Parallel linear programming in fixed dimension almost surely in constant time
Journal of the ACM (JACM)
Investigating the sparse simplex algorithm on a distributed memory multiprocessor
Parallel Computing - High performance computing in operations research
Learning to Decode Cognitive States from Brain Images
Machine Learning
On the computational complexity of coalitional resource games
Artificial Intelligence
A computational model of the cerebral cortex
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
A quantitative comparison of functional MRI cluster analysis
Artificial Intelligence in Medicine
Automated segmentation of human brain MR images using a multi-agent approach
Artificial Intelligence in Medicine
Gigaflops in linear programming
Operations Research Letters
| Hi-index | 0.00 |
This paper contributes to the emerging literature at the border between AI and cognitive neuroscience, analyzing the resource constraints that shape brain function. The brain is conceptualized as a set of areas that collaborate to perform complex cognitive tasks. Both (1) computation within individual areas and (2) communication between collaborating areas are viewed as resource-consuming activities. The efficient deployment of limited resources is formalized as a Linear Programming problem which the brain is hypothesized to solve on a moment-by-moment basis. A model of language processing is analyzed within this framework and found to exhibit resource utilization profiles consistent with those observed in functional neuroimaging studies of humans.