Results 221 to 230 of about 65,094 (251)

Bayesian brains and cognitive mechanisms:

2008
AbstractThe chapter considers the project of probabilistic rational analysis in relation to a particularly well-studied and simple heuristic, the Take the Best algorithm. The authors relate the tension between ‘rational’ and ‘algorithmic’ explanations of cognitive phenomena to the bias-variance dilemma in statistics.
Henry Brighton, Gerd Gigerenzer
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Bayes in the Brain—On Bayesian Modelling in Neuroscience

The British Journal for the Philosophy of Science, 2012
According to a growing trend in theoretical neuroscience, the human perceptual system is akin to a Bayesian machine. The aim of this article is to clearly articulate the claims that perception can be considered Bayesian inference and that the brain can be considered a Bayesian machine, some of the epistemological challenges to these claims; and some of
Colombo, M., Seriès, P.
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Brain image completion by Bayesian tensor decomposition

2017 22nd International Conference on Digital Signal Processing (DSP), 2017
The MRI data is naturally represented by a three-order tensor. The reconstruction of MRI image from sparse observations is a challenging task, which has many potential applications for data compression, feature extraction and classifications. In this paper, we employ Bayesian Tucker decomposition to learn the low-rank representations of MRI data from ...
Lihua Gui, Qibin Zhao, Jianting Cao
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Bayesian Recognition of Inflammatory Processes in Brain Gliomas

Cybernetics and Systems Analysis, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gridina, N. Ja., Gupal, A. M., Tarasov, A. L.   +2 more
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Computational Psychiatry and the Bayesian Brain

2017
Abstract This chapter considers recent advances in computational neuroscience that are especially relevant for psychiatry. We offer a review of computational psychiatry in terms of its ambitions, emerging domains of application, and promises for the future.
Karl J. Friston, Raymond J. Dolan
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A Bayesian and Emergent View of the Brain

Kronoscope, 2014
Very simple psychophysiological visual tests suggest that the brain, instead of processing visual information in a passive way as was classically thought, in fact actively evaluates probabilities of the causes of visual data and continuously proposes to the mind the ones that are more likely to account for sensory inputs.
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The emergence of autism in the Bayesian brain

2017
The brain represents the state of the world around us based upon a stream of ambiguous sensory data. This requires the integration of different sources of information, including information received from different sense modalities, and information drawn from past experience.
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Computational Psychiatry and the Bayesian Brain

Abstract Computational psychiatry is a burgeoning field that uses formal models of brain function to characterize the mechanisms of psychopathology, with the hope that these mechanistic views can generate objective and predictive targets for treatment and intervention.
Karl J. Friston, Xiaosi Gu
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Serotonin in the Bayesian brain

While theoretical models increasingly use Bayesian frameworks to explain neural processing, a significant gap exists in understanding how these mathematical principles are biologically implemented. This thesis proposes that serotonin serves as a biological mechanism for precision modulation in predictive processing, tested through experiments on ...
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Bayesian Inference for Brain Decoding

2014
Brain decoding, a paradigm that consists of predicting stimuli or mental states from concurrent functional brain data, is steadily gaining popularity in neuroimaging based research. While the machine learning and pattern recognition techniques involved in classification-based analysis are getting more and more sophisticated, the statistical methods ...
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