Towards a theory of multi-neuronal dimensionality, dynamics and measurement

  • Awardees
  • Surya Ganguli, Ph.D. Stanford University
  • Krishna Shenoy, Ph.D. Stanford University

The brain is composed of billions of neurons, yet, until recently, technology only allowed for recording the electrical activity of a single neuron at a time. Now, with President Obama’s BRAIN initiative, significant resources will be channeled into developing technology to record from thousands or millions of neurons at once. However, in order for this data to be useful, we must also develop the mathematical tools to analyze and interpret such large and complex data sets. Our group is positioned at the vanguard of such efforts to develop theories that guide biological interpretation of complex data sets. In addition to developing general theories uniting dynamical systems and high dimensional statistics, our group will collaborate with experimental laboratories to test these theories in monkeys as they plan and execute complex reaches in the face of external forces that interfere with their actions. Our aim is to develop a “Rosetta Stone” between biology and mathematics that will enable us to interpret large data sets from multi-neuronal recordings not only when monkeys reach, but for any intricate behavior emerging from the collective activity of millions of neurons.


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