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Abstract #2322

A Weighted Square Averaging Method of Combining Primary and Temporal Derivative Parameter Estimates In General Linear Model Analysis of Functional MRI

Kwan-Jin Jung1 and Hae-Min Jung2

1Human Magnetic Resonance Center, Institute of Applied Life Sciences, University of Massachusetts Amherst, Amherst, MA, United States, 2Austen Riggs Center, Stockbridge, MA, United States

The temporal derivative has been considered as a mathematical solution for the latency variation of the hemodynamic response function (HRF) in the general linear model (GLM) analysis of the task-based functional MRI (fMRI). A method of combining the primary and derivate estimates was developed by Calhoun and its implementation was introduced. However, serious defects were revealed in the existing methods from a GLM analysis of an event-related fMRI. Here, the method is revised to provide a correct combined estimate using a weighted square average method. The proposed method was confirmed with event-related fMRI studies at various phases of the double Gamma HRF.

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