Results 211 to 220 of about 65,094 (251)
Maternal chronic wasting disease infection restricts fetal head size in white-tailed deer (<i>Odocoileus virginianus</i>). [PDF]
PrionMori J +7 more
europepmc +1 more source
Causal mechanisms of individual differences in hemispheric lateralization of the face perception network: A DCM-PEB approach. [PDF]
Imaging Neurosci (Camb)Stocker JE +6 more
europepmc +1 more source
Bayesian inference of RNA velocity incorporating timepoints, lineage bifurcations, and count data. [PDF]
PLoS Comput BiolGu Y, Song Y, Blaauw D, Welch JD.
europepmc +1 more source
Corticocerebellar Effective Connectivity During Adapting to vs. Ignoring Delayed Visual Movement Feedback. [PDF]
Eur J NeurosciWang Z, Limanowski J.
europepmc +1 more source
Bayesian Estimation Improves Prediction of Outcomes After Epilepsy Surgery. [PDF]
Ann Clin Transl NeurolDickey AS +4 more
europepmc +1 more source
The history of the future of the Bayesian brain
NeuroImage, 2012 The slight perversion of the original title of this piece (The Future of the Bayesian Brain) reflects my attempt to write prospectively about 'Science and Stories' over the past 20 years. I will meet this challenge by dealing with the future and then turning to its history.
Karl J Friston
exaly +3 more sources
Bayesian modeling of temporal expectations in the human brain [PDF]
NeuroImage, 2019 The brain predicts the timing of forthcoming events to optimize processes in response to them. Temporal predictions are driven by both our prior expectations on the likely timing of stimulus occurrence and the information conveyed by the passage of time.
Antonino Visalli +2 more
exaly +3 more sources
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2006
Experimental and theoretical neuroscientists use Bayesian approaches to analyze the brain mechanisms of perception, decision-making, and motor control. A Bayesian approach can contribute to an understanding of the brain on multiple levels, by giving normative predictions about how an ideal sensory system should combine prior knowledge ...
openaire +1 more source
Experimental and theoretical neuroscientists use Bayesian approaches to analyze the brain mechanisms of perception, decision-making, and motor control. A Bayesian approach can contribute to an understanding of the brain on multiple levels, by giving normative predictions about how an ideal sensory system should combine prior knowledge ...
openaire +1 more source
Hierarchical Bayesian Inference of Brain Activity
2008Magnetoencephalography (MEG) can measure brain activity with millisecond-order temporal resolution, but its spatial resolution is poor, due to the ill-posed nature of the inverse problem, for estimating source currents from the electromagnetic measurement. Therefore, prior information on the source currents is essential to solve the inverse problem.
Masa-aki Sato, Taku Yoshioka
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