Long-term test–retest reliability of functional MRI in a classification learning task

Abstract

Functional MRI is widely used for imaging the neural correlates of psychological processes and how these brain processes change with learning, development and neuropsychiatric disorder. In order to interpret changes in imaging signals over time, for example, in patient studies, the long-term reliability of fMRI must first be established. Here, eight healthy adult subjects were scanned on two sessions, 1 year apart, while performing a classification learning task known to activate frontostriatal circuitry. We show that behavioral performance and frontostriatal activation were highly concordant at a group level at both time-points. Furthermore, intra-class correlation coefficients (ICCs), which index the degree of correlation between subjects at different time-points, were high for behavior and for functional activation. ICC was significantly higher within the network recruited by learning than outside that network. We conclude that fMRI can have high long-term test-retest reliability, making it suitable as a biomarker for brain development and neurodegeneration.

Neural activations at the junction of the inferior frontal sulcus and the inferior precentral sulcus: Interindividual variability, reliability, and association with sulcal morphology

“…This result is remarkable considering that measurements were separated by at least 4 months (up to 19 months for the subjects who participated in Study 1 and Study 3) and that different tasks were employed (variants of the task-switching paradigm and the Stroop task). Thus, our results are in line with another study that provided evidence for a high long-term reliability of fMRI data [Aron et al, 2006]. A limitation of our analysis is that conditions were contrasted against null events.…”

Evaluation of group homogeneity during acupuncture stimulation in fMRI studies

“…[Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.] working memory and learning indicating that individual difference was not significant across subjects (10)(11)(12)(13)(14). However, several acupuncture studies inferred that the influence of individual difference should be taken into consideration (17).…”

Automatic independent component labeling for artifact removal in fMRI

“…Four images at the beginning of each run were discarded to allow T1 equilibration. The behavioral task and the image acquisition parameters are fully described in (Aron et al, 2006).…”

“…was added to a set of regions that are generally activated during categorization tasks (caudate, putamen, globus pallidus, thalamus, orbital,lateral and medial frontal cortex) (Aron et al, 2006)). The ROIs were extracted by registering the BOLD scan to a T2-weighted anatomical scan of the subject, and thereafter registering the T2-weighted scan to the T2-weighted single subject BrainWeb image (Collins et al, 1998).…”