Abstract
ECoG ClusterFlow is a novel multi-scale visual analysis system for the detailed exploration of dynamic functional connectivity graphs obtained through electrocorticography.
- Developers:
- Release Date:
- 2017-04-24
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Licenses:
-
Other (Commercial or Open-Source): https://github.com/sugeerth/ECoG-ClusterFlow/blob/master/LICENSE
- Sponsoring Org.:
-
USDOEPrimary Award/Contract Number:AC02-05CH11231
- Code ID:
- 5237
- Site Accession Number:
- 7463
- Research Org.:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Country of Origin:
- United States
Citation Formats
MURUGESAN, SUGEERTH, and WEBER, GUNTHER.
ECoG Cluster Flow v1.0.
Computer Software.
https://github.com/sugeerth/ECoG-ClusterFlow.
USDOE.
24 Apr. 2017.
Web.
doi:10.11578/dc.20171025.1938.
MURUGESAN, SUGEERTH, & WEBER, GUNTHER.
(2017, April 24).
ECoG Cluster Flow v1.0.
[Computer software].
https://github.com/sugeerth/ECoG-ClusterFlow.
https://doi.org/10.11578/dc.20171025.1938.
MURUGESAN, SUGEERTH, and WEBER, GUNTHER.
"ECoG Cluster Flow v1.0." Computer software.
April 24, 2017.
https://github.com/sugeerth/ECoG-ClusterFlow.
https://doi.org/10.11578/dc.20171025.1938.
@misc{
doecode_5237,
title = {ECoG Cluster Flow v1.0},
author = {MURUGESAN, SUGEERTH and WEBER, GUNTHER},
abstractNote = {ECoG ClusterFlow is a novel multi-scale visual analysis system for the detailed exploration of dynamic functional connectivity graphs obtained through electrocorticography.},
doi = {10.11578/dc.20171025.1938},
url = {https://doi.org/10.11578/dc.20171025.1938},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20171025.1938}},
year = {2017},
month = {apr}
}