Niles Babin

Thesis Advisor: Dr. Lisette de Pillis (Harvey Mudd College - Department of Mathematics)

Second Reader: Dr. Kelvin Quiñones-Laracuente (NYU Grossman School of Medicine - Department of Neuroscience)

Contact: nbabin@hmc.edu

Statistical and informational analyses of neural dynamics

The brain's neurons processes information through the action potential, an instantaneous change in voltage potential across the neural membrane, often referred to as a neural spike or fire. Information is largely believed to be encoded in neural firing rates and specific spike timings. Given the current high-flux of neural imaging and recording technologies, it is desirable to be able to summarize and analyze neural activity represented as spike trains. This thesis provides a review of spike train analysis techniques, focusing first on general statistical summaries of prototypical firing patterns, followed by a detailed informational analysis on effective neural connectivity. This theoretical primer is then supplemented with real-world experimental spike train data recorded from in-vivo mice brains during transmission of social behaviors. These analyses provide a summary of prototypical firing patterns of the mouse's hypothalamic paraventricular nucleus and effective neural structure mapping transmitted social information to specific neural representations.