C. Mathys

发表

Active inference and epistemic value

Karl J. Friston, Thomas H. B. FitzGerald, G. Pezzulo, 2015, Cognitive neuroscience.

Adults with autism over-estimate the volatility of the sensory environment

G. Rees, C. Mathys, R. Lawson, 2017, Nature Neuroscience.

Cholinergic Stimulation Enhances Bayesian Belief Updating in the Deployment of Spatial Attention

Karl J. Friston, Rick A Adams, R. Dolan, 2014, The Journal of Neuroscience.

Pharmacological Fingerprints of Contextual Uncertainty

P. Dayan, C. Mathys, K. Stephan, 2016, PLoS biology.

Optimal inference with suboptimal models: Addiction and active Bayesian inference

Karl J. Friston, Thomas H. B. FitzGerald, R. Dolan, 2015, Medical hypotheses.

Computational approaches to psychiatry

C. Mathys, K. Stephan, 2014, Current Opinion in Neurobiology.

Allostatic Self-efficacy: A Metacognitive Theory of Dyshomeostasis-Induced Fatigue and Depression

Lilian A. E. Weber, A. Seth, M. Tittgemeyer, 2016, Front. Hum. Neurosci..

Cortical Coupling Reflects Bayesian Belief Updating in the Deployment of Spatial Attention

Karl J. Friston, C. Mathys, K. Stephan, 2015, The Journal of Neuroscience.

Hierarchical prediction errors in midbrain and septum during social learning

Lilian A. E. Weber, C. Mathys, K. Stephan, 2017, Social cognitive and affective neuroscience.

Spatial Attention, Precision, and Bayesian Inference: A Study of Saccadic Response Speed

Karl J. Friston, J. Daunizeau, J. Driver, 2013, Cerebral cortex.

Hierarchical Prediction Errors in Midbrain and Basal Forebrain during Sensory Learning

C. Mathys, K. Stephan, Sandra Iglesias, 2013, Neuron.

Pavlovian conditioning–induced hallucinations result from overweighting of perceptual priors

Albert R. Powers, C. Mathys, P. Corlett, 2017, Science.

Representational Uncertainty in the Brain During Threat Conditioning and the Link With Psychopathic Traits.

C. Mathys, I. Brazil, A. Popma, 2017, Biological psychiatry. Cognitive neuroscience and neuroimaging.

Computations of uncertainty mediate acute stress responses in humans

R. Dolan, C. Mathys, L. Marshall, 2016, Nature Communications.

Cholinergic and dopaminergic effects on prediction error and uncertainty responses during sensory associative learning

Klaas E. Stephan, Lars Kasper, Sandra Iglesias, 2020, NeuroImage.

Hierarchical Prediction Errors in Midbrain and Basal Forebrain during Sensory Learning

C. Mathys, K. Stephan, Sandra Iglesias, 2013, Neuron.

Ketamine Affects Prediction Errors about Statistical Regularities: A Computational Single-Trial Analysis of the Mismatch Negativity

Lilian A. E. Weber, F. Vollenweider, C. Mathys, 2020, The Journal of Neuroscience.

Variability in Action Selection Relates to Striatal Dopamine 2/3 Receptor Availability in Humans: A PET Neuroimaging Study Using Reinforcement Learning and Active Inference Models

Karl J. Friston, Rick A Adams, M. Nour, 2020, Cerebral cortex.

Aberrant computational mechanisms of social learning and decision-making in schizophrenia and borderline personality disorder

C. Mathys, A. Diaconescu, A. Hasan, 2020, PLoS Comput. Biol..

Role of the Medial Prefrontal Cortex in Impaired Decision Making in Juvenile Attention-Deficit/Hyperactivity Disorder

Daniel Brandeis, Reto Iannaccone, Silvia Brem, 2014 .

Action–perception mismatch in tone-deafness

Frank H. Guenther, Christoph Mathys, Psyche Loui, 2008, Current Biology.

Corrigendum : Adults with autism overestimate the volatility of the sensory environment

Geraint Rees, Christoph Mathys, G. Rees, .

Volatility estimates increase choice switching and relate to prefrontal activity in schizophrenia

Klaas E. Stephan, Andreas Heinz, Florian Schlagenhauf, 2019, bioRxiv.

Subjective estimates of uncertainty during gambling and impulsivity after subthalamic deep brain stimulation for Parkinson’s disease

Eduardo A. Aponte, M. Breakspear, C. Mathys, 2019, Scientific Reports.

