Pinned Repositories
MEEG_Source_Connectivity_SoftPack
BC-VARETA-simpack
Hierarchical Hermitian Gaussian Graphical Model (HHGGM): Methodological approach to "caulk" the "Leakage Effect" in MEEG source activity and connectivity. HHGGM leverages two theoretical aspects. First: Joint estimation of source activity and connectivity as a frequency domain linear dynamical system identification approach. Second: Incorporating priors into the sources graphical model of the connectivity estimator. The claims of this theory are supported by a simulation framework, that uses realistic head models, diverse sources setup, biological/instrumentation noisy signals, and Inverse Crime evaluation. Also, by providing comparisons to state of the art methodologies.
BC-VARETA_Toolbox
CBIG
CiftiMorph
A repository to compute volume based or surface based integro-diferential operators, and processing fields defined ny these operators. Surfaced based Laplace Beltrami and Interpolant operators are available
Elastic-Net-and-Elitist-Lasso-Sparse-Bayesian-Learning
freesurfer
Neuroimaging analysis and visualization suite
Neural_Mass_Modeling
This tool provides a new formulation of Zetterberg-Jansen and Rit Neural Mass Models (ZJR NMM), considering distributed delays and kinetics information. Numerical integration was carried out through Local Lineariation Method (LLM) to increase the program efficiency
BC-VARETA-toolbox
Tool for MEEG data processing based on Brain Connectivity Variable Resolution Tomographic Analysis (BC-VARETA) Model
Tensor-BC-VARETA
Populational Super-Resolution Cross-Spectral MEEG Source Connectivity Analysis. Tensor extension of BC-VARETA to population and frequency domain analysis.
dpazlinares's Repositories
dpazlinares/BC-VARETA-simpack
Hierarchical Hermitian Gaussian Graphical Model (HHGGM): Methodological approach to "caulk" the "Leakage Effect" in MEEG source activity and connectivity. HHGGM leverages two theoretical aspects. First: Joint estimation of source activity and connectivity as a frequency domain linear dynamical system identification approach. Second: Incorporating priors into the sources graphical model of the connectivity estimator. The claims of this theory are supported by a simulation framework, that uses realistic head models, diverse sources setup, biological/instrumentation noisy signals, and Inverse Crime evaluation. Also, by providing comparisons to state of the art methodologies.
dpazlinares/Elastic-Net-and-Elitist-Lasso-Sparse-Bayesian-Learning
dpazlinares/BC-VARETA_Toolbox
dpazlinares/CBIG
dpazlinares/CiftiMorph
A repository to compute volume based or surface based integro-diferential operators, and processing fields defined ny these operators. Surfaced based Laplace Beltrami and Interpolant operators are available
dpazlinares/freesurfer
Neuroimaging analysis and visualization suite
dpazlinares/Neural_Mass_Modeling
This tool provides a new formulation of Zetterberg-Jansen and Rit Neural Mass Models (ZJR NMM), considering distributed delays and kinetics information. Numerical integration was carried out through Local Lineariation Method (LLM) to increase the program efficiency