NETWORK OPTIMIZATION IN THE BRAIN [II, 2000]: Cerebral Cortex Layout
dc.contributor.author | Cherniak, Christopher | en_US |
dc.date.accessioned | 2004-05-31T23:32:13Z | |
dc.date.available | 2004-05-31T23:32:13Z | |
dc.date.created | 2003-09 | en_US |
dc.date.issued | 2003-09-25 | en_US |
dc.description.abstract | The hypothesis is that longrange connections in the brain are a critically constrained resource, hence there is strong selective pressure to optimize finely their deployment, to "minimize wire." Two methodological ideas are introduced: (1) Because of unfeasibility of measuring wirelengths in the cortex, a simpler adjacency-cost was validated. (2) To deal with incomplete information on brain networks, a Size Law was developed that predicts optimization patterns in subnetworks. Sensory areas of macaque and of cat cortex appear to be positioned to minimize connection costs, in some cases down to current limits of detectability. These optimization results begin to approach some of the most precise confirmed predictions in neuroscience. [ MH49867 2/00 68.3 ] (UMIACS-TR-2003-93) | en_US |
dc.format.extent | 1821306 bytes | |
dc.format.mimetype | application/pdf | |
dc.identifier.uri | http://hdl.handle.net/1903/1311 | |
dc.language.iso | en_US | |
dc.relation.isAvailableAt | Digital Repository at the University of Maryland | en_US |
dc.relation.isAvailableAt | University of Maryland (College Park, Md.) | en_US |
dc.relation.isAvailableAt | Tech Reports in Computer Science and Engineering | en_US |
dc.relation.isAvailableAt | UMIACS Technical Reports | en_US |
dc.relation.ispartofseries | UM Computer Science Department; CS-TR-4525 | en_US |
dc.relation.ispartofseries | UMIACS; UMIACS-TR-2003-93 | en_US |
dc.title | NETWORK OPTIMIZATION IN THE BRAIN [II, 2000]: Cerebral Cortex Layout | en_US |
dc.type | Technical Report | en_US |
Files
Original bundle
1 - 1 of 1