Hallucinations Under Psychedelics and in the Schizophrenia Spectrum: An Interdisciplinary and Multiscale Comparison

The recent renaissance of psychedelic science has reignited interest in the similarity of drug-induced experiences to those more commonly observed in psychiatric contexts such as the schizophrenia-spectrum. This report from a multidisciplinary working group of the International Consortium on Hallucinations Research (ICHR) addresses this issue, putting special emphasis on hallucinatory experiences. We review evidence collected at different scales of understanding, from pharmacology to brain-imaging, phenomenology and anthropology, highlighting similarities and differences between hallucinations under psychedelics and in the schizophrenia-spectrum disorders. Finally, we attempt to integrate these findings using computational approaches and conclude with recommendations for future research

Inférence circulaire dynamique en population générale et dans le spectre psychotique : apports de la prise de décision perceptive

We live in an uncertain world, yet our survival depends on how quickly and accurately we can make decisions and act upon them. To address this problem, modern neuroscience reconceptualised perception as an inference process, in which the brain combines sensory inputs and prior expectations to reconstruct a plausible image of the world. In addition to that, influential theories in the emerging field of computational psychiatry suggest that various psychiatric disorders, including schizophrenia, could be the outcome of impaired predictive processing. Among those theories, the circular inference framework suggests that an unconstrained propagation of information in the cortex, underlain by an excitatory to inhibitory imbalance, can generate false percepts and beliefs, similar to those exhibited by schizophrenia patients. In the present thesis, we probed the role of circular inference from normal to pathological brain functioning, gaining insights from perceptual decision making in the presence of high ambiguity. In the first part of the thesis, we focused on the role of circularity in bistable perception in the general population. Bistability occurs when two mutually exclusive interpretations compete and switch as dominant percepts every few seconds. In a 1st article, we manipulated sensory evidence and priors in a Necker cube task, asking how the brain combines low-level and high-level information to form perceptual interpretations. We found a significant effect of each manipulation but also an interaction between the two, a finding incompatible with Bayes optimal integration. Bayesian model comparison further supported this observation, showing that a circular inference model outperformed purely Bayesian models. Having established a link between circular inference and bistable perception, we then put forward a functional theory of bistability, based on circularity (2nd article). In particular, we derived the dynamics of a dynamical circular inference model, showing that descending loops (i.e. a form of circularity resulting in aberrant amplification of the priors) transform what is normally a leaky integration of noisy evidence into a bistable attractor with two highly trusted stable states. Importantly, this model can explain both the existence and the phenomenological properties of bistable perception, making a number of testable predictions. Finally, in a 3rd article, we tested one of the model’s predictions, namely the perceptual behaviour when the stimulus is presented discontinuously. We ran two Necker cube experiments using a novel intermittent-presentation methodology, and we calculated the stabilisation curves (i.e. persistence as a function of blank durations). We found that participants’ behaviour was compatible with the model’s prediction for a system with descending loops, suggesting that circularity constitutes a general mechanism that shapes the way healthy individuals perceive the world. In the second part, we studied circular inference in pathological conditions related to psychosis. We notably focused on two varieties of the psychotic experience, namely schizophrenia-related psychosis and drug-induced psychosis. After discussing the links between behaviour, aberrant message-passing and the corresponding neural networks (4th article), we used bistable perception to probe the computational mechanisms underlying schizophrenia in a 5th article. We compared patients with prominent positive symptoms with matched healthy controls in