CAREER: Contextual gating of information flow in large-scale brain network models — NSF Award to University of Pittsburgh (PA, $59
Faced with an ever-changing environment of rich and complex stimuli, the brain needs to flexibly adapt to changes in the outside world to efficiently process relevant information. This project studies how the brain selectively processes relevant information depending on task demands and coordinates across different bra
| Award title | CAREER: Contextual gating of information flow in large-scale brain network models |
|---|---|
| Award ID | 2337640 |
| Awardee | University of Pittsburgh |
| City | PITTSBURGH |
| State | PA |
| Amount obligated | $591,367 |
| Principal investigator | Chengcheng Huang |
| Program | Robust Intelligence |
| Start date | 10/01/2024 |
| Abstract | Faced with an ever-changing environment of rich and complex stimuli, the brain needs to flexibly adapt to changes in the outside world to efficiently process relevant information. This project studies how the brain selectively processes relevant information depending on task demands and coordinates across different brain regions to support flexible behavior. This project will develop a comprehensive framework to analyze information flow in large-scale brain network models. Research findings will |
| Source | NSF Awards |
$799/mo
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