about
sameAs
Optimizing experimental design for comparing models of brain functionTen simple rules for dynamic causal modeling.Inferring on the intentions of others by hierarchical Bayesian learningRecognizing sequences of sequences.Comparing families of dynamic causal modelsVBA: a probabilistic treatment of nonlinear models for neurobiological and behavioural dataModelling trial-by-trial changes in the mismatch negativityStriatal prediction error modulates cortical coupling.Perception and hierarchical dynamics.A hierarchy of time-scales and the brain.Spatial attention, precision, and Bayesian inference: a study of saccadic response speedRecent advances in recording electrophysiological data simultaneously with magnetic resonance imaging.Reinforcement learning or active inference?The combination of EEG source imaging and EEG-correlated functional MRI to map epileptic networks.Dynamic causal modelling: a critical review of the biophysical and statistical foundations.Observing the observer (I): meta-bayesian models of learning and decision-making.Observing the observer (II): deciding when to decide.EEG-fMRI integration: a critical review of biophysical modeling and data analysis approaches.Toward a new application of real-time electrophysiology: online optimization of cognitive neurosciences hypothesis testing.EEG and MEG data analysis in SPM8.Concepts of connectivity and human epileptic activityDynamic causal modelling of anticipatory skin conductance responses.Learning and generalization under ambiguity: an fMRI studyStochastic dynamic causal modelling of fMRI data: should we care about neural noise?Dynamic causal modeling of spontaneous fluctuations in skin conductance.The social Bayesian brain: does mentalizing make a difference when we learn?Network discovery with DCMTheory of mind: did evolution fool us?Learning about and from others' prudence, impatience or laziness: The computational bases of attitude alignment.Subliminal instrumental conditioning demonstrated in the human brain.Nonlinear dynamic causal models for fMRI.Effective connectivity: influence, causality and biophysical modelingDoes the way we read others' mind change over the lifespan? Insights from a massive web poll of cognitive skills from childhood to late adulthood.Variational Bayesian mixed-effects inference for classification studies.Population dynamics under the Laplace assumption.Automatic integration of confidence in the brain valuation signal.Dynamic causal modelling of brain-behaviour relationships.Uncertainty in perception and the Hierarchical Gaussian Filter.An electrophysiological validation of stochastic DCM for fMRI.Accurate anisotropic fast marching for diffusion-based geodesic tractography
P50
Q21145318-DBA195F2-31D0-4E69-AEAA-A289FD4757E9Q24645074-5E8B62F6-4506-4E0F-84EB-38D1925A6C9FQ27321128-2A43D467-21C7-40D1-BC16-136D94C55FD4Q27335455-21546D9B-C8A0-4270-B1BF-08EDDC83684DQ28473192-A7D2D1E0-8132-4A91-B1A8-B4965E19E037Q30000686-7113D3E1-B139-40C6-B3F6-D5CB6EAC1DA2Q30458006-BE5B0D50-53C9-44E1-B529-E56F1FF8F6EBQ30476854-8D96132B-53E7-4F3B-8034-7E7D23E9AFA8Q30487891-F3221E51-9C95-4C16-B83D-54D0203D4E04Q30492724-2A7AC107-3B41-4E6F-849A-1738AD65ADD0Q30577681-9752A1D1-391C-48D8-A411-2DBCB9057F26Q31143016-1A9B59E4-1A7A-409C-96FE-B340D0FAC710Q33488532-E71B9FEC-C692-48AC-86DC-24A2CD8ACB40Q33509611-545D423A-47C0-4169-A468-670C95CDEE44Q33517246-570C7F7A-AB70-496D-B9E1-6D2C6B9C1F15Q33778560-E4A0EC16-C4AA-470C-9833-2308E712F615Q33778574-CEB037C2-75E9-4028-85EC-11906457F7F6Q33788076-BE966F04-1FC5-4AB2-82CE-16EE54378470Q33788908-929DBFD0-0E42-445D-AFC5-772FE0B27092Q33855504-80E4B41E-3E5F-4B46-9528-0EA2CFD848AEQ33864612-82BF2604-A971-4D5C-8691-A599919FC032Q34073488-876D19FB-79C5-40C9-834B-8DB4F5994E4AQ34139899-D9198F09-A6BA-45D9-BCCF-66F885B9D970Q34266801-9AF536ED-3738-486A-B2DD-1AF8D88DFCF3Q34577311-1B796D08-38A9-45BE-956A-A18071ABAA79Q34633014-45C29C38-3D3F-482E-B9C9-2CD199285A6CQ34982217-0D744CEA-D6C2-41B1-A587-2D22CC9B4D77Q35088192-CA1066CD-44BE-452B-A3EA-D9E19943CF61Q36328314-B4222CC7-D211-4EFF-9934-FF8A02E6C1ACQ36948399-0CE8E41E-F422-42D3-A868-552F592F846FQ37086098-004E393D-B27E-411A-81B5-5AC9B51B0E7EQ38314475-BE5D2B5F-534D-4200-822C-145500FC1071Q39303179-2ED0F435-C284-40A3-8769-1D72DDDD7B78Q39449126-09F2C453-241D-46E8-9C08-E83A8852D617Q40027350-61D000B9-4D8B-4663-9677-9949F0EFD661Q40717322-D2CEEE6F-4823-43DA-9A36-DA56EA1538A8Q40904200-D78CE037-032E-49C2-8140-EEB47658B981Q41724654-87570054-9A90-416E-8DE9-918BA147F7D0Q41824873-5CCBF0C4-1E67-40FE-B933-494C992D3071Q41957183-C2210700-1C76-4F23-ACAF-D3C2BB5F3583
P50
description
hulumtues
@sq
onderzoeker
@nl
researcher
@en
հետազոտող
@hy
name
Jean Daunizeau
@ast
Jean Daunizeau
@en
Jean Daunizeau
@es
Jean Daunizeau
@nl
Jean Daunizeau
@sl
type
label
Jean Daunizeau
@ast
Jean Daunizeau
@en
Jean Daunizeau
@es
Jean Daunizeau
@nl
Jean Daunizeau
@sl
prefLabel
Jean Daunizeau
@ast
Jean Daunizeau
@en
Jean Daunizeau
@es
Jean Daunizeau
@nl
Jean Daunizeau
@sl
P1053
F-9225-2010
P106
P21
P2456
P31
P3829
P496
0000-0001-9142-1270