Double dissociation of two cognitive control networks in patients with focal brain lesions

Abstract

Neuroimaging studies of cognitive control have identified two distinct networks with dissociable resting state connectivity patterns. This study, in patients with heterogeneous damage to these networks, demonstrates network independence through a double dissociation of lesion location on two different measures of network integrity: functional correlations among network nodes and within-node graph theory network properties. The degree of network damage correlates with a decrease in functional connectivity within that network while sparing the nonlesioned network. Graph theory properties of intact nodes within the damaged network show evidence of dysfunction compared with the undamaged network. The effect of anatomical damage thus extends beyond the lesioned area, but remains within the bounds of the existing network connections. Together this evidence suggests that networks defined by their role in cognitive control processes exhibit independence in resting data.

Fig. 1.

(A) FP and CO ROI locations from Dosenbach et al. (3) (B) Degree of lesion overlap across all patients. (C) Amount of damage sustained at each node by each subject. Subjects 5–8, despite having lesions elsewhere, sustained no damage to either network.

Fig. 2.

Lesion masks in normalized space for all 21 subjects.

Fig. 3.

(A) Average FP and CO connectivity across subjects in lesion and control groups. (B) Average FP and CO network connectivity within each lesion patient sorted from high FP to high CO damage.

Fig. 4.

(A) Relative functional connectivity of CO and FP networks versus relative CO and FP anatomical damage. (B) Relative small-worldness (sigma) of CO and FP network nodes versus relative CO and FP anatomical damage.

Fig. 5.

Mean correlation values within the CO or FP networks in either patients with relatively more CO network damage or patients with relatively more FP network damage. *Significant differences between within-FP and within-CO network correlations (P < 0.05).