Role of human prefrontal cortex in the modulation of conditioned eyeblink responses

Interpersonal neural synchronization during social interactions in close relationships: A systematic review and meta-analysis of fNIRS hyperscanning studies

In recent years, researchers have used hyperscanning techniques to explore how brains interact during various human activities. These studies have revealed a phenomenon called interpersonal neural synchronization (INS), but little research has focused on the overall effect of INS in close relationships. To address this gap, this study aims to synthesize and analyze the existing literature on INS during social interactions in close relationships. We conducted a meta-analysis of 17 functional near-infrared spectroscopy (fNIRS) hyperscanning studies involving 1149 dyads participants, including romantic couples and parent-child dyads. The results revealed robust and consistent INS in the frontal, temporal, and parietal regions of the brain and found similar INS patterns in couples and parent-child studies, providing solid empirical evidence for the attachment theory. Moreover, the age of children and brain areas were significant predictors of the effect size in parent-child research. The developmental stage of children and the mismatched development of brain structures might be the crucial factors for the difference in neural performance in social and cognitive behaviors in parent-child dyads.

Cortico-Cerebellar Hyper-Connections and Reduced Purkinje Cells Behind Abnormal Eyeblink Conditioning in a Computational Model of Autism Spectrum Disorder

Empirical evidence suggests that children with autism spectrum disorder (ASD) show abnormal behavior during delay eyeblink conditioning. They show a higher conditioned response learning rate and earlier peak latency of the conditioned response signal. The neuronal mechanisms underlying this autistic behavioral phenotype are still unclear. Here, we use a physiologically constrained spiking neuron model of the cerebellar-cortical system to investigate which features are critical to explaining atypical learning in ASD. Significantly, the computer simulations run with the model suggest that the higher conditioned responses learning rate mainly depends on the reduced number of Purkinje cells. In contrast, the earlier peak latency mainly depends on the hyper-connections of the cerebellum with sensory and motor cortex. Notably, the model has been validated by reproducing the behavioral data collected from studies with real children. Overall, this article is a starting point to understanding the link between the behavioral and neurobiological basis in ASD learning. At the end of the paper, we discuss how this knowledge could be critical for devising new treatments.