Computer Science

Biophysical neural adaptation mechanisms enable artificial neural networks to capture dynamic retinal computation

S. Idrees, M. B. Manookin, et al.

Discover groundbreaking advancements in artificial neural networks with a new deep learning model that enhances the predictive capabilities of retinal responses. This promising research, conducted by Saad Idrees, Michael B. Manookin, Fred Rieke, Greg D. Field, and Joel Zylberberg, emphasizes the importance of neural adaptation in accurately interpreting dynamic visual environments.