Deep Learning and Computational Neuroscience

Excerpt

Especially young colleagues are fascinated by the potential of deep learning for neuroscience. This was obvious at the recent Society for Neuroscience meeting in Washington DC, where the few posters that had the magical words in their title attracted large crowds of attendees who seemed almost exclusively in their twenties. The success of deep learning of data representation has led to impressive applications in image, video and speech processing.¹ Compared to these, recent advances in applying reinforcement learning to playing games are outright mind blowing, with AlphaGo Zero achieving superhuman performance in just three days of training on a single machine with specialized hardware.² It is, therefore, easy to predict that the interest in deep learning among young computational neuroscientists will only increase, but the reality may be more complex than they surmise. In this Editorial, I will focus on the question of correspondence between deep learning and how the brain works.³ I will not consider the many opportunities of applying deep learning as a supporting technology. …