Exploring Activation Functions in Machine Learning and Neural Data Fitting

Today’s guest has argued that the present dominant way of doing systems neuroscience in mammals (large-scale electric or optical recordings of neural activity combined with data analysis) will be inadequate for understanding how their brain works.

Instead, he proposes to focus on the simple roundworm C.elegans with only 302 neurons and try to reverse engineer it by means of optical stimulation and recordings, and modern machine-learning techniques.