Results 51 to 60 of about 2,095,528 (293)

Cortical hierarchies perform Bayesian causal inference in multisensory perception.

PLoS Biology, 2015
To form a veridical percept of the environment, the brain needs to integrate sensory signals from a common source but segregate those from independent sources.
Tim Rohe, Uta Noppeney
doaj   +1 more source

Brain dynamics for confidence-weighted learning.

PLoS Computational Biology, 2020
Learning in a changing, uncertain environment is a difficult problem. A popular solution is to predict future observations and then use surprising outcomes to update those predictions.
Florent Meyniel
doaj   +1 more source

Brain-Inspired Hardware Solutions for Inference in Bayesian Networks

Frontiers in Neuroscience, 2021
The implementation of inference (i.e., computing posterior probabilities) in Bayesian networks using a conventional computing paradigm turns out to be inefficient in terms of energy, time, and space, due to the substantial resources required by floating ...
Leila Bagheriye, Johan Kwisthout
doaj   +1 more source

BAYESIAN SENSE OF TIME IN BIOLOGICAL AND ARTIFICIAL BRAINS

, 2023
Enquiries concerning the underlying mechanisms and the emergent properties of a biological brain have a long history of theoretical postulates and experimental findings. Today, the scientific community tends to converge to a single interpretation of the brain's cognitive underpinnings -- that it is a Bayesian inference machine.
Zafeirios Fountas, Alexey Zakharov
openaire   +2 more sources

Using stacking to average bayesian predictive distributions (with discussion) [PDF]

, 2018
Bayesian model averaging is flawed in the M-open setting in which the true data-generating process is not one of the candidate models being fit. We take the idea of stacking from the point estimation literature and generalize to the combination of ...
Grunwald, Peter, Castro-Camilo, Daniela, Li, Meng, Shin, Minsuk, Grushka-Cockayne, Yael, Gelman, Andrew, Lichtendahl, Kenneth C., Iacopini, Matteo, Dawid, A. Philip, van Dijk, Herman K., Lichtendahl, Kenneth C, Yao, Yuling, Zhou, Tianjian, Winkler, Robert L, Aastveit, Knut Are, Dawid, A Philip, Yoo, William Weimin, Pericchi, Luis, Clarke, Bertrand, Bakka, Haakon C, Freni-Sterrantino, Anna, Franck, Christopher T., Hoogerheide, Lennart, Tonellato, Stefano, Winkler, Robert L., Simpson, Daniel, Ferreira, Marco A. R., Franco-Villoria, Maria, Belitser, Eduard, Bakka, Haakon C., van Dijk, Herman K, Ferreira, Marco AR, de Heide, Rianne, Nurushev, Nurzhan, Jose, Victor Richmond R., Vehtari, Aki, Clyde, Merlise, McAlinn, Kenichiro, West, Mike, Rue, Havard, Huser, Raphael, Opitz, Thomas, Jose, Victor Richmond R, Franck, Christopher T   +43 more
core   +1 more source

(Mal)adaptive Mentalizing in the Cognitive Hierarchy, and Its Link to Paranoia

Computational Psychiatry
Humans need to be on their toes when interacting with competitive others to avoid being taken advantage of. Too much caution out of context can, however, be detrimental and produce false beliefs of intended harm.
Nitay Alon, Lion Schulz, Vaughan Bell, Michael Moutoussis, Peter Dayan, Joseph M. Barnby   +5 more
doaj   +1 more source

Bayesian Methods in Brain Connectivity Change Point Detection with EEG Data and Genetic Algorithm [PDF]

, 2019
Human brain is processing a great amount of information everyday, and our brain regions are organized optimally for this information processing. There have been increasing number of studies focusing on functional or effective connectivity in human brain ...
Liu, Bing
core   +1 more source

Segmental Bayesian estimation of gap-junctional and inhibitory conductance of inferior olive neurons from spike trains with complicated dynamics

Frontiers in Computational Neuroscience, 2015
The inverse problem for estimating model parameters from brain spike data is an ill-posed problem because of a huge mismatch in the system complexity between the model and the brain as well as its non-stationary dynamics, and needs a stochastic approach ...
Huu eHoang, Huu eHoang, Okito eYamashita, Okito eYamashita, Isao T. Tokuda, Masa-aki eSato, Mitsuo eKawato, Keisuke eToyama   +7 more
doaj   +1 more source

A Global Bayes Factor for Observations on an Infinite-Dimensional Hilbert Space, Applied to Signal Detection in fMRI

Austrian Journal of Statistics, 2021
Functional Magnetic Resonance Imaging (fMRI) is a fundamental tool in advancing our understanding of the brain's functionality. Recently, a series of Bayesian approaches have been suggested to test for the voxel activation in different brain regions.
Khalil Shafie, Mohammad Reza  Faridrohani, Siamak Noorbaloochi, Hossein Moradi Rekabdarkolaee   +3 more
doaj   +1 more source

Bayesian quantification of thermodynamic uncertainties in dense gas flows [PDF]

, 2014
A Bayesian inference methodology is developed for calibrating complex equations of state used in numerical fluid flow solvers. Precisely, the input parameters of three equations of state commonly used for modeling the thermodynamic behavior of so-called ...
CINNELLA, Paola, X. Merle, MERLE, Xavier
core   +1 more source