activity
20112019
most citedSparsity Enables Estimation of both Subcortical and Cortical Activity from MEG and EEG

165 citations · 242 across the 7 of their papers we have counts for

collaborators

7 papers

q-bio.NC2019

Constructing a control-ready model of EEG signal during general anesthesia in humans

John H. Abel, Marcus A. Badgeley, Taylor E. Baum +3

Significant effort toward the automation of general anesthesia has been made in the past decade. One open challenge is in the development of control-ready patient models for closed…

stat.AP2019★ 1 cited

Probabilistic Structure Learning for EEG/MEG Source Imaging with Hierarchical Graph Prior

Feng Liu, Li Wang, Yifei Lou +2

Brain source imaging is an important method for noninvasively characterizing brain activity using Electroencephalogram (EEG) or Magnetoencephalography (MEG) recordings. Traditional…

stat.ME2017★ 4 cited

In reply to Faes et al. and Barnett et al. regarding "A study of problems encountered in Granger causality analysis from a neuroscience perspective"

Patrick A. Stokes, Patrick L. Purdon

This reply is in response to commentaries by Barnett, Barrett, and Seth (arXiv:1708.08001) and Faes, Stramaglia, and Marinazzo (arXiv:1708.06990) on our paper entitled "A study of…

q-bio.QM2017★ 165 cited

Sparsity Enables Estimation of both Subcortical and Cortical Activity from MEG and EEG

Pavitra Krishnaswamy, Gabriel Obregon-Henao, Jyrki Ahveninen +5

Subcortical structures play a critical role in brain function. However, options for assessing electrophysiological activity in these structures are limited. Electromagnetic fields…

stat.AP2015★ 2 cited

An Analysis of How Spatiotemporal Dynamic Models of Brain Activity Could Improve MEG/EEG Inverse Solutions

Camilo Lamus, Matti S. Hamalainen, Emery N. Brown +1

MEG and EEG are noninvasive functional neuroimaging techniques that provide recordings of brain activity with high temporal resolution, and thus provide a unique window to study fa…

stat.AP2015★ 32 cited

A Spatiotemporal Dynamic Solution to the MEG Inverse Problem: An Empirical Bayes Approach

Camilo Lamus, Matti S. Hämäläinen, Simona Temereanca +2

MEG/EEG are non-invasive imaging techniques that record brain activity with high temporal resolution. However, estimation of brain source currents from surface recordings requires…