Oscillatory brain activity as unified control mechanism for working memory and mentalizing
Friedrich, E. V. C.; Hilla, Y.; Sterner, E. F.; Ostermeier, S. S.; Behnke, L.; Sauseng, P.
Show abstract
It has long been thought that coordination of briefly maintained information (working memory) and higher social cognition (mentalizing) rely on mutually exclusive brain mechanisms. However, here we show that slow rhythmical brain activity in the dorsomedial prefrontal cortex controls distributed networks associated with working memory as well as mentalizing during cognitively demanding visual and social tasks. Depending on the effort necessary for cognitive operations, the phase of slow frontal oscillations is used to precisely tune communication with posterior brain areas. For participants having low autistic personality traits, this mechanism is identical across tasks - no matter whether visual or social information is processed. This underpins a unified function of the mentioned oscillatory brain mechanism in working memory and mentalizing. Participants with high autistic personality traits - thus, with difficulty in social cognition - however, have an inability to efficiently tune brain communication depending on cognitive effort in visual information processing. Even more striking, in higher social cognition they fail to implement coordination of distributed brain networks by slow frontal oscillations completely. While these findings suggest a unified function of brain oscillations in cognitive coordination they also explain why individuals with high autistic personality traits can have difficulties with demanding cognitive processing across domains. Significance StatementOur findings revealed an interregional brain coupling mechanism based on rhythmical cortical activity to be responsible for successful social and visual working memory by tuning the fronto-parietal network depending on memory load. We suggest that this coupling mechanism can explain how communication between distant brain areas is effectively controlling cognitive functions, independent of the exact type of information that is processed. Importantly, participants with high autistic personality traits struggle with efficient tuning of fronto-parietal networks. Thus, a deficit in this coupling mechanism seems to be an underlying cause of impairments in social and visual working memory, which is often seen in individuals on the Autism Spectrum. These findings might even generalize to other mental disorders as broad cognitive control deficits and social problems are common in a variety of psychiatric and neurological conditions.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- EEG frequency tagging evidence of intact social interaction recognition in adults with autism 96%
- Increased context adjustment is associated with auditory sensitivities but not with autistic traits 96%
- Reduced language lateralization in autism and the broader autism phenotype as assessed with robust individual-subjects analyses 95%
Similar papers in this journal
- Model-based learning deficits in compulsivity are linked to faulty representations of task structure 94%
- Uncharacteristic task-evoked pupillary responses implicate atypical locus coeruleus activity in autism 94%
- Visual motion and decision-making in dyslexia: Evidence of reduced accumulation of sensory evidence and related neural dynamics 93%
Similar papers in this journal
Similar papers in this journal
- Patterns of connectome variability in autism across five functional activation tasks. Findings from the LEAP project 95%
- Dynamic functional adaptations during touch observation in autism: Connectivity strength is linked to attitudes towards social touch and social responsiveness 95%
- From cognitive abstraction to adaptive behavior: neural bases of concept learning in autistic adolescents 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.