NSF Award
0928723
The vertebrate nervous system consists of neurons that interact with each other through connections, called synapses. Changes in the strengths of the synaptic connections, due to the activity patterns of the neurons, are thought to underlie the plasticity of the brain. Furthermore, it is widely recognized that a delicate balancing of synaptic connection strength is essential to nervous system function. Unhindered connections would cause the brain to cease to operate, in a cacophony of epileptic-like feedback oscillations; if suppression dominated, stimuli would be unable to elicit a response from an apathetic, flatline brain. At the delicate interface between these two useless modes of behavior lies a regime in which groups of neurons are on the verge of oscillation, and may rapidly start or stop responding according to external influences.<br/>This project will develop a theory of self-poising, in which local activity-dependent rules for balancing synaptic response result in many groups of neurons poised at the edge of this dynamical instability. The theory will develop the interaction between self-poising and microstructure, in which local neuronal microcircuits are threaded together into global states, and the interaction with macrostructure, in which different self-poised areas communicate and interact. <br/>New theory resulting from this project will aid understanding of global activity patterns in the brain, such as Electroencephalography (EEG) or Electrocorticography (ECoG). The proposed research will contribute directly to education and outreach programs for high school students, undergraduate and graduate students, and postdoctoral researchers. These activities will be coordinated through ongoing programs at Rockefeller University. Promoting the involvement of minority undergraduate and graduate students in research environments will be a priority of this program. Results from the project will be incorporated into novel graduate courses on network theory and advanced modeling for biology students.
