Parameter Sensitivity and Optimization for Hemodynamic Response Model of fMRI
YANG Zengyu
JIANG Wentao
CHEN Yu
Abstract：Functional magnetic resonance imaging ( fMRI) is the main means to study the brain function in recent years , the basis of the imaging principle is to record hemodynamics response caused by neural activity , therefore, to explore the relationship between fMRI data and neural activity , the hemodynamic response function model is the key .The hemodynamic response function model put forward by Cohen can describe corresponding response .However , due to the coupling between parameters is not considered in the ex-perimental data fitting , the model obtained is not optimal in accuracy and fitting effect .To solve this problem , the method of combining parameter sensitivity analysis and genetic algorithm was used to obtain the optimization hemodynamic response function of 3 parameter gamma function form .Firstly, the sensitivity of parameters in the model was calculated by Latin hyper -cube sampling method and spearman rank correlation analysis theory .Then the reasonable range in which the parameters have equivalent sensitivities were ob -tained.Taking the range as the initial search range , the global optimal search was applied by the genetic algorithm .The optimal pa-rameters were the results considering the coupling effect between parameters .The optimized model predicts the hemodynamic response quite well.In addition, comparing with Cohen's model, the result makes somewhat improvement in accuracy and data fitting effect .
Keywords：Functional magnetic resonance imagingHemodynamicResponse modelGenetic algorithmParameter sensitivity
Publication Date：2017-01-01
Online Publishing Date：2026-09-11(First online date of this platform, not the publication date of the document)
Pages：5( 307-311 )