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A simulator for evaluating methods for the detection of lesion-deficit associations.

Abstract：

:Although much has been learned about the functional organization of the human brain through lesion-deficit analysis, the variety of statistical and image-processing methods developed for this purpose precludes a closed-form analysis of the statistical power of these systems. Therefore, we developed a lesion-deficit simulator (LDS), which generates artificial subjects, each of which consists of a set of functional deficits, and a brain image with lesions; the deficits and lesions conform to predefined distributions. We used probability distributions to model the number, sizes, and spatial distribution of lesions, to model the structure-function associations, and to model registration error. We used the LDS to evaluate, as examples, the effects of the complexities and strengths of lesion-deficit associations, and of registration error, on the power of lesion-deficit analysis. We measured the numbers of recovered associations from these simulated data, as a function of the number of subjects analyzed, the strengths and number of associations in the statistical model, the number of structures associated with a particular function, and the prior probabilities of structures being abnormal. The number of subjects required to recover the simulated lesion-deficit associations was found to have an inverse relationship to the strength of associations, and to the smallest probability in the structure-function model. The number of structures associated with a particular function (i.e., the complexity of associations) had a much greater effect on the performance of the analysis method than did the total number of associations. We also found that registration error of 5 mm or less reduces the number of associations discovered by approximately 13% compared to perfect registration. The LDS provides a flexible framework for evaluating many aspects of lesion-deficit analysis.

journal_name

Hum Brain Mapp

journal_title

Human brain mapping

authors

Megalooikonomou V,Davatzikos C,Herskovits EH

doi

10.1002/(sici)1097-0193(200006)10:2<61::aid-hbm20>

keywords:

subject

Has Abstract

pub_date

2000-06-01 00:00:00

pages

61-73

issue

eissn

1065-9471

issn

1097-0193

pii

10.1002/(SICI)1097-0193(200006)10:2<61::AID-HBM20>

journal_volume

pub_type

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A simulator for evaluating methods for the detection of lesion-deficit associations.