Differential functional patterns of the human posterior cingulate cortex during activation and deactivation: a meta-analytic connectivity model

Abstract

The posterior cingulate cortex (PCC) has been implicated in a host of cognitive and behavioral processes in addition to serving as a central hub in the default mode network (DMN). Moreover, the PCC has been shown to be involved in a range of psychiatric and neurological disorders. However, very little is known about the specific activated/deactivated functional profiles of the PCC. Here, we employed a dual analytic approach using robust quantitative meta-analytical connectivity modeling (MACM) and ultra-high field, high resolution resting state functional magnetic resonance imaging (rs-fMRI) to identify state-specific functional activity patterns of the human PCC. The MACM results provided evidence for regions of convergence for PCC co-activation and co-deactivation (i.e., left medial frontal gyrus, left amygdala, and left anterior cingulate) as well as regions of divergence specific to either PCC activation (i.e., bilateral inferior frontal gyri) or PCC deactivation (i.e., left parahippocampal gyrus). In addition, exploratory MACMs on dorsal and ventral subregions of the PCC revealed differential functional activity patterns such as greater co-activation of the right PCC and left inferior parietal lobule with the dorsal PCC and greater co-activation of right precuneus with the ventral PCC. Resting state connectivity analyses showed widespread connectivity similar to that of the PCC co-activation-based MACM, but also demonstrated additional regions of activity, including bilateral superior parietal regions and right superior temporal regions. These analyses highlight the diverse neurofunctional repertoire of the human PCC, provide additional insight into its dynamic functional activity patterns as it switches between activated and deactivated states, and elucidates the cognitive processes that may be implicated in clinical populations.

Keywords: Activation analysis; Attention; Brain; Magnetic resonance imaging; Neuroimaging.

Fig. 1

PCC ROI mosaic with dorsal and ventral 3D ROIs in sagittal and superior renderings. The color bar represents the probability threshold across all voxels of the PCC ROI

Fig. 2

Meta-analytic connectivity modeling of the PCC with overlays of the ALE maps for PCC co-activation and PCC co-deactivation MACMs and the qualitative overlap between the two MACMs. ALE maps were individually thresholded using p_{cluster-corrected} < 0.05 (1000 permutations) and p_pvoxel-level < 0.001

Fig. 3

Meta-analytic connectivity modeling of the dPCC and vPCC with overlays of the ALE maps for dPCC co-activation and vPCC co-activation and co-deactivation contrast MACMs. ALE maps were individually thresholded using p_{cluster-corrected} < 0.05 (1000 permutations) and p_pvoxel-level < 0.001

Fig. 4

Qualitative comparison of rs-fMRI and MACM activations for the PCC ROI. ALE maps were thresholded using p_{cluster-corrected} < 0.05 (1000 permutations) and p_pvoxel-level < 0.001. Rs-fMRI seed-to-voxel connectivity maps were thresholded at p_{FDR-corrected} < 0.001 at the voxel-level and p_{FWE-corrected}< 0.001 at the cluster-level (two-tailed)

Fig. 5

Qualitative comparison of rs-fMRI and MACM deactivations for the PCC ROI. ALE maps were thresholded using p_{cluster-corrected} < 0.05 (1000 permutations) and p_pvoxel-level < 0.001. Rs-fMRI seed-to-voxel connectivity maps were thresholded at p_{FDR-corrected} < 0.001 at the voxel-level and p_{FWE-corrected}< 0.001 at the cluster-level (two-tailed)