Name
Abstract | ||
|---|---|---|
Is there any hope of achieving a thorough understanding of higher functions such as perception, memory, thought and emotion or is the stunning complexity of the brain a barrier which will limit such efforts for the foreseeable future? In this perspective we discuss methods to handle complexity, approaches to model building, and point to detailed large-scale models as a new contribution to the toolbox of the computational neuroscientist. We elucidate some aspects which distinguishes large-scale models and some of the technological challenges which they entail. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.3389/neuro.11.001.2008 | Front. Neuroinform. |
Keywords | Field | DocType |
large-scale model,subsampling,computational neuroscience,simulation,brain,cortex,modeling methodology,parallel computing,biomedical research,neurosciences,bioinformatics | Data science,Scale model,Computational neuroscience,Computer science,Toolbox,Model building,Perception | Journal |
Volume | ISSN | Citations |
2 | 1662-5196 | 21 |
PageRank | References | Authors |
1.86 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mikael Djurfeldt | 1 | 298 | 22.07 |
| Örjan Ekeberg | 2 | 330 | 55.95 |
| Anders Lansner | 3 | 647 | 100.03 |