Understanding how brain activity is organized for efficient learning.
A multi-level framework for characterizing task-efficient coding geometry of neural population activities
['FUNDING_R01'] · NEW YORK UNIVERSITY · NIH-11158577
This study is looking at how our brains work when we learn, hoping to find ways to help people with cognitive disorders think and learn better.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | NEW YORK UNIVERSITY (nih funded) |
| Locations | 1 site (NEW YORK, UNITED STATES) |
| Trial ID | NIH-11158577 on ClinicalTrials.gov |
What this research studies
This research investigates the patterns of neural activity in the brain to understand how these patterns can be optimized for better learning and cognitive function. By using advanced computational models and machine learning techniques, the study aims to characterize the geometry of neural population activities across different brain regions. Patients may benefit from insights gained about how the brain processes information, potentially leading to improved treatments for cognitive disorders.
Who could benefit from this research
Good fit: Ideal candidates include individuals with cognitive challenges or those interested in understanding brain function related to learning.
Not a fit: Patients with acute neurological conditions or those not experiencing cognitive difficulties may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to enhanced learning strategies and therapies for cognitive impairments.
How similar studies have performed: Previous research in computational neuroscience has shown promise in understanding neural coding, suggesting that this approach could yield valuable insights.
Where this research is happening
NEW YORK, UNITED STATES
- NEW YORK UNIVERSITY — NEW YORK, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: CHUNG, SUEYEON — NEW YORK UNIVERSITY
- Study coordinator: CHUNG, SUEYEON
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.