Meta-analysis of neuroimaging studies of the Wisconsin card-sorting task and component processes

Abstract

A quantitative meta-analysis using the activation likelihood estimation (ALE) method was used to investigate the brain basis of the Wisconsin Card-Sorting Task (WCST) and two hypothesized component processes, task switching and response suppression. All three meta-analyses revealed distributed frontoparietal activation patterns consistent with the status of the WCST as an attention-demanding executive task. The WCST was associated with extensive bilateral clusters of reliable cross-study activity in the lateral prefrontal cortex, anterior cingulate cortex, and inferior parietal lobule. Task switching revealed a similar, although less robust, frontoparietal pattern with additional clusters of activity in the opercular region of the ventral prefrontal cortex, bilaterally. Response-suppression tasks, represented by studies of the go/no-go paradigm, showed a large and highly right-lateralized region of activity in the right prefrontal cortex. The activation patterns are interpreted as reflecting a neural fractionation of the cognitive components that must be integrated during the performance of the WCST.

Figure 1

Axial slices showing significant ALE activation in WCST (green), task switching (red), and the conjunction of WCST and task switching (yellow) overlaid on the International Consortium for Brain Mapping (ICBM) single subject template.

Figure 2

Axial slices showing significant ALE activation in WCST (green), go/no‐go (blue), and the conjunction of WCST and go/no‐go (blue) overlaid on the ICBM single subject template.

Figure 3

Three‐dimensional surface rendered views of all three task meta‐analyses including all possible conjunctions. 1, WCST (green); 2, task switching (red); 3, go/no‐go (blue); 4, WCST and task switching (yellow); 5, WCST and go/no‐go (cyan); 6, task switching and go/no‐go (violet); 7, WCST and task switching and go/no‐go (white). Image rendering was created with SUMA (and associated AFNI program 3dVol2Surf; [Saad et al.,2004]) using a surface representation of the ICBM single‐subject brain that was created with the FreeSurfer software package [Dale et al.,1999; Fischl et al.,1999].