Statistical Inference and Experimental Design for Recurrent Event Data with Applications in Neuroscience

University Of California-Davis, Davis CA

Investigators

Abstract

Modern technologies allow neuroscientists to record and control neural activities at cellular resolution in living, intact brains. While these technologies open up a path toward understanding the brain, they also pose new challenges for neuroscientists and statisticians. Modern neuroscience experiments produce massive recordings of neural activities in the form of recurring spikes. Despite the large volume, missing data and measurement errors pose significant statistical challenges. Moreover, with techniques such as optogenetics and multi-photon imaging, it is increasingly clear that statistical experimental designs should be utilized to facilitate modern neuroscience experiments. The research focuses on answering two questions of interest to the scientific community: (1) how to rigorously analyze the newly-acquired neural data, and (2) how to optimally design neuroscience experiments to aid scientific discovery. There are two main aims in this research project. The first aim focuses on the development of statistical theory and methods for analyzing neural data using a class of point process models known as the Hawkes process. While the Hawkes process is widely used in neuroscience applications, the underlying theoretical properties are not well-studied. The proposed research will seek to (a) develop novel theory for the Hawkes process under realistic assumptions, (b) establish a causal inference framework for partially observed networks using instrumental variables, and (c) account for calibration errors in spike detection. In the second aim, an automatic procedure for model-based design of optogenetics experiments for mapping neural microcircuits will be developed leveraging results obtained as part of the first aim. Computationally efficient algorithms for online learning and designing on neural data will also be developed. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.