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Bayesian brain edge-based connectivity (BBeC): a Bayesian model for brain edge-based connectivity inference [PDF]
BMC BioinformaticsBackground Brain connectivity analysis based on magnetic resonance imaging is crucial for understanding neurological mechanisms. However, edge-based connectivity inference faces significant challenges, particularly the curse of dimensionality when ...
Zijing Li, Chenhao Zeng, Shufei Ge
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Animal affect, welfare and the Bayesian brain [PDF]
Animal WelfareAccording to the Bayesian brain hypothesis, the brain can be viewed as a predictive machine, such that predictions (or expectations) affect how sensory inputs are integrated.
Benjamin Lecorps, Daniel Weary
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How Psychedelic-Assisted Treatment Works in the Bayesian Brain [PDF]
Frontiers in Psychiatry, 2022 Psychedelics are experiencing a renaissance in clinical research. In recent years, an increasing number of studies on psychedelic-assisted treatment have been conducted. So far, the results are promising, suggesting that this new (or rather, rediscovered)
Daniel Villiger, Daniel Villiger
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Hierarchical disruption in the Bayesian brain: Focal epilepsy and brain networks [PDF]
NeuroImage: Clinical, 2017 In this opinion paper, we describe a combined view of functional and effective brain connectivity along with the free-energy principle for investigating persistent disruptions in brain networks of patients with focal epilepsy.
Amir Omidvarnia +4 more
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Bayesian multisource data integration for explainable brain-behavior analysis
Frontiers in Neuroscience, 2022 Different data sources can provide complementary information. Moving from a simple approach based on using one data source at a time to a systems approach that integrates multiple data sources provides an opportunity to understand complex brain disorders
Rong Chen
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A Quantum Predictive Brain: Complementarity Between Top-Down Predictions and Bottom-Up Evidence
Frontiers in Psychology, 2022 Predictive brain theory challenges the general assumption of a brain extracting knowledge from sensations and considers the brain as an organ of inference, actively constructing explanations about reality beyond its sensory evidence. Predictive brain has
Antonio Mastrogiorgio
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PLoS Computational Biology, 2021 Individualized anatomical information has been used as prior knowledge in Bayesian inference paradigms of whole-brain network models. However, the actual sensitivity to such personalized information in priors is still unknown. In this study, we introduce
Meysam Hashemi +9 more
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An Investigation of the Free Energy Principle for Emotion Recognition
Frontiers in Computational Neuroscience, 2020 This paper offers a prospectus of what might be achievable in the development of emotional recognition devices. It provides a conceptual overview of the free energy principle; including Markov blankets, active inference, and—in particular—a discussion of
Daphne Demekas +2 more
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Extraction of features from sleep EEG for Bayesian assessment of brain development. [PDF]
PLoS ONE, 2017 Brain development can be evaluated by experts analysing age-related patterns in sleep electroencephalograms (EEG). Natural variations in the patterns, noise, and artefacts affect the evaluation accuracy as well as experts' agreement.
Vitaly Schetinin, Livija Jakaite
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A Bayesian Account of Psychopathy: A Model of Lacks Remorse and Self-Aggrandizing
Computational Psychiatry, 2018 This article proposes a formal model that integrates cognitive and psychodynamic psychotherapeutic models of psychopathy to show how two major psychopathic traits called 'lacks remorse' and 'self-aggrandizing' can be understood as a form of abnormal ...
Aaron Prosser +3 more
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