Subjective estimates of uncertainty and volatility during gambling predict impulsivity after subthalamic deep brain stimulation for Parkinson’s disease

Eduardo A. Aponte, M. Breakspear, C. Mathys, 2018, bioRxiv.

Neural arbitration between social and individual learning systems

P. Tobler, C. Mathys, A. Diaconescu, 2020, eLife.

Attractor-like Dynamics in Belief Updating in Schizophrenia

Gary Napier, Christoph Mathys, Jonathan P Roiser, 2018, The Journal of Neuroscience.

Atypical processing of uncertainty in individuals at risk for psychosis

K. Vogeley, M. Tittgemeyer, C. Mathys, 2020, NeuroImage: Clinical.

Volatility Estimates Increase Choice Switching and Relate to Prefrontal Activity in Schizophrenia.

C. Mathys, K. Stephan, L. Deserno, 2019, Biological psychiatry. Cognitive neuroscience and neuroimaging.

F150. OVERESTIMATING ENVIRONMENTAL VOLATILITY INCREASES SWITCHING BEHAVIOR AND IS LINKED TO ACTIVATION OF DORSOLATERAL PREFRONTAL CORTEX IN SCHIZOPHRENIA

C. Mathys, K. Stephan, L. Deserno, 2017, Schizophrenia Bulletin.

Conditioned Hallucinations and Prior Overweighting Are State-Sensitive Markers of Hallucination Susceptibility

Andrew D. Sheldon, Albert R. Powers, C. Mathys, 2022, Biological Psychiatry.

Updating beliefs beyond the here-and-now: the counter-factual self in anosognosia for hemiplegia

Karl J. Friston, Louise P. Kirsch, C. Mathys, 2020, Brain communications.

Corrigendum to "Active inference and epistemic value" [Cognitive Neuroscience, 6 (2015), 187-214. doi: 10.1080/17588928.2015.1020053]

Karl J. Friston, Giovanni Pezzulo, Dimitri Ognibene, 2016 .

A novel framework for improving psychiatric diagnostic nosology

Karl J. Friston, A. Redish, C. Mathys, 2016 .

Computational modeling of perceptual inference: A hierarchical Bayesian approach that allows for individual and contextual differences in weighting of input

Karl J. Friston, Klaas E. Stephan, Sandra Iglesias, 2012 .

Active inference and epistemic value (vol 6, pg 187, 2015)

Karl J. Friston, Giovanni Pezzulo, Dimitri Ognibene, 2016 .

Bayesian modelling captures inter-individual differences in social belief computations in the putamen and insula

C. Mathys, A. Diaconescu, L. Schilbach, 2020, Cortex.

A generative framework for the study of delusions

C. Mathys, Tore Erdmann, 2021, Schizophrenia Research.

Hierarchical Prediction Errors in Midbrain and Basal Forebrain during Sensory Learning

C. Mathys, K. Stephan, Sandra Iglesias, 2013, Neuron.

Attractor-like dynamics in belief 1 updating in schizophrenia 2 3 4

J. Roiser, C. Mathys, J. Gilleen, 2018 .

Non-Invasive Brain Stimulation Applied to Heschl's Gyrus Modulates Pitch Discrimination

G. Schlaug, C. Mathys, P. Loui, 2010, Front. Psychology.

Hierarchical Gaussian Filtering of Sufficient Statistic Time Series for Active Inference

Lilian A. E. Weber, C. Mathys, 2020 .

Neural arbitration between social and individual learning systems

Lars Kasper, Andreea Oliviana Diaconescu, Christopher J. Burke, 2019, bioRxiv.

Playing with free energy

C. Mathys, 2020 .

The Dopaminergic Midbrain Encodes the Expected Certainty about Desired Outcomes

Karl J. Friston, Thomas H. B. FitzGerald, R. Dolan, 2014, Cerebral cortex.

TAPAS: An Open-Source Software Package for Translational Neuromodeling and Computational Psychiatry

Eduardo A. Aponte, Samuel J. Harrison, Lilian A. E. Weber, 2021, bioRxiv.

Ketamine Affects Prediction Errors about Statistical Regularities: A Computational Single-Trial Analysis of the Mismatch Negativity

Klaas E. Stephan, Andreea Oliviana Diaconescu, Christoph Mathys, 2019, The Journal of Neuroscience.

