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Reconstructing anatomy from electro-physiological data
(Academic Press Inc., 2017)
© 2017 Here we show how it is possible to make estimates of brain structure based on MEG data. We do this by reconstructing functional estimates onto distorted cortical manifolds parameterised in terms of their spherical ...
Reconstructing anatomy from electro physiological data
(Elsevier, 2017)
Here we show how it is possible to make estimates of brain structure based on MEG data. We do this by reconstructing functional estimates onto distorted cortical manifolds parameterised in terms of their spherical harmonics. ...
Single meg/eeg source reconstruction with multiple sparse priors and variable patches
(Universidad Nacional de Colombia Sede Medellín, 2012)
MEG/EEG brain imaging has become an important tool in neuroimaging. The reconstruction of cortical current flow is an ill-posed problem, but its uncertainty can be reduced by including prior information within a Bayesian ...
Imágenes del cerebro basadas en algoritmos Bayesianos para problemas inversos mal condicionados MEG/EEG
(2012)
La reconstrucción de actividad neuronal con datos EEG/MEG es un problema mal condicionado y sujeto a incertidumbre. En este documento de tesis se presenta un análisis de las técnicas Bayesianas utilizadas para resolver el ...
An integrative model of auditory phantom perception: tinnitus as a unified percept of interacting separable subnetworks
(Elsevier, 2013-04-15)
Tinnitus is a considered to be an auditory phantom phenomenon, a persistent conscious percept of a salient memory trace, externally attributed, in the absence of a sound source. It is perceived as a phenomenological unified ...
Exploring the temporal dynamics of speech production with EEG and group ICA
(Scientific Reports, 2020)
A graph-theoretical approach in brain functional networks. Possible implications in EEG studies
(2010)
Abstract
Background
Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging ...
Periodogram Connectivity of EEG Signals for the Detection of Dyslexia
(Corporación Universidad de la Costa, 2020)