Greater Social Competence Is Associated With Higher Interpersonal Neural Synchrony in Adolescents With Autism

Difficulty engaging in reciprocal social interactions is a core characteristic of autism spectrum disorder. The mechanisms supporting effective dynamic real-time social exchanges are not yet well understood. This proof-of-concept hyperscanning electroencephalography study examined neural synchrony as the mechanism supporting interpersonal social interaction in 34 adolescents with autism spectrum disorder (50% female), age 10–16 years, paired with neurotypical confederates of similar age. The degree of brain-to-brain neural synchrony was quantified at temporo-parietal scalp locations as the circular correlation of oscillatory amplitudes in theta, alpha, and beta frequency bands while the participants engaged in a friendly conversation. In line with the hypotheses, interpersonal neural synchrony was significantly greater during the social interaction compared to the baseline. Lower levels of synchrony were associated with increased behavioral symptoms of social difficulties. With regard to sex differences, we found evidence for stronger interpersonal neural synchrony during conversation than baseline in females with autism, but not in male participants, for whom such condition differences did not reach statistical significance. This study established the feasibility of hyperscanning during real-time social interactions as an informative approach to examine social competence in autism, demonstrated that neural coordination of activity between the interacting brains may contribute to social behavior, and offered new insights into sex-related variability in social functioning in individuals with autism spectrum disorders.

“The Enemy of My Enemy is My Friend”: Shared Negative but not Positive Emotional Experience is Associated with Neural Synchrony in the Medial Prefrontal Cortex

Prevalent, automatic, and powerful, emotional experience forms an integral part of human life. Despite numerous studies pointing at the impact of emotion in shaping one’s interpretation of situation and guiding action, emotional experience has not been studied extensively due to its idiosyncratic nature. However, advances in neuroimaging techniques and statistical analysis methods enabled more rigorous investigation of subjective experience, one of which is neural synchrony. Here we sought to examine if neural synchrony in regions within the default mode network, including medial prefrontal cortex (mPFC), bilateral temporoparietal junctions (TPJ) and inferior parietal lobules (IPL), underlies shared emotional experience. A hundred and four participants watched political videos while being scanned by Functional Near-Infrared Spectroscopy (fNIRS) and rated their emotional experience afterwards. Although initial Inter- Subject Correlation Analysis and Inter-Subject Representational Similarity Analysis did not yield significant findings, we addressed limitations of both approaches – loss of dimensionality and unequal comparisons of dyads – by combining them with k-means clustering. This improved version of analysis revealed that subjects who reported more similarly negative, but not positive, emotional experiences exhibited more synchronized neural fluctuations in mPFC. The results suggest that neural synchrony in mPFC may be driven primarily by negative sentiments and serve as a neural signature for subjective emotional experience.

Preservation of neural synchrony at peak alpha frequency via global synaptic scaling compensates for white matter structural decline over adult lifespan

We propose that preservation of functional integration, estimated from measures of neural synchrony, is a key neurocompensatory mechanism associated with healthy human ageing. To support this proposal, we demonstrate how phase-locking at peak alpha frequency from Magnetoencephalography (MEG) data is invariant over lifespan in a large cohort of human participants, aged 18-88 years. Using empirically derived connection topologies from diffusion tensor imaging (DTI) data, we create an in-silico model of whole-brain alpha dynamics. We show that enhancing inter-areal coupling can cancel the effect of increased axonal transmission delay associated with age-related degeneration of white matter tracts and thus, preserve neural synchrony. Together with analytical solutions for non-biological all-to-all connection scenarios, our model establishes the theoretical principles by which frequency slowing with age, frequently observed in the alpha band in diverse populations, can be viewed as an epiphenomenon of the underlying neurocompensatory mechanisms.

Aperiodic EEG activity masks the dynamics of neural oscillations during loss of consciousness from propofol

EEGs are known to provide biomarkers for consciousness. Although EEG correlates of loss of consciousness (LOC) are often ascribed to changes in neural synchrony, mounting evidence suggests that some changes result from asynchronous neural activity. By combining EEG recordings of humans undergoing propofol administration with biophysical modelling, we present here a principled decomposition of EEG changes during LOC into synchronous and asynchronous sources. Our results reveal that IPSP decay rate and mean spike rate shape aperiodic EEG features, and that propofol's effects on these parameters largely explain the changes in EEG spectra following propofol infusion. We further show that traditional spectral EEG analysis likely conflates these effects with changes in rhythmic activity, thereby masking the true dynamics of neural synchrony. We conclude that the well-documented propofol-induced alpha rhythm in fact appears before LOC, and that the moment of LOC is uniquely correlated with the sudden appearance of a delta rhythm.

Getting in synch: Unpacking the role of parent–child synchrony in the development of internalizing and externalizing behaviors

While substantial research supports the role of parent–child interactions on the emergence of psychiatric symptoms, few studies have explored biological mechanisms for this association. The current study explored behavioral and neural parent–child synchronization during frustration and play as predictors of internalizing and externalizing behaviors across a span of 1.5 years. Parent–child dyads first came to the laboratory when the child was 4–5 years old and completed the Disruptive Behavior Diagnostic Observation Schedule: Biological Synchrony (DB-DOS: BioSync) task while functional near-infrared spectroscopy (fNIRS) data were recorded. Parents reported on their child's internalizing and externalizing behaviors using the Child Behavior Checklist (CBCL) four times over 1.5 years. Latent growth curve (LGC) modeling was conducted to assess neural and behavioral synchrony as predictors of internalizing and externalizing trajectories. Consistent with previous investigations in this age range, on average, internalizing and externalizing behaviors decreased over the four time points. Parent–child neural synchrony during a period of play predicted rate of change in internalizing but not externalizing behaviors such that higher parent–child neural synchrony was associated with a more rapid decrease in internalizing behaviors. Our results suggest that a parent–child dyad's ability to coordinate neural activation during positive interactions might serve as a protective mechanism in the context of internalizing behaviors.

Neural Synchrony for Adaptive Control

Cognitive control can be adaptive along several dimensions, including intensity (how intensely do control signal influence bottom–up processing) and selectivity (what information is selected for further processing). Furthermore, control can be exerted along slow or fast time scales. Whereas control on a slow time scale is used to proactively prepare for upcoming challenges, control can also be used on a faster time scale to react to unexpected events that require control. Importantly, a systematic comparison of these dimensions and time scales remains lacking. Moreover, most current models of adaptive control allow predictions only at a behavioral, not neurophysiological, level, thus seriously reducing the range of available empirical restrictions for informing model formulation. The current article addresses this issue by implementing a control loop in an earlier model of neural synchrony. The resulting model is tested on a Stroop task. We observe that only the model that exerts cognitive control on intensity and selectivity dimensions, as well as on two time scales, can account for relevant behavioral and neurophysiological data. Our findings hold important implications for both cognitive control and how computational models can be empirically constrained.