John Hertz

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Primary fields of research

statistical physics, biological physics, computational neuroscience

Current research

I am using methods from statistical physics to develop techniques for extracting information about the structure of biological (primarily neurobiological) networks from records of the activity of the units in these networks.  More specifically, my current work deals with extracting the synaptic connectivity of neural networks from multi-neuron spike train recordings.  Mathematically, this involves solving the inverse problem for a Glauber model of coupled Ising variables.  I am also interested in the dynamic properties of neural networks, in particular how cortical and spinal-cord networks generate spontaneously highly chaotic activity with low correlation between the firing of different neurons. 

Teaching

statistical physics, biological physics, complex systems