To this end, an inverse method has been developed using sparse data and model constraints to generate estimates of brain motion. Based on methodology from ocean ...
To this end, an inverse method has been developed using sparse data and model constraints to generate estimates of brain motion. Based on methodology from ocean ...
surface motion for use in brain deformation modeling. The surgical procedure ... Inverse technique for combined model and sparse data estimates of brain motion.
Nov 8, 2014 · We first describe how to extract functional connectivity-based features from fMRI, using sparse inverse covariance models and other correlation- ...
We adopt the framework to provide insight into the performance of several linear inverse operators in reconstructing propagating cortical activity from MEG/EEG ...
Mar 1, 2007 · This relatively simple inverse finite-element approach is investigated within the context of a series of phantom experiments, two in vivo cases, ...
The proposed framework is capable of estimation the discriminative brain sources under given different brain states where traditional inverse methods failed ...
Based on free-knot splines techniques, we develop a fully Bayesian method to make inference about the autoregressive and functional-coefficient moving-average ...
Missing: motion. | Show results with:motion.
May 30, 2024 · Compute MNE inverse solution on evoked data with a mixed source space ... Estimate data SNR using an inverse · Computing ... data/MEG/sample/ ...
Characterizing interactions between multiple brain regions is important for understanding brain function. Functional connectivity measures based on partial ...