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Kevan Martin

 

Wednesday 12th June 2013

Time: 4pm

 

Basement Seminar Room

Alexandra House, 17 Queen Square, London, WC1N 3AR

 

Biography

Kevan A.C. Martin is Director of the Institute of Neuroinformatics and a Double Professor of Systems Neurophysiology at the University of Zurich and the Swiss Federal Institute of Technology (ETH). His research is on the structure and function of the neocortex. He also explores many aspects of performance in search of answers to the simple question: what is the relationship between thought and movement? His own performance is as a member of 4-Brain, a formation skydiving team that trains in Switzerland.

 

How to survive without a connectome.

Inside one voxel of a cubic millimeter of neocortex, one hundred thousand neurons use four kilometers of axonal cable to form three to fifteen hundred million synapses with each other.  While in the human such voxel is a small fragment of a cortical area, in the mouse an entire cortical area, like the primary auditory cortex, can be contained in a voxel of this size. This raises the fundamental question of what happens inside such a voxel? Are the circuits contained in this voxel, and their operations, different in every area, or are there general principles that are conserved across cortical areas and species? Such questions go to the heart of understanding how the neocortex wires itself and works. Currently one approach to answering these questions is by mapping the entire circuit at synaptic resolution to produce a ‘connectome’ of the cortical column, and ultimately, the entire brain. However, such a high-resolution connectome is self-evidently unachievable with the tools available and as a strategy it still leaves us short of understanding the ‘principles of neural engineering’. We have taken another route and use physiology and computational modeling as a means of generating ‘predictive anatomy’, where the questions about underlying structure are directed to fundamental principles of organization and operation of the cortical circuits. This approach includes ‘sparse’ rather than ‘dense’ reconstructions at light and electron microscope resolution, which keeps the questions well-matched to current experimental tools. Rather than providing a snap-shot of an entire wiring diagram, our strategy provides for a statistical description of the circuits and integrates theory, function, and structure in a common framework.