Networks from Time Series: Deciphering the Brain Connectome High-dimensional time series have become ubiquitous in many scientific fields. They are particularly instrumental in monitoring the activities of neurons and/or brain regions, and have led to valuable insight into cognitive processes and neurodegenerative diseases. I will discuss new methodological, computational, and theoretical developments for learning networks from high-dimensional time series. Motivated by emerging calcium florescent imaging data that record the activities of individual neurons, the talk will primarily focus on learning neuronal connectivity networks from high-dimensional spike train data. Time permitting, I will also discuss a new approach for learning networks from multiple experiments, and handling non-stationarity in brain imaging data.
Irene Felicetti 764-5452Networks from Time Series: Deciphering the Brain Connectome
Biostatistics Seminar with Ali Shojaie, PhD
September 19, 2019
3:00 pm - 5:00 pm
3755 SPH I
1415 Washington Heights
Ann Arbor, MI 48109-2029
Contact Information: Irene Felicetti 764-5452
Networks from Time Series: Deciphering the Brain Connectome High-dimensional time series have become ubiquitous in many scientific fields. They are particularly instrumental in monitoring the activities of neurons and/or brain regions, and have led to valuable insight into cognitive processes and neurodegenerative diseases. I will discuss new methodological, computational, and theoretical developments for learning networks from high-dimensional time series. Motivated by emerging calcium florescent imaging data that record the activities of individual neurons, the talk will primarily focus on learning neuronal connectivity networks from high-dimensional spike train data. Time permitting, I will also discuss a new approach for learning networks from multiple experiments, and handling non-stationarity in brain imaging data.
