| _ | meg | _ |
|---|
| Automated Classification of Cognitive Visual Objects Using Multivariate Swarm Sparse Decomposition From Multichannel EEG- | meg | Signals |
| Automatic Spatial Calibration of Ultra-Low-Field MRI for High-Accuracy Hybrid | meg | -MRI |
| Bayesian Machine Learning: EEG/ | meg | signal processing measurements |
| Classifying Event-Related Desynchronization in EEG, ECoG and | meg | Signals |
| Conservative Finite Element Modeling of EEG and | meg | on Unstructured Grids |
| Debiased Estimation and Inference for Spatial-Temporal EEG/ | meg | Source Imaging |
| DECAF: | meg | -Based Multimodal Database for Decoding Affective Physiological Responses |
| Decoding affect in videos employing the | meg | brain signal |
| Differential transient | meg | and fMRI responses to visual stimulation onset rate |
| EEG/ | meg | source imaging in the absence of subject's brain MRI scan: Perspective on co-registration and MRI selection approach |
| Efficient | meg | signal decoding of direction in wrist movement using curve fitting (EMDC) |
| Fully-Automated Spike Detection and Dipole Analysis of Epileptic | meg | Using Deep Learning |
| Inverse EEG and | meg | Problems: The Adjoint State Approach I: The Continuous Case, The |
| Iterative Reweighted Mixed-Norm Estimate for Spatio-Temporal | meg | /EEG Source Reconstruction, The |
| Kernel alignment for identifying objective criteria from brain | meg | recordings in schizophrenia |
| meg | source reconstruction with basis functions source model |
| meg | , RFFTs, and the Hunt for High Frequency Oscillations |
| meg | -based imaging of focal neuronal current sources |
| meg | : Multi-Evidence GNN for Multimodal Semantic Forensics |
| meg | : Multi-Expert Gender Classification from Face Images in a Demographics-Balanced Dataset |
| meg | : Texture operators for multi-expert gender classification |
| Movie Genre Classification by Exploiting | meg | Brain Signals |
| New Application of | meg | and DTI on Word Recognition, A |
| Numerical aspects of spatio-temporal current density reconstruction from EEG-/ | meg | -data |
| Optical Co-Registration Method of Triaxial OPM- | meg | and MRI |
| Probabilistic Structure Learning for EEG/ | meg | Source Imaging With Hierarchical Graph Priors |
| Robust | meg | Source Localization of Event Related Potentials: Identifying Relevant Sources by Non-Gaussianity |
| signal-to-image transformation approach for EEG and | meg | signal classification, A |
| Source Extent Estimation in OPM- | meg | : A Two-Stage Champagne Approach |
| Source Imaging Method Based on Spatial Smoothing and Edge Sparsity (SISSES) and Its Application to OPM- | meg | |
| Spatially Sparse, Temporally Smooth | meg | Via Vector L_0 |
| Spatiotemporal forward solution of the EEG and | meg | using network modeling |
| STARTS: A Self-Adapted Spatio-Temporal Framework for Automatic E/ | meg | Source Imaging |
| Statistical Method for Source Localization in | meg | /EEG Tomographic Reconstruction Problem |
| Testing Viewpoint Invariance in the Neural Representation of Faces: An | meg | Study |
| Tetrahedral 3D finite element meshes of head tissues from MRI for the | meg | /EEG forward problem |
| Three-dimensional FDTD modeling of neurons to solve EEG and | meg | forward problem |
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