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Individual differences in probabilistic learning and updating predictive representations in individuals with obsessive-compulsive tendencies

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BMC PSYCHIATRY 2025年第1期25卷 1-17页

作者： Brezoczki, Bianka Farkas, Bence Csaba Hann, Flora Pesthy, Orsolya Toth-Faber, Eszter Farkas, Kinga Csigo, Katalin Nemeth, Dezso Vekony, Teodora Eotvos Lorand Univ Doctoral Sch Psychol Budapest Hungary Eotvos Lorand Univ Inst Psychol Budapest Hungary HUN REN Res Ctr Nat Sci Inst Cognit Neurosci & Psychol Brain Memory & Language Res Grp Budapest Hungary Inst Psychotraumatisme Enfant & Adolescent Conseil Dept & Yvelines & Hauts de Seine Versailles France Ctr Hosp Versailles Versailles France Univ Paris Saclay Ctr Rech Epidemiol & Sante Populat UVSQ Inserm Versailles France PSL Res Univ Ecole Normale Super Dept Etud Cognit LNCINSERM Paris France HUN REN Res Ctr Nat Sci Inst Expt Med Budapest Hungary Univ Claude Bernard Lyon 1 Ctr Rech Neurosci Lyon CNRS INSERMUMR5292CRNLU1028 Bron France Semmelweis Univ Dept Psychiat & Psychotherapy Budapest Hungary Nyiro Gyula Natl Inst Psychiat & Addictol Budapest Hungary Pazmany Peter Catholic Univ Inst Psychol Budapest Hungary Eotvos Lorand Univ Inst Psychol BML NAP Res Grp Budapest Hungary HUN REN Res Ctr Nat Sci Inst Cognit Neurosc & Psychol Budapest Hungary Univ Atlantico Medio Gran Canaria Cognit Res Ctr Dept Educ & Psychol Las Palmas Gran Canaria Spain

BackgroundObsessive-compulsive (OC) tendencies involve intrusive thoughts and rigid, repetitive behaviours that also manifest at the subclinical level in the general population. The neurocognitive factors driving the development and persistence of the excessive presence of these tendencies remain highly elusive, though emerging theories emphasize the role of implicit information processing. Despite various empirical studies on distinct neurocognitive processes, the incidental retrieval of environmental structures in dynamic and noisy environments, such as probabilistic learning, has received relatively little *** this study, we aimed to unravel potential individual differences in implicit probabilistic learning and the updating of predictive representations related to OC tendencies in a non-clinical population. We conducted two independent online experiments (NStudy1 = 164, NStudy2 = 256) with university students. Probabilistic learning was assessed using an implicit visuomotor probabilistic learning task, involving sequences with second-order non-adjacent *** findings revealed that implicit probabilistic learning remained remarkably robust among OC tendencies within a non-clinical population. Furthermore, the results highlighted effective updating capabilities of predictive representations, which were not influenced by OC *** results offer new insights into individual differences in probabilistic learning and updating in relation to OC tendencies, contributing to theoretical, methodological, and practical approaches for understanding the maladaptive behavioural manifestations of OC disorder and subclinical tendencies.

关键词： Obsessive-compulsive tendencies Obsessive-compulsive disorder Probabilistic learning predictive processing Individual differences Statistical learning

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The specificity of sequential statistical learning: Statistical learning accumulates predictive information from unstructured input but is dissociable from (declarative) memory for words

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COGNITION 2025年 261卷 106130页

作者： Endress, Ansgar D. de Seyssel, Maureen City St Georges Univ London Dept Psychol Northampton Sq London EC1V 0HB England PSL Univ CNRS EHESS ENSLab Sci Cognit & PsycholinguistDept Etud Cogn Paris France Univ Paris Cite CNRS Lab Linguist Formelle Paris France

Learning statistical regularities from the environment is ubiquitous across domains and species. It might support the earliest stages of language acquisition, especially identifying and learning words from fluent speech (i.e., word-segmentation). But how do the statistical learning mechanisms involved in word-segmentation interact with the memory mechanisms needed to remember words - and with the learning situations where words need to be learned? Through computational modeling, we first show that earlier results purportedly supporting memory-based theories of statistical learning can be reproduced by memory-less Hebbian learning mechanisms. We then show that, in a memory recall task after exposure to continuous, statistically structured speech sequences, participants track the statistical structure of the speech sequences and are thus sensitive to probable syllable transitions. However, they hardly remember any items at all, with 82% producing no high-probability items. Among the 30% of participants producing (correct) high-or (incorrect) low-probability items, half produced high-probability items and half low-probability items - even while preferring high-probability items in a recognition test. Only discrete familiarization sequences with isolated words yield memories of actual items. Turning to how specific learning situations affect statistical learning, we show that it predominantly operates in continuous speech sequences like those used in earlier experiments, but not in discrete chunk sequences likely more characteristic of early language acquisition. Taken together, these results suggest that statistical learning might be specialized to accumulate distributional information, but that it is dissociable from the (declarative) memory mechanisms needed to acquire words and does not allow learners to identify probable word boundaries.

