Presentation Topic: Branching Process Models of Cancer

Abstract

It is common to use a multitype branching process to model the accumulation of mutations that leads to cancer progression, metastasis, and resistance to treatment. In this talk I will describe results from multitype branching processes that are useful in evaluating possible screening strategies for ovarian cancer, and in quantifying the amount of heterogeneity in a tumor.

Presentation Topic: The Central Role of Modern Regression in Statistical Thinking about Neural Spike Trains

Abstract

One of the most important techniques in learning about the functioning of the brain has involved examining neural activity in laboratory animals under differing experimental conditions. Neural information is represented and communicated through series of action potentials, or spike trains, which are represented probabilistically as point processes. Because repeated presentations of stimuli often produce quite variable neural responses, statistical models have played an important role in advancing neuroscientific knowledge. In my talk I will outline some of the progress made, by many people, over roughly the past 10 years using point process regression models, and I will highlight recent work on neural synchrony (Kass, Kelly, and Loh, 2011, Annals of Applied Statistics). I will also use this body of work as a starting point for remarks about the central role of regression in statistical thinking more generally.