribution of MMs for understanding its role remains elusive.

Low-level, prediction-based sensory and motor processes are unimpaired in Autism.

A new promising account of human brain function suggests that sensory cortices try to optimise information processing via predictions that are based on prior experiences. The brain is thus likened to a probabilistic prediction machine. There has been a growing - though inconsistent - literature to suggest that features of autism spectrum conditions (ASCs) are associated with a deficit in modelling the world through such prediction-based inference. However empirical evidence for differences in low-level sensorimotor predictions in autism is still lacking. One approach to examining predictive processing in the sensorimotor domain is in the context of self-generated (predictable) as opposed to externally-generated (less predictable) effects. We employed two complementary tasks - forcematching and intentional binding - which examine self-versus externally-generated action effects in terms of sensory attenuation and intentional binding respectively in adults with and without autism. The results show that autism was associated with normal levels of sensory attenuation of internally-generated force and with unaltered temporal attraction of voluntary actions and their outcomes. Thus, our results do not support a general deficit in predictive processing in autism.

Childhood trauma and cognitive biases associated with psychosis: A systematic review and meta-analysis.

Childhood trauma is associated with an increased risk of psychosis, but the mechanisms that mediate this relationship are unknown. Exposure to trauma has been hypothesised to lead to cognitive biases that might have causal effects on psychotic symptoms. The literature on whether childhood trauma is associated with psychosis-related cognitive biases has not been comprehensively reviewed. A systematic review and meta-analysis or narrative synthesis of studies examining the association between childhood trauma and the following biases: external locus of control (LOC), external attribution, probabilistic reasoning, source monitoring, top-down processing, and bias against disconfirmatory evidence. Studies were assessed for quality, and sources of heterogeneity were explored. We included 25 studies from 3,465 studies identified. Individuals exposed to childhood trauma reported a more external LOC (14 studies: SMD Median = 0.40, Interquartile range 0.07 to 0.52), consistent with a narrative synthesis of 11 other studies of LOC. There was substantial heterogeneity in the meta-analysis (I2 = 93%) not explained by study characteristics examined. Narrative syntheses for other biases showed weaker, or no evidence of association with trauma. The quality of included studies was generally low. Our review provides some evidence of an association between childhood trauma and a more external LOC, but not with the other biases examined. The low quality and paucity of studies for most of the cognitive biases examined highlights the need for more rigorous studies to determine which biases occur after trauma, and whether they mediate an effect of childhood trauma on psychosis.

Meaning maps and saliency models based on deep convolutional neural networks are insensitive to image meaning when predicting human fixations.

Eye movements are vital for human vision, and it is therefore important to understand how observers decide where to look. Meaning maps (MMs), a technique to capture the distribution of semantic information across an image, have recently been proposed to support the hypothesis that meaning rather than image features guides human gaze. MMs have the potential to be an important tool far beyond eye-movements research. Here, we examine central assumptions underlying MMs. First, we compared the performance of MMs in predicting fixations to saliency models, showing that DeepGaze II - a deep neural network trained to predict fixations based on high-level features rather than meaning - outperforms MMs. Second, we show that whereas human observers respond to changes in meaning induced by manipulating object-context relationships, MMs and DeepGaze II do not. Together, these findings challenge central assumptions underlying the use of MMs to measure the distribution of meaning in images.

Forms of prediction in the nervous system.

The idea that predictions shape how we perceive and comprehend the world has become increasingly influential in the field of systems neuroscience. It also forms an important framework for understanding neuropsychiatric disorders, which are proposed to be the result of disturbances in the mechanisms through which prior information influences perception and belief, leading to the production of suboptimal models of the world. There is a widespread tendency to conceptualize the influence of predictions exclusively in terms of 'top-down' processes, whereby predictions generated in higher-level areas exert their influence on lower-level areas within an information processing hierarchy. However, this excludes from consideration the predictive information embedded in the 'bottom-up' stream of information processing. We describe evidence for the importance of this distinction and argue that it is critical for the development of the predictive processing framework and, ultimately, for an understanding of the perturbations that drive the emergence of neuropsychiatric symptoms and experiences.

