NSF-SNSF: Scalable accelerated learning in continuous neuronal systems — NSF Award to Yale University (CT, $400,000)
Computer simulations are an essential part of modern scientific inquiry. They allow detailed investigations of phenomena at time and length scales difficult to observe directly. In particular for complex systems such as the human brain, they have become indispensable for testing hypotheses and making predictions for ex
| Award title | NSF-SNSF: Scalable accelerated learning in continuous neuronal systems |
|---|---|
| Award ID | 2449506 |
| Awardee | Yale University |
| City | NEW HAVEN |
| State | CT |
| Amount obligated | $400,000 |
| Principal investigator | Rajit Manohar |
| Program | EPMQD: Electronic, Photonic, M |
| Start date | 04/01/2025 |
| Abstract | Computer simulations are an essential part of modern scientific inquiry. They allow detailed investigations of phenomena at time and length scales difficult to observe directly. In particular for complex systems such as the human brain, they have become indispensable for testing hypotheses and making predictions for experiments. Cognitive phenomena such as learning and memory evolve on timescales from minutes to years, while the underlying processes on the level of individual nerve cells involve |
| Source | NSF Awards |
$799/mo
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