Christoph Mathys
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Predictive Processing Over the Course of Aging: Multiple Timescales of Effective Connectivity Open
Predictive processing theories describe perception as a dynamic interplay between top‐down predictions and bottom‐up prediction errors across hierarchical stages of sensory processing. However, it remains unclear how neural connectivity fl…
Using personalised brain stimulation to modulate social cognition in adults with autism-spectrum-disorder: protocol for a randomised single-blind rTMS study Open
Background Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairments of social interaction and communication as well as repetitive, stereotyped behaviour. Previous research indicates that ASD without inte…
Bayesian Workflow for Generative Modeling in Computational Psychiatry Open
Computational (generative) modelling of behaviour has considerable potential for clinical applications. In order to unlock the potential of generative models, reliable statistical inference is crucial. For this, Bayesian workflow has been …
View article: Thermosensory predictive coding underpins an illusion of pain
Thermosensory predictive coding underpins an illusion of pain Open
The human brain has a remarkable ability to learn and update its beliefs about the world. Here, we investigate how thermosensory learning shapes our subjective experience of temperature and the misperception of pain in response to harmless…
View article: Neurochemical markers of uncertainty processing in humans
Neurochemical markers of uncertainty processing in humans Open
How individuals process and respond to uncertainty has important implications for cognition and mental health. Here we use computational phenotyping to examine individualised “uncertainty fingerprints” in relation to neurometabolites and t…
As One and Many: Relating Individual and Emergent Group-Level Generative Models in Active Inference Open
Active inference under the Free Energy Principle has been proposed as an across-scales compatible framework for understanding and modelling behaviour and self-maintenance. Crucially, a collective of active inference agents can, if they mai…
Introducing ActiveInference.jl: A Julia Library for Simulation and Parameter Estimation with Active Inference Models Open
We introduce a new software package for the Julia programming language, the library ActiveInference.jl. To make active inference agents with Partially Observable Markov Decision Process (POMDP) generative models available to the growing re…
View article: Bayesian Workflow for Generative Modeling in Computational Psychiatry
Bayesian Workflow for Generative Modeling in Computational Psychiatry Open
Computational (generative) modelling of behaviour has considerable potential for clinical applications. In order to unlock the potential of generative models, reliable statistical inference is crucial. For this, Bayesian workflow has been …
Introducing ActiveInference.jl: A Julia Library for Simulation and Parameter Estimation with Active Inference Models Open
We introduce a new software package for the Julia programming language, the library ActiveInference.jl. To make active inference agents with Partially-Observable Markov Decision Process (POMDP) generative models available to the growing re…
View article: Guided by Expectations: Overweighted Semantic Priors in Schizotypy and their Links to Glutamate
Guided by Expectations: Overweighted Semantic Priors in Schizotypy and their Links to Glutamate Open
An imbalance in the weighting of prior beliefs and sensory evidence are thought to contribute to the development of psychotic symptoms, such as hallucinations and delusions. We investigated how much individuals with schizotypal traits, a s…
As One and Many: Relating Individual and Emergent Group-Level Generative Models in Active Inference Open
Active inference under the Free Energy Principle has been proposed as an across-scales compatible framework for understanding and modelling behaviour and self-maintenance. Crucially, a collective of active inference agents can, if they mai…
pyhgf: A neural network library for predictive coding Open
Bayesian models of cognition have gained considerable traction in computational neuroscience and psychiatry. Their scopes are now expected to expand rapidly to artificial intelligence, providing general inference frameworks to support embo…
Exploring when to exploit: The cognitive underpinnings of foraging-type decisions in relation to psychopathy Open
Impairments in reinforcement learning (RL) might underlie the tendency of individuals with elevated psychopathic traits to behave exploitatively, as they fail to learn from their mistakes. Most studies on the topic have focused on binary c…
Exploring when to exploit: The cognitive underpinnings of foraging-type decisions in relation to psychopathy Open
Impairments in reinforcement learning (RL) might underlie the tendency of individuals with elevated psychopathic traits to behave exploitatively, as they fail to learn from their mistakes. Most studies on the topic have focused on binary c…
View article: Uncertainty in Thermosensory Expectations Enhances an Illusion of Pain
Uncertainty in Thermosensory Expectations Enhances an Illusion of Pain Open
The human brain has a remarkable ability to learn and update its beliefs about the world. Here, we investigate how thermosensory learning shapes our subjective experience of temperature and the misperception of pain in response to harmless…
View article: Bayesian Workflow for Generative Modeling in Computational Psychiatry
Bayesian Workflow for Generative Modeling in Computational Psychiatry Open
Computational (generative) modelling of behaviour has considerable potential for clinical applications. In order to unlock the potential of generative models, reliable statistical inference is crucial. For this, Bayesian workflow has been …
Pain and still no gain: Diminished pain sensitivity mediates the relationship between psychopathic traits and reduced learning from pain Open
Individuals with elevated psychopathic traits exhibit decision-making deficits linked to a failure to learn from negative outcomes. We investigated how reduced pain sensitivity affects reinforcement-based decision-making in individuals wit…
Adaptive social decisions are disrupted in highly antagonistic individuals Open
BackgroundHealthy social functioning relies on an ability to form accurate representations of others’ character and to utilize the representations to guide decisions. Here, we take a transdiagnostic longitudinal approach to investigate dis…
Computational phenotyping of aberrant belief updating in individuals with schizotypal traits and schizophrenia Open
Psychotic and psychotic-like experiences are thought to emerge from various patterns of disrupted belief updating. These include belief rigidity, overestimating the reliability of sensory information, and misjudging task volatility. Yet, t…
Phi fluctuates with surprisal: An empirical pre-study for the synthesis of the free energy principle and integrated information theory Open
The Free Energy Principle (FEP) and Integrated Information Theory (IIT) are two ambitious theoretical approaches. The first aims to make a formal framework for describing self-organizing and life-like systems in general, and the second att…
View article: Lesions to the mediodorsal thalamus but not orbitofrontal cortex enhance volatility beliefs linked to paranoia
Lesions to the mediodorsal thalamus but not orbitofrontal cortex enhance volatility beliefs linked to paranoia Open
Beliefs – attitudes toward some state of the environment – guide action selection and should be robust to variability but sensitive to meaningful change. Beliefs about volatility (expectation of change) are associated with paranoia in huma…