Enhanced default mode connectivity predicts metacognitive accuracy in traumatic brain injury

To examine the role that intrinsic functional networks, specifically the default mode network, have on metacognitive accuracy for individuals with moderate to severe traumatic brain injury (TBI).

A sample of 44 individuals (TBI, n = 21; healthy controls [HCs], n = 23) were included in the study. All participants underwent an MRI scan and completed neuropsychological testing. Metacognitive accuracy was defined as participants' ability to correctly judge their item-by-item performance on an abstract reasoning task. Metacognitive values were calculated using the signal detection theory approach of area under the receiver operating characteristic curve. Large-scale subnetworks were created using Power's 264 Functional Atlas. The graph theory metric of network strength was calculated for six subsystem networks to measure functional connectivity.

There were significant interactions between head injury status (TBI or HC) and internetwork connectivity between the anterior default mode network (DMN) and salience network on metacognitive accuracy (R2 = 0.13, p = .047) and between the posterior DMN and salience network on metacognitive accuracy (R2 = 0.15, p = .038). There was an interpretable interaction between head injury status and internetwork connectivity between the attention network and salience network on metacognitive accuracy (R2 = 0.13, p = .067). In all interactions, higher connectivity predicted better metacognitive accuracy in the TBI group, but this relationship was reversed for the HC group.

Enhanced connectivity to both anterior and posterior regions within the DMN facilitates metacognitive accuracy postinjury. These findings are integrated into a larger literature examining network plasticity in TBI. (PsycINFO Database Record (c) 2019 APA, all rights reserved).