关键词： Statistical learning Declarative memory predictive processing Language acquisition Hebbian learning

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Altered category learning and reduced generalization in autistic adults

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AUTISM RESEARCH 2025年第2期18卷 295-311页

作者： Van Overwalle, Jaana van der Donck, Stephanie Geusens, Birte Boets, Bart Wagemans, Johan Katholieke Univ Leuven Leuven Brain Inst Dept Brain & Cognit B-3000 Leuven Belgium Katholieke Univ Leuven Leuven Autism Res LAuRes Leuven Belgium Katholieke Univ Leuven Leuven Brain Inst Ctr Dev Psychiat Leuven Belgium

Individuals with autism spectrum condition (ASC) are suggested to experience difficulties with categorization and generalization. However, empirical studies have mainly focused on one process at a time, and neglected underlying neural mechanisms. Here, we investigated categorization and generalization at a behavioral and neural level in 38 autistic and 38 neurotypical (NT) adults. By presenting shapes sampled from an artificial multidimensional stimulus space, we investigated (1) behavioral and neural underpinnings of category learning and (2) behavioral generalization of trained categorization to both an extended version of the stimulus space and a novel stimulus space. Our previous findings showed that individuals with autism were slower in category learning. In this study, we demonstrate that this slower learning in autism was not related to differences in applied categorization strategy. In contrast, electroencephalography recordings during training did reveal a reduced amplitude of the N1 component in the right occipital temporal cortex after stimulus presentation in autistic participants, which suggests atypical categorical proficiency. In addition, we observed delayed and higher activation in the frontal regions after receiving (negative) feedback in the autistic group, potentially suggesting more explicit feedback processing or a higher salience of prediction errors in autism. Finally, autistic and NT individuals were able to generalize their learned categorization after training. However, when generalizing to a novel set of shapes, autistic individuals were significantly less accurate. Reduced generalization significantly correlated with increased intolerance to uncertainty scores. This multi-level approach reveals behavioral and neural differences in learning and generalization that could be related to clinical symptoms in autism.

关键词： autism categorization electroencephalography generalization intolerance to uncertainty perceptual learning predictive processing

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Unexpected Twists: Electrophysiological Correlates of Encoding and Retrieval of Events Eliciting Prediction Error

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PSYCHOPHYSIOLOGY 2025年第1期62卷 e14752页

作者： Turan, Goezem Spiertz, Veronika Bein, Oded Shing, Yee Lee Nolden, Sophie Goethe Univ Frankfurt Dept Psychol Frankfurt Germany DIPF Leibniz Inst Res & Informat Educ IDeA Ctr Individual Dev & Adapt Educ Frankfurt Germany Princeton Univ Princeton Neurosci Inst Princeton NJ USA Weill Cornell Med Dept Psychiat Weill Cornell Inst Geriatr Psychiat New York NY USA

According to the predictive processing framework, our brain constantly generates predictions based on past experiences and compares these predictions with incoming sensory information. When an event contradicts these predictions, it results in a prediction error (PE), which has been shown to enhance subsequent memory. However, the neural mechanisms underlying the influence of PEs on subsequent memory remain unclear. This study investigated the electrophysiological correlates during encoding and retrieval of events eliciting PEs. We employed a statistical learning task in which participants were presented with pairs of objects in sequence. Subsequently, while recording electroencephalography (EEG), we introduced PEs by replacing the second object of each pair with new objects and we then tested the participants' memory. Behaviorally, PEs did not enhance memory. During retrieval, we observed higher amplitudes in the recollection-related late positive component for violation items that were remembered compared to those that were forgotten. In contrast, no evidence for the presence of the FN400 component associated with familiarity was found. These results suggest that recollection, but not familiarity, plays a crucial role in the interplay between PE and memory. Contrary to our hypothesis, we did not observe a relationship between PEs and the P3 component during encoding. In conclusion, our study contributes to the growing body of knowledge concerning the intricate relationship between PEs and episodic memory. It sheds light on the underlying neural mechanisms involved and emphasizes the importance of recollection in this context.

