Cognitive Effort Modulates Connectivity between Dorsal Anterior Cingulate Cortex and Task-Relevant Cortical Areas.

Investment of cognitive effort is required in everyday life and has received ample attention in recent neurocognitive frameworks. The neural mechanism of effort investment is thought to be structured hierarchically, with dorsal anterior cingulate cortex (dACC) at the highest level, recruiting task-specific upstream areas. In the current fMRI study, we tested whether dACC is generally active when effort demand is high across tasks with different stimuli, and whether connectivity between dACC and task-specific areas is increased depending on the task requirements and effort level at hand. For that purpose, a perceptual detection task was administered that required male and female human participants to detect either a face or a house in a noisy image. Effort demand was manipulated by adding little (low effort) or much (high effort) noise to the images. Results showed a network of dACC, anterior insula (AI), and intraparietal sulcus (IPS) to be more active when effort demand was high, independent of the performed task (face or house detection). Importantly, effort demand modulated functional connectivity between dACC and face-responsive or house-responsive perceptual areas, depending on the task at hand. This shows that dACC, AI, and IPS constitute a general effort-responsive network and suggests that the neural implementation of cognitive effort involves dACC-initiated sensitization of task-relevant areas.SIGNIFICANCE STATEMENT Although cognitive effort is generally perceived as aversive, its investment is inevitable when navigating an increasingly complex society. In this study, we demonstrate how the human brain tailors the implementation of effort to the requirements of the task at hand. We show increased effort-related activity in a network of brain areas consisting of dorsal anterior cingulate cortex (dACC), anterior insula, and intraparietal sulcus, independent of task specifics. Crucially, we also show that effort-induced functional connectivity between dACC and task-relevant areas tracks specific task demands. These results demonstrate how brain regions specialized to solve a task may be energized by dACC when effort demand is high.

Continuous track paths reveal additive evidence integration in multistep decision making.

Multistep decision making pervades daily life, but its underlying mechanisms remain obscure. We distinguish four prominent models of multistep decision making, namely serial stage, hierarchical evidence integration, hierarchical leaky competing accumulation (HLCA), and probabilistic evidence integration (PEI). To empirically disentangle these models, we design a two-step reward-based decision paradigm and implement it in a reaching task experiment. In a first step, participants choose between two potential upcoming choices, each associated with two rewards. In a second step, participants choose between the two rewards selected in the first step. Strikingly, as predicted by the HLCA and PEI models, the first-step decision dynamics were initially biased toward the choice representing the highest sum/mean before being redirected toward the choice representing the maximal reward (i.e., initial dip). Only HLCA and PEI predicted this initial dip, suggesting that first-step decision dynamics depend on additive integration of competing second-step choices. Our data suggest that potential future outcomes are progressively unraveled during multistep decision making.

Avoiding the conflict: Metacognitive awareness drives the selection of low-demand contexts.

Previous research attempted to explain how humans strategically adapt behavior in order to achieve successful task performance. Recently, it has been suggested that 1 potential strategy is to avoid tasks that are too demanding. Here, we report 3 experiments that investigate the empirically neglected role of metacognitive awareness in this process. In these experiments, participants could freely choose between performing a task in either a high-demand or a low-demand context. Using subliminal priming, we ensured that participants were not aware of the visual stimuli creating these different demand contexts. Our results showed that participants who noticed a difference in task difficulty (i.e., metacognitive aware participants) developed a clear preference for the low-demand context. In contrast, participants who experienced no difference in task difficulty (i.e., metacognitive unaware participants) based their choices on variables unrelated to cognitive demand (e.g., the color or location associated with a context), and did not develop a preference for the low-demand context. Crucially, this pattern was found despite identical task performance in both metacognitive awareness groups. A multiple regression approach confirmed that metacognitive awareness was the main factor driving the preference for low-demand contexts. These results argue for an important role of metacognitive awareness in the strategic avoidance of demanding tasks. (PsycINFO Database Record