Results 11 to 20 of about 2,193,761 (259)

The myth of the Bayesian brain. [PDF]

Eur J Appl Physiol
The Bayesian brain hypothesis—the idea that neural systems implement or approximate Bayesian inference—has become a dominant framework in cognitive neuroscience over the past two decades. While mathematically elegant and conceptually unifying, this paper
Mangalam M.
europepmc   +2 more sources

Spatial 3D Matérn Priors for Fast Whole-Brain fMRI Analysis

, 2021
Bayesian whole-brain functional magnetic resonance imaging (fMRI) analysis with three-dimensional spatial smoothing priors has been shown to produce state-of-the-art activity maps without pre-smoothing the data.
Lindgren, Finn,, Bolin, David, Eklund, Anders,, Bolin, David,, Sidén, Per, Eklund, Anders, Villani, Mattias, Sidén, Per,, Lindgren, Finn, Villani, Mattias,, David Bolin, Finn Lindgren, Mattias Villani, Per Sidén, Anders Eklund   +14 more
core   +1 more source

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, Leighton Hinkley, Yijing Gao, Ali Hashemi, Stefan Haufe, Kensuke Sekihara, Srikantan S. Nagarajan   +6 more
doaj   +1 more source

Searching multiregression dynamic models of resting-state fMRI networks using integer programming [PDF]

, 2015
A Multiregression Dynamic Model (MDM) is a class of multivariate time series that represents various dynamic causal processes in a graphical way. One of the advantages of this class is that, in contrast to many other Dynamic Bayesian Networks, the ...
Smith, Jim, Cussens, James, Duff, Eugene P., Nichols, Thomas, Makin, Tamar, Costa, Lilia, Smith, J. Q., Duff, Eugene, Makin, Tamar R., Nichols, Thomas E.   +9 more
core   +1 more source

Bayesian Approximations to Hidden Semi-Markov Models for Telemetric Monitoring of Physical Activity [PDF]

, 2022
We propose a Bayesian hidden Markov model for analyzing time series and sequential data where a special structure of the transition probability matrix is embedded to model explicit-duration semi-Markovian dynamics.
Fiecas, Mark, Jewson, Jack, Hadj-Amar, Beniamino, Mark Fiecas, Jack Jewson, Beniamino Hadj-Amar   +5 more
core   +1 more source

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
doaj   +1 more source

The Bayesian Virtual Epileptic Patient: A probabilistic framework designed to infer the spatial map of epileptogenicity in a personalized large-scale brain model of epilepsy spread

NeuroImage, 2020
Despite the importance and frequent use of Bayesian frameworks in brain network modeling for parameter inference and model prediction, the advanced sampling algorithms implemented in probabilistic programming languages to overcome the inference ...
M. Hashemi, A.N. Vattikonda, V. Sip, M. Guye, F. Bartolomei, M.M. Woodman, V.K. Jirsa   +6 more
doaj   +1 more source

Efficient utility-based clustering over high dimensional partition spaces [PDF]

, 2009
Because of the huge number of partitions of even a moderately sized dataset, even when Bayes factors have a closed form, in model-based clustering a comprehensive search for the highest scoring (MAP) partition is usually impossible.
Smith, JQ, Millar, A. J., Millar, AJ, Liverani, Silvia, Smith, J. Q., Liverani, S, Anderson, Paul E., Anderson, PE, Edwards, Kieron D., Edwards, KD   +9 more
core   +1 more source

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, Jian Kang, Tianwei Yu, Tianwei Yu   +3 more
doaj   +1 more source

Bayesian mapping of brain regions using compound Markov random field priors [PDF]

, 2003
Human brain mapping, i.e. the detection of functional regions and their connections, has experienced enormous progress through the use of functional magnetic resonance imaging (fMRI).
Gössl, Christoff, Fahrmeir, Ludwig, Hennerfeind, Andrea   +2 more
core   +1 more source