关键词： electroencephalography episodic memory event-related potentials prediction error predictive processing statistical learning

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Cellular psychology: relating cognition to context-sensitive pyramidal cells

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TRENDS IN COGNITIVE SCIENCES 2025年第1期29卷 28-40页

作者： Phillips, William A. Bachmann, Talis Spratling, Michael W. Muckli, Lars Petro, Lucy S. Zolnik, Timothy Univ Stirling Fac Nat Sci Psychol Stirling FK9 4LA England Univ Tartu Inst Psychol Tartu Estonia Univ Luxembourg Dept Behav & Cognit Sci L-4366 Esch Belval Luxembourg Univ Glasgow Coll Med Vet & Life Sci Ctr Cognit Neuroimaging Sch Psychol & Neurosci Glasgow G12 8QB Scotland Univ Glasgow Coll Med Vet & Life Sci Imaging Ctr Excellence Glasgow Scotland Queen Elizabeth Univ Hosp Glasgow Scotland Charite Univ Med Berlin Dept Biochem D-10117 Berlin Germany Humboldt Univ Dept Biol D-10117 Berlin Germany

'Cellular psychology' is a new field of inquiry that studies dendritic mechanisms for adapting mental events to the current context, thus increasing their coherence, flexibility, effectiveness, and comprehensibility. Apical dendrites of neocortical pyramidal cells have a crucial role in cognition - those dendrites receive input from diverse sources, including feedback, and can amplify the cell's feedforward transmission if relevant in that context. Specialized subsets of inhibitory interneurons regulate this cooperative context-sensitive processing by increasing or decreasing amplification. Apical input has different effects on cellular output depending on whether we are awake, deeply asleep, or dreaming. Furthermore, wakeful thought and imagery may depend on apical input. Highresolution neuroimaging in humans supports and complements evidence on these cellular mechanisms from other mammals.

关键词： cellular psychology context-sensitive disambiguation apical amplification apical drive mental state predictive processing

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Counteracting uncertainty: exploring the impact of anxiety on updating predictions about environmental states

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BIOLOGICAL CYBERNETICS 2025年第2-3期119卷 1-16页

作者： Harris, David Arthur, Tom Wilson, Mark Le Gallais, Ben Parsons, Thomas Dill, Ally Vine, Sam Univ Exeter Sch Publ Hlth & Sport Sci Med Sch St Lukes Campus Exeter EX1 2LU England

Anxious emotional states disrupt decision-making and control of dexterous motor actions. Computational work has shown that anxiety-induced uncertainty alters the rate at which we learn about the environment, but the subsequent impact on the predictive beliefs that drive action control remains to be understood. In the present work we tested whether anxiety alters predictive (oculo)motor control mechanisms. Thirty participants completed an experimental task that consisted of manual interception of a projectile performed in virtual reality. Participants were subjected to conditions designed to induce states of high or low anxiety using performance incentives and social-evaluative pressure. We measured subsequent effects on physiological arousal, self-reported state anxiety, and eye movements. Under high pressure conditions we observed visual sampling of the task environment characterised by higher variability and entropy of position prior to release of the projectile, consistent with an active attempt to reduce uncertainty. Computational modelling of predictive beliefs, using gaze data as inputs to a partially observable Markov decision process model, indicated that trial-to-trial updating of predictive beliefs was reduced during anxiety, suggesting that updates to priors were constrained. Additionally, state anxiety was related to a less deterministic mapping of beliefs to actions. These results support the idea that organisms may attempt to counter anxiety-related uncertainty by moving towards more familiar and certain sensorimotor patterns.

关键词： Gaze Stress Eye tracking Bayesian predictive processing

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Bayesian brain theory: Computational neuroscience of belief

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NEUROSCIENCE 2025年 566卷 198-204页

作者： Bottemanne, Hugo Univ Paris Saclay Fac Med Paris Saclay CESP Ctr Rech Epidemiol & Sante Populat MOODS TeamINSERM 1018 Le Kremlin Bicetre France Paris Saclay Univ Bicetre Hosp Assistance Publ Hop Paris AP HP Mood Ctr Paris SaclayDept PsychiatDMU Neurosci Le Kremlin Bicetre France Inst Natl Sante & Rech Med INSERM U1127 Paris Brain Inst Inst Cerveau Paris France

Bayesian brain theory, a computational framework grounded in the principles of predictive processing (PP), proposes a mechanistic account of how beliefs are formed and updated. This theory assumes that the brain encodes a generative model of its environment, made up of probabilistic beliefs organized in networks, from which it generates predictions about future sensory inputs. The difference between predictions and sensory signals produces prediction errors, which are used to update belief networks. In this article, we introduce the fundamental principles of Bayesian brain theory, and show how the brain dynamics of prediction are associated with the generation and evolution of beliefs.

