[Brainmap]: Jingyuan Chen, Ph.D. - Temporal characteristics of intrinsic brain activity based on fMRI

Wednesday, March 21, 2018 - 12:00 to 13:00
149 13th Street (Building 149), Room 2204

Title: Temporal characteristics of intrinsic brain activity based on fMRI  

 

Abstract: 

Emerging evidence has suggested that brain resting state functional connectivity may transiently reconfigure at temporal scales of several seconds to minutes, and such brain dynamics have great potential to unveil novel understanding in both cognitive and clinical applications. In spite of the growing popularity of studying brain dynamics in recent years, methods to quantitatively characterize such fluctuating network patterns remain limited. In the first part of my talk, I will present advancements based on co-activation pattern analyses to quantify and synthesize dynamic functional information. With such analyses, we are able to reveal elaborate changes in network dynamics exerted by a sustained working memory task; and demonstrate distinct anti-correlation patterns associated with different branches of the brain’s default-mode network.  

With faster acquisitions, several groups have reported structured network patterns persisting at frequencies well above 0.1 Hz (up to 5 Hz), which exhibit apparent spectrum-dependency that may pose new biomarker opportunities. However, such intriguing findings of high-frequency neural activity ought to be treated with caution, as BOLD contrasts stem from inherently sluggish hemodynamic processes. In the second part of my talk, I will share my explorations into the mechanisms of such high-frequency phenomena at rest. Briefly, using multi-echo acquisitions, I will show fractional contributions of non-BOLD components increase as frequency increases; then demonstrate that existing observations on high-frequency functional connectivity may be partially explained by improper preprocessing and possibly altered hemodynamics at rest.  

 

About the Speaker:

Jingyuan Chen obtained her PhD from Stanford University in 2017, with a major in Electrical Engineering and a minor in Statistics. Her PhD thesis work, mentored by Dr. Gary Glover, focused on modeling and analysis of brain spontaneous fluctuations. In last October, she joined Martinos Center to probe the biophysics of resting state functional connectivity using single vessel imaging techniques, under the supervision of Drs. Jonathan Polimeni and Laura Lewis.