Name
Abstract | ||
|---|---|---|
A crucial challenge for both clinical and systems neuroscience is reliable mapping of brain networks to higher-order cognitive functions in both health and disease. In this paper, we map the brain's emerging language network in the human connectome based on data from rTMS studies on healthy volunteers as well as brain tumor patients. The key finding is that cortical areas which are involved in the language network are more likely to be connected to Wernicke's and Broca's areas based on standard graph theoretic measures. In addition, the higher the connectivity of a particular area to the classic language areas, the more likely it is that region is involved in the language network. We comment on the clinical value that these structure-function connectome maps can have for planning and aiding neurosurgical procedures. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-44778-0_10 | ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2016, PT I |
Keywords | Field | DocType |
Brain mapping, Connectomics, Neurosurgery | Brain mapping,Graph,Neuroscience,Connectomics,Computer science,Connectome,Brain tumor,Artificial intelligence,Human Connectome,Cognition,Systems neuroscience,Machine learning | Conference |
Volume | ISSN | Citations |
9886 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gregory Zegarek | 1 | 0 | 0.34 |
| Xerxes D. Arsiwalla | 2 | 84 | 17.84 |
| David Dalmazzo | 3 | 1 | 0.70 |
| Paul F. M. J. Verschure | 4 | 677 | 116.64 |