RESUMEN
Social motivation, the human desire to engage with others, is likely to underlie higher levels of social cognition and the formation of interpersonal relationships. Yet, this topic has been understudied in adolescents despite the critical developmental and maturational changes that occur during this period and the relevance of social motivation to clinical and neurodevelopmental disorders. Using electroencephalography (EEG) and an implicit-association paradigm (Choose-A-Movie Task; Dubey et al., 2015), we examined how brain responses underlying socially motivated decisions informed future decisions in 54 youth (aged 10-14 years) and 50 young adults (aged 18-33 years). As the first study to use this task during EEG recording, we implemented time-frequency analyses and a trial-by-trial dynamic statistical approach. Results suggested that both age groups preferred low-effort choices and increasingly preferred nonsocial choices over time. P3 amplitude also increased over time and was sensitive to effortful decisions, particularly for adults, but not social content. Both groups showed larger leftward frontal alpha asymmetry (FAA) during nonsocial feedback, and FAA predicted future decisions differently for adults than youth. The current study highlights FAA and trial-by-trial analyses as useful tools in understanding the neural mechanisms underlying socially motivated decisions, which differ across development, time, and individuals.
RESUMEN
Biological systems typically exhibit complex behavior with nonlinear dynamic properties. Nonlinear signal processing techniques such as sample entropy is a novel approach to characterize the temporal dynamics of brain connectivity. Estimating entropy is especially important in clinical populations such as autism spectrum disorder (ASD) as differences in entropy may signal functional alterations in the brain. Considering the models of disrupted brain network connectivity in ASD, sample entropy would provide a novel direction to understand brain organization. Resting state fMRI data from 45 high-functioning children with ASD and 45 age-and-IQ-matched typically developing (TD) children were obtained from the Autism Brain Imaging Data Exchange (ABIDE-II) database. Data were preprocessed using the CONN toolbox. Sample entropy was then calculated using the complexity toolbox, in a whole-brain voxelwise manner as well as in regions of interests (ROIs) based methods. ASD participants demonstrated significantly increased entropy in left angular gyrus, superior parietal lobule, and right inferior temporal gyrus; and reduced sample entropy in superior frontal gyrus compared to TD participants. Positive correlations of average entropy in clusters of significant group differences scores across all subjects were found. Finally, ROI analysis revealed a main effect of lobes. Differences in entropy between the ASD and TD groups suggests that entropy may provide another important index of brain dysfunction in clinical populations like ASD. Further, the relationship between increased entropy and ASD symptoms in our study underscores the role of optimal brain synchronization in cognitive and behavioral functions.