An energy costly architecture of neuromodulators for human brain evolution and cognition.

In comparison to other species, the human brain exhibits one of the highest energy demands relative to body metabolism. It remains unclear whether this heightened energy demand uniformly supports an enlarged brain or if specific signaling mechanisms necessitate greater energy. We hypothesized that the regional distribution of energy demands will reveal signaling strategies that have contributed to human cognitive development. We measured the energy distribution within the brain functional connectome using multimodal brain imaging and found that signaling pathways in evolutionarily expanded regions have up to 67% higher energetic costs than those in sensory-motor regions. Additionally, histology, transcriptomic data, and molecular imaging independently reveal an up-regulation of signaling at G-protein-coupled receptors in energy-demanding regions. Our findings indicate that neuromodulator activity is predominantly involved in cognitive functions, such as reading or memory processing. This study suggests that an up-regulation of neuromodulator activity, alongside increased brain size, is a crucial aspect of human brain evolution.

Learning something new versus changing your ways: Distinct effects on midfrontal oscillations and cardiac activity for learning and flexible adjustments.

We need to be able to learn new behaviour, but also be capable of changing existing routines, when they start conflicting with our long-term goals. Little is known about to what extent blank-slate learning of new and adjustment of existing behavioural routines rely on different neural and bodily mechanisms. In the current study, participants first acquired novel stimulus-response contingencies, which were subsequently randomly changed to create the need for flexible adjustments. We measured midfrontal theta oscillations via EEG as an indicator of neural conflict processing, as well as heart rate as a proxy of autonomic activity. Participants' trial-wise learning progress was estimated via computation modelling. Theta power and heart rate significantly differed between correct and incorrect trials. Differences between correct and incorrect trials in both neural and cardiac feedback processing were more pronounced for adjustments compared to blank-slate learning. This indicates that both midfrontal and cardiac processing are sensitive to changes in stimulus-response contingencies. Increases in individual learning rates predicted lower impact of performance feedback on midfrontal theta power, but higher impact on heart rate. This suggests that cardiac and midfrontal reactivity are partially reflective of different mechanisms related to feedback learning. Our results shed new light on the role of neural and autonomic mechanisms for learning and behavioural adjustments.