| Title |
Source Connectivity Analysis from MEG and its Application to Epilepsy Source Localization
|
|---|---|
| Published in |
Brain Topography, November 2011
|
| DOI | 10.1007/s10548-011-0211-0 |
| Pubmed ID | |
| Authors |
Yakang Dai, Wenbo Zhang, Deanna L. Dickens, Bin He |
| Abstract |
We report an approach to perform source connectivity analysis from MEG, and initially evaluate this approach to interictal MEG to localize epileptogenic foci and analyze interictal discharge propagations in patients with medically intractable epilepsy. Cortical activities were reconstructed from MEG using individual realistic geometry boundary element method head models. Directional connectivity among cortical regions of interest was then estimated using directed transfer function. The MEG source connectivity analysis method was implemented in the eConnectome software, which is open-source and freely available at http://econnectome.umn.edu . As an initial evaluation, the method was applied to study MEG interictal spikes from five epilepsy patients. Estimated primary epileptiform sources were consistent with surgically resected regions, suggesting the feasibility of using cortical source connectivity analysis from interictal MEG for potential localization of epileptiform activities. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 2 | 2% |
| United States | 2 | 2% |
| China | 1 | 1% |
| Korea, Republic of | 1 | 1% |
| Unknown | 91 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 19 | 20% |
| Researcher | 16 | 16% |
| Student > Master | 10 | 10% |
| Professor > Associate Professor | 9 | 9% |
| Student > Doctoral Student | 7 | 7% |
| Other | 24 | 25% |
| Unknown | 12 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 24 | 25% |
| Engineering | 19 | 20% |
| Neuroscience | 19 | 20% |
| Computer Science | 5 | 5% |
| Agricultural and Biological Sciences | 3 | 3% |
| Other | 7 | 7% |
| Unknown | 20 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 February 2012.
All research outputs
#15,242,272
of 22,663,150 outputs
Outputs from Brain Topography
#303
of 483 outputs
Outputs of similar age
#161,869
of 238,834 outputs
Outputs of similar age from Brain Topography
#3
of 4 outputs
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