Biology subjects

Friedrich, E. V. C.

Publications and source records attributed to Friedrich, E. V. C..

3 recordsLinked to original sources

bioRxiv2023

Oscillatory brain activity as unified control mechanism for working memory and mentalizing

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.

neuroscience↗

bioRxiv2023

Who you gonna call? TMS-induced inhibition of the left premotor cortex acts as a Bayesian Ghost Buster by altering illusory social perception

Communicative actions from one person are used to predict another persons response. However, in some cases, these predictions can outweigh the processing of sensory information and lead to illusory social perception such as seeing two people interact, although only one is present (i.e., seeing a Bayesian ghost). We applied either inhibitory brain stimulation over the left premotor cortex (i.e., real TMS) or sham TMS. Then, participants indicated the presence or absence of a masked agent that followed a communicative or individual gesture of another agent. As expected, participants had more false alarms (i.e., Bayesian ghosts) in the communicative than individual condition in the sham TMS session and this difference between conditions vanished after real TMS. In contrast to our hypothesis, the number of false alarms increased (rather than decreased) after real TMS. These pre-registered findings confirm the significance of the premotor cortex for social action predictions and illusory social perception. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=145 SRC="FIGDIR/small/526257v2_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1b5812corg.highwire.dtl.DTLVardef@1338411org.highwire.dtl.DTLVardef@123b84eorg.highwire.dtl.DTLVardef@192a4b_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LISocial predictions can outweigh sensory information and lead to illusory perception C_LIO_LIPremotor cortex is linked to the illusory social perception of a Bayesian ghost C_LIO_LITMS over premotor cortex modulates how social predictions influence our perception C_LI

neuroscience↗

bioRxiv2022

Temporal dynamics of oscillatory brain activity during the observation of communicative interactions between point-light agents

Predicting actions from nonverbal cues and using them to optimize ones response behavior (i.e., interpersonal predictive coding) is essential in everyday social interactions. We aimed to investigate the neural correlates of different cognitive processes evolving over time during interpersonal predictive coding. Thirty-nine participants watched two agents depicted by moving point-light stimuli while an electroencephalogram (EEG) was recorded. One well-recognizable agent performed either a communicative or an individual action. The second agent either was blended into a cluster of noise dots (i.e., present), or was entirely replaced by noise dots (i.e., absent), which participants had to differentiate. EEG amplitude and coherence analyses for theta, alpha and beta frequency bands revealed a dynamic pattern unfolding over time: Watching communicative actions was associated with enhanced coupling within medial anterior regions involved in social and mentalizing processes and with dorsolateral prefrontal activation indicating a higher deployment of cognitive resources. Trying to detect the agent in the cluster of noise dots without having seen communicative cues was related to enhanced coupling in posterior regions for social perception and visual processing. Observing an expected outcome was modulated by motor system activation. Finally, when the agent was detected correctly, activation in posterior areas for visual processing of socially-relevant features was increased. Taken together, our results demonstrate that it is crucial to consider the temporal dynamics of social interactions and of their neural correlates to better understand interpersonal predictive coding. This could lead to optimized treatment approaches for individuals with problems in social interactions.

neuroscience↗