two bistable perception tasks. Our results suggest an enhanced amplification of sensory inputs in patients, combined with an overestimation of the environmental volatility. In the last article (6th), we delineated a multiscale account of psychedelics, ultimately linking the macroscale (i.e. phenomenological considerations such as the crossmodal character of the psychedelics experience), the mesoscale (i.e. loops) and the microscale (i.e. neuromodulators and canonical microcircuits).Nous évoluons dans un monde incertain. De ce fait, notre survie dépend de notre capacité à prendre rapidement des décisions, et ce de manière fiable et adaptative. Il est possible de mieux comprendre cette capacité en considérant la perception comme un processus d’inférence probabiliste au cours duquel les informations sensorielles sont combinées à nos attentes pour produire une interprétation plausible de notre environnement. Les théories récentes de psychiatrie computationnelle suggèrent par ailleurs que la grande variabilité des troubles psychiatriques, au rang desquelles figure la schizophrénie, pourrait résulter d’une altération de ces mêmes processifs prédictifs. L’Inférence Circulaire est l’une de ces théories. Ce cadre de pensée stipule qu’une propagation incontrôlée d’information dans la hiérarchie corticale pourrait générer des percepts ou des croyances aberrantes. Afin d’explorer le rôle joué par l’Inférence Circulaire en condition normale ou pathologique, ce travail de thèse s’est appuyé sur des tâches de prise de décision en conditions perceptives ambigües. Dans une première partie, nous nous sommes intéressés au rôle joué par la circularité dans la perception bistable. Le phénomène de bistabilité survient lorsque deux interprétations se succèdent à intervalle régulier pour un même percept. Nous présentons les résultats d’une tâche conduite en population saine où nous avons manipulé les informations sensorielles et à priori utilisées par les participants lors de la visualisation d’un cube de Necker (article 1). Nous avons pu montrer un effet propre à chaque manipulation, mais également une interaction entre ces deux sources d’information, incompatible avec une intégration Bayésienne optimale. Résultat confirmé par la comparaison de divers modèles computationnels ajustés aux données, qui a pu mettre en évidence la supériorité de l’Inférence Circulaire sur les modèles Bayésiens classiques. Nous avons ensuite voulu tester un modèle fonctionnel de la bistabilité (article 2). Nous avons donc dérivé la dynamique du modèle et montré que la présence de boucles descendantes dans la hiérarchie corticale, transformait ce qui était jusque là un intégrateur imparfait du bruit sensoriel en modèle à attracteur bistable. Ce modèle ne reproduit pas seulement le phénomène de bistabilité, mais également l’ensemble de ces caractéristiques phénoménologiques. Dans un 3ème article, nous avons testé une prédiction, notamment en cas de présentation discontinue d’un stimulus bistable. Deux expériences complémentaires utilisant un paradigme de présentation intermittente du cube de Necker ont donc été conduites en population générale. Nos résultats étaient compatible avec les prédictions faites par le modèle de l’Inférence Circulaire Dynamique, suggérant que la circularité puisse être un mécanisme générique à l’origine de notre façon de voir le monde. Dans la seconde partie de ce travail, nous avons étudié l’Inférence Circulaire en condition pathologique, notamment lors d’expériences psychotiques (schizophrénie, psychédéliques). Nous avons utilisé la perception bistable pour explorer les mécanismes computationnels à l’œuvre dans la schizophrénie (article 4,5). Nous avons comparé les performances de patients présentant des symptômes psychotiques à des témoins sains appariés lors d’une tâche de perception bistable. Nous avons pu montrer chez les patients une amplification des informations sensorielles combinée à une surestimation de la volatilité environnementale. Enfin nous terminons ce travail en proposant une approche transversale de l’effet des psychédéliques (article 6), sur la base des résultats précédents et de la spécificité clinique de ces expériences sensorielles cross-modales, afin de relier l’échelle macroscopique (i.e., comportement et phénoménologie), mésoscopique (i.e., les boucles inférentielles) et microscopique (i.e., les différents neurotransmetteurs impliqués aboutissant à un microcircuit canonique)

Can circular inference relate the neuropathological and behavioral aspects of schizophrenia?

