Test-retest variability underlying fMRI measurements
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文摘

Introduction

A high test-retest reliability is of pivotal importance for many disciplines in fMRI research. To assess the current limits of fMRI reliability, we estimated the variability in true underlying Blood Oxygen Level Dependent (BOLD) activation, with which we mean the variability that would be found in the theoretical case when we could obtain an unlimited number of scans in each measurement.

Methods

In this test-retest study, subjects were scanned twice with one week apart, while performing a visual and a motor inhibition task. We addressed the nature of the variability in the underlying BOLD signal, by separating for each brain area and each subject the between-session differences in the spatial pattern of BOLD activation, and the global (whole brain) changes in the amplitude of the spatial pattern of BOLD activation.

Results

We found evidence for changes in the true underlying spatial pattern of BOLD activation for both tasks across the two sessions. The sizes of these changes in pattern activation were approximately 16 % of the total activation within the pattern, irrespective of brain area and task. After spatial smoothing, this variability was greatly reduced, which suggests it takes place at a small spatial scale. The mean between-session differences in the amplitude of activation across the whole brain were 13.8 % for the visual task and 23.4 % for the motor inhibition task.

Conclusions

Between-session changes in the true underlying spatial pattern of BOLD activation are always present, but occur at a scale that is consistent with partial voluming effects or spatial distortions. We found no evidence that the reliability of the spatial pattern of activation differs systematically between brain areas. Consequently, between-session changes in the amplitude of activation are probably due to global effects. The observed variability in amplitude across sessions warrants caution when interpreting fMRI estimates of height of brain activation. A Matlab implementation of the used algorithm is available for download at .

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