제1차 심리학과 콜로키움 안내

제목: Multilevel Dynamic Generalized Structured Component Analysis(GSCA) for Brain Connectivity Analysis

발표자: 정광희 교수, University of Texas Health Science Center at Houston

날짜:  5월 15일(금)

시간 : 오후 1:00 ~ 3:00
장소 : 수선관 61907호

콜로키움 주제 설명:

  As a novel approach to structural equation modeling (SEM), Dynamic GSCA (Generalized Structured Component Analysis) extended the original GSCA by incorporating a multivariate autoregressive model to deal with longitudinal/time series data. Functional neuroimaging data are typically hierarchically structured, where time points are nested within participants who are in turn nested within an experimental group. The proposed approach, named Multilevel Dynamic GSCA, explicitly accommodates the nested structure in functional neuroimaging data. Explicitlytaking the nested structure into account, the proposed method allows investigating subject-wise variability of the loadings and path coefficients by looking at the variance estimates of the corresponding random effects, as well as fixed loadings between observed and latent variables and fixed path coefficients between latent variables. We demonstrate the effectiveness of the proposed approach by applying the method to the multi-subject functional neuroimaging data for brain connectivity analysis, where time series data-level measurements are nested within subjects.

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