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Updated: Jan 25, 2026

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
Published on: November 1, 2019
Model selection for spatiotemporal modeling of early childhood sub-cortical development
James Fishbaugh1, Beatriz Paniagua2, Mahmoud Mostapha3
1Computer Science and Engineering, Tandon School of Engineering, NYU.
Abstract:
Spatiotemporal shape models capture the dynamics of shape change over time and are an essential tool for monitoring and measuring anatomical growth or degeneration. In this paper we evaluate non-parametric shape regression on the challenging problem of modeling early childhood sub-cortical development starting from birth. Due to the flexibility of the model, it can be challenging to choose parameters which lead to a good model fit yet does not over fit. We systematically test a variety of parameter settings to evaluate model fit as well as the sensitivity of the method to specific parameters, and we explore the impact of missing data on model estimation.
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