Task-dependent individual differences in prefrontal connectivity

Abstract

Recent advances in neuroimaging have permitted testing of hypotheses regarding the neural bases of individual differences, but this burgeoning literature has been characterized by inconsistent results. To test the hypothesis that differences in task demands could contribute to between-study variability in brain-behavior relationships, we had participants perform 2 tasks that varied in the extent of cognitive involvement. We examined connectivity between brain regions during a low-demand vigilance task and a higher-demand digit-symbol visual search task using Granger causality analysis (GCA). Our results showed 1) Significant differences in numbers of frontoparietal connections between low- and high-demand tasks 2) that GCA can detect activity changes that correspond with task-demand changes, and 3) faster participants showed more vigilance-related activity than slower participants, but less visual-search activity. These results suggest that relatively low-demand cognitive performance depends on spontaneous bidirectionally fluctuating network activity, whereas high-demand performance depends on a limited, unidirectional network. The nature of brain-behavior relationships may vary depending on the extent of cognitive demand. High-demand network activity may reflect the extent to which individuals require top-down executive guidance of behavior for successful task performance. Low-demand network activity may reflect task- and performance monitoring that minimizes executive requirements for guidance of behavior.

Figure 1.

Trial sequence of the modified DSST. On each trial, a code table appeared in the middle of the screen while a probe digit–symbol pair appeared below it. These stimuli stayed on the screen for 3.5 s followed by variable intertrial intervals (0.5, 4.5, 8.5, or 12.5 s).

Figure 2.

Average t-values (thresholded from cyan to blue and red to yellow, respectively, at −2.00 ≥ t ≥ 2.00, P < 0.05 uncorrected), spatially normalized to Talairach space via affine transformation to the Colin-brain template. The mean t-values are shown on surface models created from the Colin template. These results show task-related signal change in the previously identified target regions, including dorsolateral PFC (BA 9 and BA 46), ventrolateral (BA 44, BA 45, and BA 47) PFC, and inferior parietal cortex (BA 39 and BA 40).

Figure 3.

Results of the GCAs for the vigilance task (A) and for the DSST task (B). For both tasks, the results are arranged in a circular fashion with rostral information represented on the left side of each circle, relatively ventral and posterior regions are illustrated in the middle portions so that the caudal-most ROIs are on the right side of the circle. Arrows indicate significant influences; thicker black and dashed arrows represent influences with P < 0.05; thinner gray arrows represent influences with 0.05 < P < 0.10.

Figure 4.

Mean numbers of unidirectional and bidirectional influences for both task types across ROIs. Unidirectional influences are illustrated in solid open bars and labeled with single arrows. Bidirectional influences are illustrated as filled bars and labeled with 2 arrows.

Figure 5.

Scatterplot showing relationships between DSST RT and unidirectional output PFC influences (determined by GCA) from BA 9 for the vigilance (filled squares) and DSST (open triangles) tasks.