Uncertainty in perception and the Hierarchical Gaussian Filter

Karl J. Friston, Klaas E. Stephan, Sandra Iglesias, 2014, Front. Hum. Neurosci..

A Bayesian Foundation for Individual Learning Under Uncertainty

Karl J. Friston, Klaas E. Stephan, Jean Daunizeau, 2011, Front. Hum. Neurosci..

Human visual exploration reduces uncertainty about the sensed world

Karl J. Friston, Karl J Friston, Christoph Mathys, 2018, PloS one.

Paranoia and belief updating during the COVID-19 crisis

C. Mathys, P. Corlett, Aaron J. Moss, 2021, Nature Human Behaviour.

Hierarchical Bayesian models of social inference for probing persecutory delusional ideation.

Katharina V. Wellstein, C. Mathys, K. Stephan, 2020, Journal of abnormal psychology.

Atypical processing of uncertainty in individuals at risk for psychosis

Klaas E. Stephan, Andreea O. Diaconescu, Kai Vogeley, 2019, NeuroImage: Clinical.

Inferring on the Intentions of Others by Hierarchical Bayesian Learning

Klaas E. Stephan, Lars Kasper, Jean Daunizeau, 2014, PLoS Comput. Biol..

Bayesian mixed-effects inference on classification performance in hierarchical data sets

Joachim M. Buhmann, Cheng Soon Ong, Klaas E. Stephan, 2012, J. Mach. Learn. Res..

Scene Construction, Visual Foraging, and Active Inference

Karl J. Friston, Rick A. Adams, Christoph Mathys, 2016, Front. Comput. Neurosci..

Modeling subjective relevance in schizophrenia and its relation to aberrant salience

Norbert Kathmann, Henrik Walter, Andreas Heinz, 2018, PLoS Comput. Biol..

A unifying Bayesian account of contextual effects in value-based choice

Raymond J. Dolan, Karl J. Friston, Christoph Mathys, 2017, PLoS Comput. Biol..

Dynamic causal modelling revisited

Adeel Razi, Karl J. Friston, Jakob Heinzle, 2017, NeuroImage.

Evidence for surprise minimization over value maximization in choice behavior

Karl J. Friston, Philipp Schwartenbeck, Karl Friston, 2015, Scientific Reports.

Variational Bayesian mixed-effects inference for classification studies

Joachim M. Buhmann, Klaas E. Stephan, Jean Daunizeau, 2013, NeuroImage.

Inferring in Circles: Active Inference in Continuous State Space Using Hierarchical Gaussian Filtering of Sufficient Statistics

C. Mathys, N. Mikus, P. T. Waade, 2021, PKDD/ECML Workshops.

The Switching Hierarchical Gaussian Filter

Bert de Vries, Albert Podusenko, Christoph Mathys, 2021, 2021 IEEE International Symposium on Information Theory (ISIT).

The generalized Hierarchical Gaussian Filter

Lilian A. E. Weber, C. Mathys, K. Stephan, 2023, ArXiv.

Adults with autism over-estimate the volatility of the sensory environment

G. Rees, C. Mathys, Rebecca P. Lawson, 2017, Nature Neuroscience.

A computational hierarchy in human cortex

Karl J. Friston, C. Mathys, K. Stephan, 2017, 1709.02323.

F157. HIERARCHICAL PREDICTION ERRORS DURING AUDITORY MISMATCH UNDER PHARMACOLOGICAL MANIPULATIONS: A COMPUTATIONAL SINGLE-TRIAL EEG ANALYSIS

Dario Schöbi, Sandra Iglesias, Christoph Mathys, 2018, Schizophrenia Bulletin.

Active inference and epistemic value

Karl J. Friston, Thomas H. B. FitzGerald, G. Pezzulo, 2015, Cognitive neuroscience.

Allostatic Self-efficacy: A Metacognitive Theory of Dyshomeostasis-Induced Fatigue and Depression

Lilian A. E. Weber, A. Seth, M. Tittgemeyer, 2016, Front. Hum. Neurosci..

How could we get nosology from computation

Christoph Mathys, C. Mathys, 2016 .

Variational Bayesian mixed-effects inference for classification studies

J. Buhmann, J. Daunizeau, C. Mathys, 2013, NeuroImage.

Volatility estimates increase choice switching and relate to prefrontal activity in schizophrenia

C. Mathys, K. Stephan, L. Deserno, 2017, bioRxiv.

Human Neuroscience

J. Daunizeau, C. Mathys, K. Friston, 2022 .