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2019.06 Ting Xu

Ting Xu (CMI): Individual variation in nonhuman primate and cross-species comparison

Location: Demo room 7F
Date: June 18th, 2pm

Abstract:

Comparative neurosciences studies are critical to the development and evaluation of nonhuman models and human psychiatric illness. Long dependent upon postmortem examinations of targeted regions or circuits, the capabilities of comparative studies have expanded dramatically with the maturation of noninvasive multimodal MRI imaging. However, the development of optimized methods for cross-species alignment has lagged, limiting our ability to appreciate difference among species. In this talk, I will first focus on mapping the individual variation of functional connectivity in non-human primate (NHP) to address the gap in knowledge regarding individual differences in NHP, as well as methodological implications that must be considered in any pursuit to study individual variation in NHP models. Second, I will introduce a method for cross species cortical alignment that leverage recent advances in describing neural organization in a dimensional framework. This approach allows us to quantify homologous regions across species even when their location is decoupled from anatomy. The findings suggest that the inter-species similarity within and across functional systems mirrored the functional hierarchies established in the human. Moreover, the default mode network, as the apex of a cognitive hierarchy is a relatively recent evolutionary adaptation.

Short Bio:

Ting Xu, PhD, is a research scientist at the Center for the Developing Brain, Child Mind Institute in New York. Her research focuses on investigating the brain connectome in human and non-human primates via various mathematical and statistical methods to understand the brain changes associated with development and evolution. Dr. Xu was initially trained in mathematics and increased her focus on neuroscience and neuroimaging with a particular focus on large-scale datasets, investigating the low-frequency oscillations in BOLD (blood oxygen level dependent) signals by using time-frequency analyses (e.g., wavelet), as well as on developing the computational platforms and statistical models for establishing reliability and reproducibility of the functional connectome. Her postdoctoral work focused on parcellation methodologies for characterizing cortical areal organization based upon functional MRI and understanding issues related to inter-individual variation and reliability in human and non-human primates (NHP). Recently, she has placed a growing emphasis on the cross-species comparison and brain reorganization in evolution in NHP.