Schizophrenia is a complex and heterogeneous mental disorder, and researchers have only recently begun to understand its neuropathology. However, since the time of Kraepelin and Bleuler, much information has been accumulated regarding the behavioral abnormalities usually encountered in patients suffering from schizophrenia. Despite recent progress, how the latter are caused by the former is still debated. Here, we argue that circular inference, a computational framework proposed as a potential explanation for various schizophrenia symptoms, could help end this debate. Based on Marr's three levels of analysis, we discuss how impairments in local and more global neural circuits could generate aberrant beliefs, with far-ranging consequences from probabilistic decision making to high-level visual perception in conditions of ambiguity. Interestingly, the circular inference framework appears to be compatible with a variety of pathophysiological theories of schizophrenia while simulating the behavioral symptoms

Hydrodynamic analysis of deformable hydrofoils with application to fish locomotion

175 σ.Στις μέρες μας είναι καθολικά αποδεκτό ότι η φύση και ιδιαίτερα οι ζωντανοί οργανισμοί έχουν αναπτύξει μηχανισμούς κατά πολύ ανώτερους από την πλειονότητα των επιτευγμάτων της ανθρώπινης προηγμένης τεχνολογίας, με αποτέλεσμα να κρίνεται απαραίτητη η προσπάθεια παρατήρησης και απομίμησης των μηχανισμών αυτών. Στόχος της εργασίας είναι η δημιουργία ενός 2D γεωμετρικού μοντέλου της κίνησης των ψαριών το οποίο εν συνεχεία μελετάται παραμετρικά ως προς την παραγωγή δυνάμεων και ιδιαίτερα ώσης. Για το σκοπό αυτό θεωρείται ταλαντούμενη συμμετρική υδροτομή της οποίας η σύνθετη κίνηση αναλύεται σε μια μετατόπιση, μια στροφή και μια παραμόρφωση (εισάγεται με χρήση μοντέλου μεταβλητής ακμής εκφυγής). Η υδροδυναμική ανάλυση γίνεται με χρήση μιας μεθόδου συνεκτικής-μη συνεκτικής αλληλεπίδρασης, με βηματική ολοκλήρωση στο χρόνο, που στηρίζεται στη σύζευξη της μεθόδου των συνοριακών στοιχείων με μια ολοκληρωτική διατύπωση των εξισώσεων του οριακού στρώματος.Nowadays, it's widely accepted that nature and living animals have developed mechanisms superior to anything human technology has ever achieved. As a result, it is really important to observe those mechanisms and try to immitate them. The aim of this thesis is to create a 2D geometrical model of fish locomotion and analyse the force generation and especially the generation of thrust. For this purpose, we consider a symmetrical flapping hydrofoil whose complex motion can be analysed into a heaving motion, a pitching motion and a deformation (introduced by using a deformable trailing edge model). For the hydrodynamic analysis we use a method of viscous-inviscid interaction, with step integration in time, based on a coupling of the boundary elements method with the integral formulation of the boundary layer equations.Παντελής Χ. Λεπτουργό

Paranoia, self-deception and overconfidence

Self-deception, paranoia, and overconfidence involve misbeliefs about the self, others, and world. They are often considered mistaken. Here we explore whether they might be adaptive, and further, whether they might be explicable in Bayesian terms. We administered a difficult perceptual judgment task with and without social influence (suggestions from a cooperating or competing partner). Crucially, the social influence was uninformative. We found that participants heeded the suggestions most under the most uncertain conditions and that they did so with high confidence, particularly if they were more paranoid. Model fitting to participant behavior revealed that their prior beliefs changed depending on whether the partner was a collaborator or competitor, however, those beliefs did not differ as a function of paranoia. Instead, paranoia, self-deception, and overconfidence were associated with participants’ perceived instability of their own performance. These data are consistent with the idea that self-deception, paranoia, and overconfidence flourish under uncertainty, and have their roots in low self-esteem, rather than excessive social concern. The model suggests that spurious beliefs can have value–self-deception is irrational yet can facilitate optimal behavior. This occurs even at the expense of monetary rewards, perhaps explaining why self-deception and paranoia contribute to costly decisions which can spark financial crashes and devastating wars.</p

