We are employing a number of tools to the study of visual and motor areas in neocortex.
Two-photon imaging provides us with exquisite spatial resolution and the ability to image neurons deep in the brain. The main drawback of the method is it’s temporal resolution which we have addressed with our Heuristically Optimal Path Scan Technique. The approach was first postulated by Maria Goeppert-Mayer (1930): the unit for the two-photon absorption cross section is named the Goeppert Mayer (GM) unit.
Developed by Erwin Neher and Bert Sakmann (1980) patch clamp recordings allow us to record the subthreshold voltage of individual neurons and resolve individual synaptic connections.
Pierre Belon (1555) is largely credited as the father of comparative biology. He conducted systematic comparisons of the skeletons of birds and humans. Comparison between visual and motor areas of neocortex will allow us to identify dynamical features that generalize between these two areas and those that do not. We postulate that generalized features will yield insight into how neocortex computes.
We apply many quantitative approaches to the analysis of our data and also generate neuronal network models. Louis Lapicque, (1907) developed the first integrate and fire model neurons.
The brain is a complex system comprised of many interconnected neurons. Network science provides us with a set of tools to study the neocortex as a system of interacting neurons. One set of tools is provided by graph theory, first developed by Leonhard Euler in 1736.