Deep neural networks uncover what the brain likes to see

Experimental approaches to characterize their responses to images have proven challenging in part because the number of possible images is endless. In the past, seminal insights often resulted from stimuli that neurons in the brain'liked.' Finding them relied on the intuition of the scientists and a good portion of luck. Researchers at Baylor College of Medicine and the University of Tübingen in Germany have now developed a novel computational approach to accelerate finding these optimal stimuli. They built deep artificial neural networks that can accurately predict the neural responses produced by a biological brain to arbitrary visual stimuli.