If you think self-driving cars can’t get here soon enough, you’re not alone. But programming computers to recognize objects is very technically challenging, especially since scientists don’t fully understand how our own brains do it. How precisely this recognition happens is still a mystery, in part because neurons that encode objects respond in complicated ways. Associate Professor Tatyana Sharpee and Research Associate Ryan Rowekamp have developed a statistical method that takes these complex responses and describes them in interpretable ways, which could be used to help decode vision for computer-simulated vision. The duo analyzed how neurons in a critical part of the brain, called V2, respond to natural scenes, providing a better understanding of vision processing and how the brain works in general.
- Untangling the mysteries of the spinal cordConverging research and innovative technologies are tackling some of the deadliest motor diseases.
- An interview with Diana HargreavesInside Salk talked with Hargreaves about why she prefers smaller intellectual environments, what excites her about the science she does at the Institute, and how she thinks about being a woman in science.
- Delving into the best of both worlds with Shani SternAs the only electrophysiologist in the lab, Stern uses her engineering expertise to delve into the biological mysteries that most intrigue her, particularly bipolar disorder.