Publisher Correction: Forms of prediction in the nervous system.

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

Inability to improve performance with control shows limited access to inner states.

Any repeatedly performed action is characterized by endogenous variability, affecting both speed and accuracy-for a large part presumably caused by fluctuations in underlying brain and body states. The current research questions concerned (a) whether such states are accessible to us and (b) whether we can act upon this information to reduce variability. For example, when playing a game of darts, there is an implicit assumption that people can wait to throw until they are in the right perceptual-attentional state. If this is true, taking away the ability to self-pace the game should worsen performance. We first tested precisely this assumption asking participants to play darts in a self-paced and a fixed-paced condition. There was no benefit of self-pacing, showing that participants were unable to use such control to improve their performance and reduce their variability. Next, we replicated these findings in 2 computer-based tasks, in which participants performed a rapid action-selection and a visual detection task in 1 self-paced and 3 forced-paced conditions. Over 4 different empirical tests, we show that the self-paced condition did not lead to improved performance or reduced variability, nor to reduced temporal dependencies in the reaction time (RT) series. Overall, it seems that, if people have any access to their fluctuating performance-relevant inner states, this access is limited and not relevant for upcoming performance. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Disaggregating physiological components of cortisol output: A novel approach to cortisol analysis in a clinical sample - A proof-of-principle study.

Although childhood adversity (CA) increases risk for subsequent mental illnesses, developmental mechanisms underpinning this association remain unclear. The hypothalamic-pituitary-adrenal axis (HPAA) is one candidate system potentially linking CA with psychopathology. However, determining developmental effects of CA on HPAA output and differentiating these from effects of current illness has proven difficult. Different aspects of HPAA output are governed by differentiable physiological mechanisms. Disaggregating HPAA output according to its biological components (baseline tonic cortisol, background diurnal variation, phasic stress response) may improve precision of associations with CA and/or psychopathology. In a novel proof-of-principle investigation we test whether different predictors, CA (distal risk factor) and current depressive symptoms, show distinct associations with dissociable HPAA components. A clinical group (aged 16-25) at high-risk for developing severe psychopathology (n = 20) were compared to age and sex matched healthy controls (n = 21). Cortisol was measured at waking (x4), following stress induction (x8), and during a time-environment-matched non-stress condition. Using piecewise multilevel modeling, stress responses were disaggregated into increase and decrease, while controlling for waking cortisol, background diurnal output and confounding variables. Elevated waking cortisol was specifically associated with higher CA scores. Higher non-stress cortisol was specifically associated with higher depressive scores. Following stress induction, depressive symptoms attenuated cortisol increase, whilst CA attenuated cortisol decrease. The results support a differential HPAA dysregulation hypothesis where physiologically dissociable components of HPAA output are differentially associated with distal (CA) or proximal (depressive symptoms) predictors. This proof-of-principle study demonstrates that future cortisol analyses need to disaggregate biologically independent mechanisms of HPAA output.

A hierarchical model of social perception: Psychophysical evidence suggests late rather than early integration of visual information from facial expression and body posture.

Facial expressions are one of the most important sources of information about another's emotional states. More recently, other cues such as body posture have been shown to influence how facial expressions are perceived. It has been argued that this biasing effect is underpinned by an early integration of visual information from facial expression and body posture. Here, we replicate this biasing effect, but, using a psychophysical procedure, show that adaptation to facial expressions is unaffected by body context. The integration of face and body information therefore occurs downstream of the sites of adaptation, known to be localised in high-level visual areas of the temporal lobe. Contrary to previous research, our findings thus provide direct evidence for late integration of information from facial expression and body posture. They are consistent with a hierarchical model of social perception, in which social signals from different sources are initially processed independently and in parallel by specialised visual mechanisms. Integration of these different inputs in later stages of the visual system then supports the emergence of the integrated whole-person percept that is consciously experienced.

