Results 21 to 30 of about 65,094 (251)
Bayesian decoding of brain images [PDF]
NeuroImage, 2008 This paper introduces a multivariate Bayesian (MVB) scheme to decode or recognise brain states from neuroimages. It resolves the ill-posed many-to-one mapping, from voxel values or data features to a target variable, using a parametric empirical or hierarchical Bayesian model.
Karl J. Friston +6 more
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Probabilistic Biases Meet the Bayesian Brain [PDF]
Current Directions in Psychological Science, 2020 In Bayesian cognitive science, the mind is seen as a spectacular probabilistic-inference machine. But judgment and decision-making (JDM) researchers have spent half a century uncovering how dramatically and systematically people depart from rational norms.
Chater, Nick +5 more
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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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Empirical Bayesian localization of event-related time-frequency neural activity dynamics
NeuroImage, 2022 Accurate reconstruction of the spatio-temporal dynamics of event-related cortical oscillations across human brain regions is an important problem in functional brain imaging and human cognitive neuroscience with magnetoencephalography (MEG) and ...
Chang Cai +6 more
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Bayesian Approach to Psychotherapy Integration: Strategic Modification of Priors
Frontiers in Psychology, 2019 Integrative psychotherapies have become the mainstay in mental health care. The most researched therapy, CBT, being integrative itself, continues to integrate such new elements as mindfulness, spirituality, and experiential techniques.
Valery Krupnik
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Bayesian nonparametric method for genetic dissection of brain activation region
Frontiers in Neuroscience, 2023 Biological evidence indicewates that the brain atrophy can be involved at the onset of neuropathological pathways of Alzheimer's disease. However, there is lack of formal statistical methods to perform genetic dissection of brain activation phenotypes ...
Zhuxuan Jin +3 more
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Bayesian inference of structural brain networks [PDF]
NeuroImage, 2013 Structural brain networks are used to model white-matter connectivity between spatially segregated brain regions. The presence, location and orientation of these white matter tracts can be derived using diffusion-weighted magnetic resonance imaging in combination with probabilistic tractography. Unfortunately, as of yet, none of the existing approaches
Max Hinne +3 more
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Epistemic Irrationality in the Bayesian Brain
The British Journal for the Philosophy of Science, 2021 A large body of research in cognitive psychology and neuroscience draws on Bayesian statistics to model information processing within the brain. Many theorists have noted that this research seems to be in tension with a large body of experimental results purportedly documenting systematic deviations from Bayesian updating in human belief formation.
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Symptom perception, placebo effects, and the Bayesian brain. [PDF]
Pain, 2019 The standard and ideal biomedical model of symptom perception treats the brain largely as a passive stimulus-driven organ. It embraces the notion that the brain absorbs sensory signals from the body and converts them, directly, into conscious experience. Accordingly, biomedicine operates under the assumption that symptoms are the direct consequences of
Ongaro G, Kaptchuk TJ.
europepmc +5 more sources
Human’s Intuitive Mental Models as a Source of Realistic Artificial Intelligence and Engineering
Frontiers in Psychology, 2022 Despite the success of artificial intelligence (AI), we are still far away from AI that model the world as humans do. This study focuses for explaining human behavior from intuitive mental models’ perspectives.
Jyrki Suomala, Janne Kauttonen
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