Neurophysiological correlates of interpersonal discrepancy and social adjustment in an interactive decision-making task in dyads

Summary:  View help for Summary The pursuit of convergence and the social behavioral adjustment of conformity are fundamental cooperative behaviors that help people adjust their mental frameworks to reach a common goal. However, while social psychology extensively studies conformity, there is still plenty to investigate about the neural mechanisms underlying this behavior. We proposed a paradigm with two phases, a pre-activation phase to enhance cooperative tendencies and, later, a social decision-making phase where conformity happens spontaneously and synchronously through the pursuit of convergence.  Study 1 shows evidence from 80 participants that the pre-activation phase enhances convergence in dyads. In Study 2, we registered in phase 2 the electroencephalographical (EEG) activity of 36 participants in which dyads had to make a perceptual estimation in three consecutive trials and converge in their decisions without an explicit request or reward to do so. Event-related Potentials (ERP) revealed signal differences in response divergence in three intervals. Time-frequency analysis showed theta, alpha, and beta evidence related to cognitive control, attention, and reward processing associated with social convergence. 

Sampling:  View help for Sampling EEG was recorded using an ANT Neuro ASALab EEG amplifier at 1024 Hz using two different elastic caps from 27 scalp electrodes (Fp1/2, Fz, F3/4, F7/8, FC1/2, FC5/6, Cz, C3/4, Cp1/2, CP5/6, Pz, P3/4, P7/8, Poz, Oz, M1/2). Eye movements were registered with an electrode associated with the participant's dominant hand at the infraorbital ridge of the eye. The electrode impedance was kept below 5kΩ during the task.  The electrophysiological signal was bandpass filtered, with cut-off frequencies of 0.1 Hz to 30Hz, and re-referenced to the activity of the two mastoids. Epoch events were extracted from -2 to 2 seconds after the stimuli showing the estimated position of each participant (feedback). Independent Component Analysis (ICA) (Makeig & Onton, 2011) was used to clean artifacts and, afterwards, epochs exceeding ± 100 μV from -100 ms to 1000 ms were automatically rejected. Time-frequency (TF) analysis was also computed by convolving single trials with 7 cycle complex Morlet wavelet for frequencies ranging from 1 to 30 Hz. Changes in power were computed by dividing power value by baseline (-400 ms to -100 ms) for each electrode, frequency, and condition. The ERP/TF analysis focused on three midline electrodes (Fz, Cz and Pz) and the different time ranges were based on visual inspection of the corresponding ERPs.  Statistical analysis of time-frequency data was performed in theta (4-8Hz), alpha (8-12Hz) and beta (12-30Hz) bands.