When using functional magnetic resonance imaging (fMRI) for mapping important language functions, a high test-retest reliability is mandatory, both in basic scientific research and for clinical applications. We, therefore, systematically tested the short- and long-term reliability of fMRI in a group of healthy subjects using a picture naming task and a sparse-sampling fMRI protocol. We hypothesized that test-retest reliability might be higher for (i) speech-related motor areas than for other language areas and for (ii) the short as compared to the long intersession interval.
16 right-handed subjects (mean age: 29 years) participated in three sessions separated by 2–6 (session 1 and 2, short-term) and 21–34 days (session 1 and 3, long-term). Subjects were asked to perform the same overt picture naming task in each fMRI session (50 black-white images per session). Reliability was tested using the following measures: (i) Euclidean distances (ED) between local activation maxima and Centers of Gravity (CoGs), (ii) overlap volumes and (iii) voxel-wise intraclass correlation coefficients (ICCs). Analyses were performed for three regions of interest which were chosen based on whole-brain group data: primary motor cortex (M1), superior temporal gyrus (STG) and inferior frontal gyrus (IFG).
Our results revealed that the activation centers were highly reliable, independent of the time interval, ROI or hemisphere with significantly smaller ED for the local activation maxima (6.45 Symbol 1.36mm) as compared to the CoGs (8.03 Symbol 2.01mm). In contrast, the extent of activation revealed rather low reliability values with overlaps ranging from 24% (IFG) to 56% (STG). Here, the left hemisphere showed significantly higher overlap volumes than the right hemisphere. Although mean ICCs ranged between poor (ICC<0.5) and moderate (ICC 0.5–0.74) reliability, highly reliable voxels (ICC>0.75) were found for all ROIs. Voxel-wise reliability of the different ROIs was influenced by the intersession interval.
Taken together, we could show that, despite of considerable ROI-dependent variations of the extent of activation over time, highly reliable centers of activation can be identified using an overt picture naming paradigm.