Relationships between cognitive biases, decision-making, and delusions

Abstract Multiple measures of decision-making under uncertainty (e.g. jumping to conclusions (JTC), bias against disconfirmatory evidence (BADE), win-switch behavior, random exploration) have been associated with delusional thinking in independent studies. Yet, it is unknown whether these variables explain shared or unique variance in delusional thinking, and whether these relationships are specific to paranoia or delusional ideation more broadly. Additionally, the underlying computational mechanisms require further investigation. To investigate these questions, task and self-report data were collected in 88 individuals (46 healthy controls, 42 schizophrenia-spectrum) and included measures of cognitive biases and behavior on probabilistic reversal learning and explore/exploit tasks. Of those, only win-switch rate significantly differed between groups. In regression, reversal learning performance, random exploration, and poor evidence integration during BADE showed significant, independent associations with paranoia. Only self-reported JTC was associated with delusional ideation, controlling for paranoia. Computational parameters increased the proportion of variance explained in paranoia. Overall, decision-making influenced by strong volatility and variability is specifically associated with paranoia, whereas self-reported hasty decision-making is specifically associated with other themes of delusional ideation. These aspects of decision-making under uncertainty may therefore represent distinct cognitive processes that, together, have the potential to worsen delusional thinking across the psychosis spectrum

Learned uncertainty:the free energy principle in anxiety

Generalized anxiety disorder is among the world’s most prevalent psychiatric disorders and often manifests as persistent and difficult to control apprehension. Despite its prevalence, there is no integrative, formal model of how anxiety and anxiety disorders arise. Here, we offer a perspective derived from the free energy principle; one that shares similarities with established constructs such as learned helplessness. Our account is simple: anxiety can be formalized as learned uncertainty. A biological system, having had persistent uncertainty in its past, will expect uncertainty in its future, irrespective of whether uncertainty truly persists. Despite our account’s intuitive simplicity—which can be illustrated with the mere flip of a coin—it is grounded within the free energy principle and hence situates the formation of anxiety within a broader explanatory framework of biological self-organization and self-evidencing. We conclude that, through conceptualizing anxiety within a framework of working generative models, our perspective might afford novel approaches in the clinical treatment of anxiety and its key symptoms

Conspiracy beliefs and perceptual inference in times of political uncertainty

Socio-political crises with uncertain issues accumulated in recent years, providing fertile ground for the emergence of conspiracy ideations. Computational models constitute valuable tools for understanding the mechanisms at play in the formation and rigidification of these unshakeable beliefs. Here, the Circular Inference model was used to capture associations between changes in perceptual inference, and the dynamics of conspiracy ideations in times of uncertainty. Large populations from three polarized countries performed a bistable perception task and conspiracy beliefs assessments, around major socio-political events. We show that when uncertainty peaks, an overweighting of sensory information is associated with conspiracy ideations. Progressively, this exploration strategy gives way to an exploitation strategy, in which increased adherence to conspiracy theories is associated with the amplification of prior information. Overall, the Circular Inference model sheds new light on the possible mechanisms underlying the progressive rigidification of conspiracy theories when facing highly uncertain situations

Conspiracy beliefs and perceptual inference in times of political uncertainty.

International audienceSociopolitical crises causing uncertainty have accumulated in recent years, providing fertile ground for the emergence of conspiracy ideations. Computational models constitute valuable tools for understanding the mechanisms at play in the formation and rigidification of these unshakeable beliefs. Here, the Circular Inference model was used to capture associations between changes in perceptual inference and the dynamics of conspiracy ideations in times of uncertainty. A bistable perception task and conspiracy belief assessment focused on major sociopolitical events were administered to large populations from three polarized countries. We show that when uncertainty peaks, an overweighting of sensory information is associated with conspiracy ideations. Progressively, this exploration strategy gives way to an exploitation strategy in which increased adherence to conspiracy theories is associated with the amplification of prior information. Overall, the Circular Inference model sheds new light on the possible mechanisms underlying the progressive strengthening of conspiracy theories when individuals face highly uncertain situations