Understanding the processing of information in our cortex is a significant part of understanding how the brain works and of understanding intelligence itself, arguably one of the greatest problems in science today. In particular, our visual abilities are computationally amazing and we are still far from imitating them with computers. Thus, visual cortex may well be a good proxy for the rest of the cortex and indeed for intelligence itself. But despite enormous progress in the physiology and anatomy of the visual cortex, our understanding of the underlying computations remains fragmentary. 

I will describe a class of quantitative models of the ventral stream in visual cortex, which, constrained by physiology and biophysics, have been developed during the last two decades to explain several physiological data across different visual areas. I will discuss their performance and architecture from the point of view of state-of-the-art computer vision systems for object recognition. 

The broad thesis of this talk is that computational neuroscience is beginning to provide novel insights into the problem of how our visual cortex is computing and in how some aspects of learning and intelligence may be implemented in machines. In this spirit, I will describe a new Intelligence Initiative at MIT, based on our belief that it is time again for a new, fresh attack on the problem of intelligence.  The launching off point will be a new integration of the fields of cognitive science, which studies the mind, neuroscience, which studies the brain, and computer science and artificial intelligence, which develop intelligent hardware and software. 

Relevant papers can be downloaded from https://cbcl.mit.edu/publications/index-pubs.html