Results 261 to 270 of about 5,911,579 (291)

Dynamic Causal Modeling With Genetic Algorithms

Journal of Neuroscience Methods, 2011
In the last years, dynamic causal modeling has gained increased popularity in the neuroimaging community as an approach for the estimation of effective connectivity from functional magnetic resonance imaging (fMRI) data. The algorithm calls for an a priori defined model, whose parameter estimates are subsequently computed upon the given data.
Tilo T. Kircher, Dominik Heider, Andreas Jansen   +2 more
exaly   +3 more sources

Dynamic Causal Modeling With Neural Fields

NeuroImage, 2012
The aim of this paper is twofold: first, to introduce a neural field model motivated by a well-known neural mass model; second, to show how one can estimate model parameters pertaining to spatial (anatomical) properties of neuronal sources based on EEG or LFP spectra using Bayesian inference.
Karl J. Friston, Dimitris A. Pinotsis, R J Moran   +2 more
exaly   +4 more sources

Mpdcm: A Toolbox for Massively Parallel Dynamic Causal Modeling

Journal of Neuroscience Methods, 2016
BACKGROUND: Dynamic causal modeling (DCM) for fMRI is an established method for Bayesian system identification and inference on effective brain connectivity. DCM relies on a biophysical model that links hidden neuronal activity to measurable BOLD signals.
Jakob Heinzle, Eduardo A Aponte, William Penny   +2 more
exaly   +2 more sources

Dynamic modelling and causality

Scandinavian Actuarial Journal, 1987
Abstract In 1965 Erling Sverdrup published a paper on the use of Markov chains in modelling disability. This paper has been a source of inspiration for further development of statistical theory for Markov processes and the closely related counting processes.
openaire   +1 more source

Dynamic causal modelling for schizophrenia

2011 International Symposium on Humanities, Science and Engineering Research, 2011
Schizophrenia is a complex psychiatric disorder which leads to local abnormalities in brain activity. Functional Magnetic Resonance Imaging (fMRI) technology enables medical doctors to observe brain activity patterns that represent the execution of subject tasks, both physical and mental. In general, each subject exhibits his own activation pattern for
M. B. Nagori, W. Gore Ranjana, Madhuri Joshi   +2 more
openaire   +1 more source

Evaluating Effective Connectivity of Trust in Human–Automation Interaction: A Dynamic Causal Modeling (DCM) Study

Human Factors, 2022
Jiali Huang, Chang S Nam, Sanghyun Choo
exaly  

Multiple-Shooting Adjoint Method for Whole-Brain Dynamic Causal Modeling

Lecture Notes in Computer Science, 2021
James Duncan, Pamela Ventola, Sekhar Tatikonda   +2 more
exaly  

Dynamic Causal Modeling for Evoked Responses

2009
Kiebel, Stefan J., Garrido, Marta I., Friston, Karl J.   +2 more
openaire   +3 more sources

Studying Brain Circuit Function With Dynamic Causal Modeling for Optogenetic fMRI

Neuron, 2017
Jin Hyung Lee, David Bernal-Casas, Hyun Joo Lee   +2 more
exaly  

A Causal Approach to Dynamics Modeling.

IEEE Database Eng. Bull., 1984
DE ANTONELLIS, Valeria, B. Zonta
openaire   +2 more sources