关键词： Belief Computational neuroscience predictive processing predictive coding Bayesian brain

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Role and limits of socio-normative influences in delusions of control

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SYNTHESE 2025年第5期205卷 1-24页

作者： Pacherie, Elisabeth Univ PSL Ecole Normale Super Inst Jean NicodDept Etud Cognit EHESSCNRS 29 Rue Ulm F-75005 Paris France

To what extent are the cognitive processes underlying human subjective experiences, thoughts, and behaviors shaped by socio-cultural norms and values, or conversely, impervious to socio-normative influences? To explore this question, I use delusions of control as a case study. Delusions of control present two apparent paradoxes, the resolution of which may illuminate the interplay between processes permeable to socio-cultural norms and those that are not. The first is the agency attribution paradox: individuals with delusions of control exhibit both under- and over-attribution of self-agency. The second is the paradox of double social standards: delusions of control simultaneously demonstrate permeability to socio-cultural influences and imperviousness to intersubjective evidence. I argue that a version of the predictive processing theory of the sense of agency, as proposed by Leptourgos and Corlett (2020, Frontiers in Big Data, 3, 27), may help resolve the agency attribution paradox and clarify some limits of socio-normative penetrability in cognitive processes. Furthermore, I suggest that the paradox of double social standards may be partly explained by metacognitive impairments and abnormally strong metacognitive feelings of confidence attached to delusional beliefs. These factors may account for both the significant role of socio-cultural priors in shaping delusional content and the resistance of delusions to change, even in the face of corrective social influences.

关键词： Delusions of control Socio-normative penetrability of cognitive processes predictive processing Paradox of attribution Double social standards Metacognitive impairments

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Common threads: Altered interoceptive processes across affective and anxiety disorders

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JOURNAL OF AFFECTIVE DISORDERS 2025年 369卷 244-254页

作者： Saltafossi, Martina Heck, Detlef Kluger, Daniel S. Varga, Somogy Univ Munster Inst Biomagnetism & Biosignal Anal Munster Germany Univ Munster Otto Creutzfeldt Ctr Cognit & Behav Neurosci Munster Germany Univ Minnesota Med Sch Dept Biomed Sci Duluth MN USA Univ Minnesota Ctr Cerebellar Network Struct & Funct Hlth & Dis Duluth MN USA Aarhus Univ Dept Philosophy Aarhus Denmark

There is growing attention towards atypical brain-body interactions and interoceptive processes and their potential role in psychiatric conditions, including affective and anxiety disorders. This paper aims to synthesize recent developments in this field. We present emerging explanatory models and focus on brain-body coupling and modulations of the underlying neurocircuitry that support the concept of a continuum of affective disorders. Grounded in theoretical frameworks like peripheral theories of emotion and predictive processing, we propose that altered interoceptive processes might represent transdiagnostic mechanisms that confer common vulnerability traits across multiple disorders. A deeper understanding of the interplay between bodily states and neural processing is essential for a holistic conceptualization of mental disorders.

关键词： Interoception Affective disorders Anxiety predictive processing Transdiagnostic mechanisms

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Computational Phenotyping of Aberrant Belief Updating in Individuals With Schizotypal Traits and Schizophrenia

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BIOLOGICAL PSYCHIATRY 2025年第2期97卷 188-197页

作者： Mikus, Nace Lamm, Claus Mathys, Christoph Univ Wien Fac Psychol Dept Cognit Emot & Methods Psychol Vienna Austria Aarhus Univ Interacting Minds Ctr Aarhus Denmark Univ Zurich Translat Neuromodeling Unit Zurich Switzerland Swiss Fed Inst Technol Zurich Switzerland Scuola Int Super Avanzati Trieste Italy

BACKGROUND: 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. METHODS: 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 RESULTS: 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. CONCLUSIONS: 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.

关键词： Bayesian inference predictive inference task predictive processing Psychotic symptoms Symptom differentiation Test-retest reliability

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