Association of Trauma Type, Age of Exposure, and Frequency in Childhood and Adolescence With Psychotic Experiences in Early Adulthood.

Importance: Cross-sectional and longitudinal studies have consistently reported associations between childhood trauma and psychotic experiences and disorders. However, few studies have examined whether the age of exposure or specific trauma types are differently associated with the risk of developing psychotic experiences. Objective: To examine whether exposure to trauma, assessed at multiple age periods between 0 and 17 years of age, is associated with an increased risk of psychotic experiences by age 18 years and whether this association varies according to trauma type as well as age and frequency of exposure. Design, Setting, and Participants: This study used data from the Avon Longitudinal Study of Parents and Children, a large population-based birth cohort in the United Kingdom that recruited women who resided in the Avon Health Authority area and had an expected delivery date between April 1, 1991, and December 31, 1992. Data on psychotic experiences were included in the study, along with trauma variables derived from assessments completed by the parents or self-reported by the participants. The variables represent exposure to any trauma type between ages 0 and 17 years; any trauma type within a distinct age period: early childhood (0-4.9 years), middle childhood (5-10.9 years), or adolescence (11-17 years); specific trauma types between ages 0 and 17 years; and specific trauma types within early childhood, middle childhood, or adolescence. Data were analyzed from January 9, 2017, to November 30, 2017. Main Outcomes and Measures: Suspected or definite psychotic experiences were assessed using the psychosis-like symptoms semistructured interview at age 12 years and then at age 18 years. Results: The sample of 4433 participants included 2504 (56.5%) females, with a mean (SD) age of 17.8 (0.38) years. Exposure to any trauma up to age 17 years was associated with increased odds of psychotic experiences at age 18 years (adjusted odds ratio, 2.91; 95% CI, 2.15-3.93). All trauma types from age 0 to 17 years were associated with an increased odds of psychotic experiences. The population-attributable fraction for childhood and adolescent trauma on psychotic experiences at age 18 years was 45% (95% CI, 25%-60%). Effect sizes for most trauma types were greater for exposure that was more proximal to the outcome, although CIs overlapped with those for more distal trauma. Evidence supported dose-response associations for exposure to multiple trauma types and at multiple age periods. In an analysis aimed at minimizing reverse causality, adolescent trauma was also associated with past-year incident psychotic experiences at age 18 years. Conclusions and Relevance: These findings are consistent with the thesis that trauma could have a causal association with psychotic experiences; if so, identification of modifiable mediators is required to inform prevention strategies.

Prior object-knowledge sharpens properties of early visual feature-detectors.

Early stages of visual processing are carried out by neural circuits activated by simple and specific features, such as the orientation of an edge. A fundamental question in human vision is how the brain organises such intrinsically local information into meaningful properties of objects. Classic models of visual processing emphasise a one-directional flow of information from early feature-detectors to higher-level information-processing. By contrast to this view, and in line with predictive-coding models of perception, here, we provide evidence from human vision that high-level object representations dynamically interact with the earliest stages of cortical visual processing. In two experiments, we used ambiguous stimuli that, depending on the observer's prior object-knowledge, can be perceived as either coherent objects or as a collection of meaningless patches. By manipulating object knowledge we were able to determine its impact on processing of low-level features while keeping sensory stimulation identical. Both studies demonstrate that perception of local features is facilitated in a manner consistent with an observer's high-level object representation (i.e., with no effect on object-inconsistent features). Our results cannot be ascribed to attentional influences. Rather, they suggest that high-level object representations interact with and sharpen early feature-detectors, optimising their performance for the current perceptual context.

Sensory Neuroscience: Linking Dopamine, Expectation, and Hallucinations.

Psychosis is associated with a dysregulation of the brain's dopamine-mediated neurotransmitter system. Yet, specific mechanisms underlying psychotic symptoms are not well understood. A new study has now uncovered a dopamine-dependent mechanism that explains why psychotic patients experience hallucinations.