Understanding how the brain processes sounds using machine learning
Official title: CRCNS: Identifying principles of auditory cortical organization with machine learning
Funded at University of California at Davis · NIH-10886826 · Data updated 2026-11-12
This study looks at how our brains make sense of sounds, like music and speech, by comparing the brain activity of monkeys to computer models, and the goal is to help improve hearing aids and treatments for people with hearing issues.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California at Davis NIH-funded |
| Lab location | 1 site (Davis, United States) |
| Project start | July 12, 2023 |
| Project end | June 30, 2028 |
| Funding year | 2024 |
| Award (this year) | $379,319 |
| NIH project number | 5R01DC021600-02 |
| Project ID | NIH-10886826 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for participation or benefit from this research would include individuals with hearing disorders or those interested in auditory processing.
✕Less likely to help
Patients with no auditory processing issues or those not affected by hearing disorders may not receive direct benefits from this research.
What this research studies
This research investigates how the human auditory system interprets and organizes sounds into recognizable objects, such as music or speech. By comparing brain activity in macaque monkeys with artificial neural networks that mimic human sound processing, the study aims to uncover the principles of auditory cortical organization. The approach involves using advanced machine learning techniques to analyze how different sounds are represented in the brain, which could lead to better understanding of hearing disorders and improve auditory technologies. Patients may benefit from insights gained about sound processing and potential applications in hearing aids or therapies.
Why it matters
Potential benefit: If successful, this research could enhance our understanding of auditory processing, leading to improved treatments for hearing disorders and advancements in auditory technology.
How similar studies have gone: Other research has shown success in using machine learning to model brain functions, suggesting that this approach could yield valuable insights into auditory processing.
Where this research is happening
-
University of California at Davis
Davis, United States Active
Researchers
- Principal investigator: Recanzone, Gregg Howard — University of California at Davis
- Study coordinator: Recanzone, Gregg Howard
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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.