Kanwisher Lab

The Kanwisher Lab investigates the functional organization of the human brain as a window in to the architecture of the mind. Over the last 20 years our lab has played a central role in the identification of a number of regions of the cortex in humans that are engaged in particular components of perception and cognition. Many of these regions are very specifically engaged in a single mental function such as the visual perception of faces, places, and bodies, and auditory perception of speech and music. Others selectively process abstract, uniquely human functions like understanding the mental states of others or the meaning of a sentence. Each of these regions is present in approximately the same location in virtually every normal person. This new neural portrait of the human mind reveals a vast landscape of new questions that we are tackling now about the representations, computations, and origins of each region. Much of our current work exploits the spatiotemporal resolution of intracranial recordings from neurosurgery patients, and the power of deep neural networks to test computationally precise hypotheses about what exactly the brain computes, and how and why it computes the way it does.

One major thread in our current work investigates the developmental origins of cortical specialization, including recent discoveries by grad student Heather Kosakowski (in collaboration with Saxelab) that the FFA, PPA, and EBA are present in 6-month old infants, by postdoc Ratan Murty that a “tactile FFA” is present in congenitally blind participants, and by grad student Dana Boebinger (in collaboration with McDermott lab) that music-selective neural populations are present in people with no explicit musical training.

Another line of work in collaboration with Tenenbaum lab starts from the observation that visual percepts contain much more than a list of features and objects, but include information about the shapes of faces, objects, and scenes, and the physical properties and relationships of objects in the scene. We have identified brain regions engaged during intuitive physical inference, and shown that these regions contain information about the mass of objects. Postdoc Pramod RT has further shown that these regions contain information about the stability of objects in a scene, information key to predicting what will happen next.

But why does the brain exhibit functional specialization in the first place, and why we do have the particular brain specializations we do? Ongoing deep net modeling work by postdoc Katharina Dobs finds that CNNs simultaneously optimized for face and object recognition spontaneously segregate these tasks into distinct processing streams, to a much greater degree than CNNs optimized for object and food or car recognition. These results suggest that for face recognition, and perhaps more broadly, the domain-specific organization of the cortex reflects a computational optimization over the loss function of life.

For more information on these topics, you can browse the short videos for newcomers to the field at NancysBrainTalks, or our recent scientific publications.

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