Search Results - "Daunizeau, J."

Bayesian model selection for group studies — Revisited by Rigoux, L., Stephan, K.E., Friston, K.J., Daunizeau, J.

“…In this paper, we revisit the problem of Bayesian model selection (BMS) at the group level. We originally addressed this issue in Stephan et al. (2009), where…”
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Dynamic causal modelling of brain–behaviour relationships by Rigoux, L., Daunizeau, J.

“…In this work, we expose a mathematical treatment of brain–behaviour relationships, which we coin behavioural Dynamic Causal Modelling or bDCM. This approach…”
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Dynamic causal modelling: A critical review of the biophysical and statistical foundations by Daunizeau, J., David, O., Stephan, K.E.

“…The goal of dynamic causal modelling (DCM) of neuroimaging data is to study experimentally induced changes in functional integration among brain regions. This…”
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An Overcomplete Approach to Fitting Drift-Diffusion Decision Models to Trial-By-Trial Data by Feltgen, Q, Daunizeau, J

“…Drift-diffusion models or DDMs are becoming a standard in the field of computational neuroscience. They extend models from signal detection theory by proposing…”
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Ten simple rules for dynamic causal modeling by Stephan, K.E., Penny, W.D., Moran, R.J., den Ouden, H.E.M., Daunizeau, J., Friston, K.J.

“…Dynamic causal modeling (DCM) is a generic Bayesian framework for inferring hidden neuronal states from measurements of brain activity. It provides posterior…”
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Computational neuroimaging strategies for single patient predictions by Stephan, K.E., Schlagenhauf, F., Huys, Q.J.M., Raman, S., Aponte, E.A., Brodersen, K.H., Rigoux, L., Moran, R.J., Daunizeau, J., Dolan, R.J., Friston, K.J., Heinz, A.

“…Neuroimaging increasingly exploits machine learning techniques in an attempt to achieve clinically relevant single-subject predictions. An alternative to…”
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Stochastic dynamic causal modelling of fMRI data: Should we care about neural noise? by Daunizeau, J., Stephan, K.E., Friston, K.J.

“…Dynamic causal modelling (DCM) was introduced to study the effective connectivity among brain regions using neuroimaging data. Until recently, DCM relied on…”
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DEM: A variational treatment of dynamic systems by Friston, K.J., Trujillo-Barreto, N., Daunizeau, J.

“…This paper presents a variational treatment of dynamic models that furnishes time-dependent conditional densities on the path or trajectory of a system's…”
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Variational Bayesian identification and prediction of stochastic nonlinear dynamic causal models by Daunizeau, J., Friston, K.J., Kiebel, S.J.

“…In this paper, we describe a general variational Bayesian approach for approximate inference on nonlinear stochastic dynamic models. This scheme extends…”
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Recent advances in recording electrophysiological data simultaneously with magnetic resonance imaging by Laufs, H., Daunizeau, J., Carmichael, D.W., Kleinschmidt, A.

“…Simultaneous recording of brain activity by different neurophysiological modalities can yield insights that reach beyond those obtained by each technique…”
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Evaluation of EEG localization methods using realistic simulations of interictal spikes by Grova, C., Daunizeau, J., Lina, J.-M., Bénar, C.G., Benali, H., Gotman, J.

“…Performing an accurate localization of sources of interictal spikes from EEG scalp measurements is of particular interest during the presurgical investigation…”
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EEG-fMRI integration: a critical review of biophysical modeling and data analysis approaches by Rosa, M J, Daunizeau, J, Friston, K J

“…The diverse nature of cerebral activity, as measured using neuroimaging techniques, has been recognised long ago. It seems obvious that using single modality…”
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A neural mass model of spectral responses in electrophysiology by Moran, R.J., Kiebel, S.J., Stephan, K.E., Reilly, R.B., Daunizeau, J., Friston, K.J.

“…We present a neural mass model of steady-state membrane potentials measured with local field potentials or electroencephalography in the frequency domain. This…”
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Concordance between distributed EEG source localization and simultaneous EEG-fMRI studies of epileptic spikes by Grova, C., Daunizeau, J., Kobayashi, E., Bagshaw, A.P., Lina, J-M., Dubeau, F., Gotman, J.

“…In order to analyze where epileptic spikes are generated, we assessed the level of concordance between EEG source localization using distributed source models…”
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Learning and generalization under ambiguity: an fMRI study by Chumbley, J R, Flandin, G, Bach, D R, Daunizeau, J, Fehr, E, Dolan, R J, Friston, K J

“…Adaptive behavior often exploits generalizations from past experience by applying them judiciously in new situations. This requires a means of quantifying the…”
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Accurate Anisotropic Fast Marching for Diffusion-Based Geodesic Tractography by Jbabdi, S., Bellec, P., Toro, R., Daunizeau, Jean, Pélégrini-Issac, M., Benali, Habib

“…Using geodesics for inferring white matter fibre tracts from diffusion-weighted MR data is an attractive method for at least two reasons: (i) the method…”
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Bayesian spatio-temporal approach for EEG source reconstruction: conciliating ECD and distributed models by Daunizeau, J., Mattout, J., Clonda, D., Goulard, B., Benali, H., Lina, J.-M.

“…Characterizing the cortical activity sources of electroencephalography (EEG)/magnetoencephalography data is a critical issue since it requires solving an…”
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Diffusion-based spatial priors for functional magnetic resonance images by Harrison, L.M., Penny, W., Daunizeau, J., Friston, K.J.

“…We recently outlined a Bayesian scheme for analyzing fMRI data using diffusion-based spatial priors [Harrison, L.M., Penny, W., Ashburner, J.,…”
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A Generic Framework for fMRI-constrained MEG Source Reconstruction by Flandin, G., Henson, R., Daunizeau, J., Friston, K., Mattout, J.

“…Introduction In a series of previous communications, we described a Parametric Empirical Bayes (PEB) approach to MEG source reconstruction that accounts for…”
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An electrophysiological validation of stochastic DCM for fMRI by Daunizeau, J, Lemieux, L, Vaudano, A E, Friston, K J, Stephan, K E

“…In this note, we assess the predictive validity of stochastic dynamic causal modeling (sDCM) of functional magnetic resonance imaging (fMRI) data, in terms of…”
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