Dissociable intrinsic connectivity networks for salience processing and executive control

Abstract

Variations in neural circuitry, inherited or acquired, may underlie important individual differences in thought, feeling, and action patterns. Here, we used task-free connectivity analyses to isolate and characterize two distinct networks typically coactivated during functional MRI tasks. We identified a "salience network," anchored by dorsal anterior cingulate (dACC) and orbital frontoinsular cortices with robust connectivity to subcortical and limbic structures, and an "executive-control network" that links dorsolateral frontal and parietal neocortices. These intrinsic connectivity networks showed dissociable correlations with functions measured outside the scanner. Prescan anxiety ratings correlated with intrinsic functional connectivity of the dACC node of the salience network, but with no region in the executive-control network, whereas executive task performance correlated with lateral parietal nodes of the executive-control network, but with no region in the salience network. Our findings suggest that task-free analysis of intrinsic connectivity networks may help elucidate the neural architectures that support fundamental aspects of human behavior.

Figures

Figure 1.

Disentangling the task-activation ensemble with task-free fcMRI. A, A spatial working memory activation map (two-back minus control) was used to select seed ROIs (circled) within the right frontal lobe. B, Temporal correlations in BOLD signal determined the intrinsic connectivity patterns with the frontoinsular (red-orange colorbar) and dorsolateral prefrontal (blue-green colorbar) ROIs (height and extent thresholds, p < 0.001, corrected) during undirected wakefulness. For display purposes, the t-score color bars in B were adjusted so that the top of the bar reflects the maximum t score seen outside the seed ROI for each network. Effortful tasks like the one used in A often coactivate the networks disentangled using a task-free, intrinsic connectivity analysis in B. These ROI-based maps (B) were used as templates for subsequent independent components analyses (Fig. 2). Functional images are displayed on a standard brain template (MNI). On axial and coronal images, the left side of the image corresponds to the left side of the brain.

Figure 2.

Separable intrinsic connectivity networks revealed by independent component analysis. The salience network (red-orange colorbar) is anchored by paralimbic anterior cingulate and frontoinsular cortices and features extensive connectivity with subcortical and limbic structures. In the executive-control network (blue-green colorbar), the dorsolateral frontal and parietal neocortices are linked, with more selective subcortical coupling. Functional images are displayed as in Figure 1. AI, Anterior insula; antTHAL, anterior thalamus; dCN, dorsal caudate nucleus; dmTHAL, dorsomedial thalamus; DMPFC, dorsomedial prefrontal cortex; HT, hypothalamus; PAG, periaqueductal gray; Put, putamen; SLEA, sublenticular extended amygdala; SN/VTA, substantia nigra/ventral tegmental area; TP, temporal pole; VLPFC, ventrolateral prefrontal cortex.

Figure 3.

Dissociable correlations between intrinsic functional connectivity and individual differences in emotion and cognition. Within the salience network, functional connectivity in two clusters, the dACC, and dorsolateral prefrontal cortex (−32, 44, 16, BA 46 data not shown) correlate with subject ratings of prescan anxiety (left). Within the executive-control network, functional connectivity in two clusters, located in the bilateral intraparietal sulcus/superior parietal lobule, predicts superior Trails B performance (right). Scatterplots depict these correlations graphically in the larger of the two significant clusters from each map. The y-axes show averaged voxel z-scores within the dACC or right intraparietal sulcus (IPS) cluster from each subject's salience or executive-control component, respectively. The z-scores here reflect the degree to which the time series of a given region is correlated with the overall network time series. Note that the correlation between prescan anxiety and dACC z-scores was recalculated with the outlying data point (anxiety rating of 7) removed and the correlation remained significant with an r2 value of 0.74 (p < 0.0001 for Fisher's r to z). Functional images are displayed as in Figure 1..