Empathy concerns enhance prosociality and modulate frontal theta oscillatory activity in young adults

Abstract

Decision making is a process that can be strongly affected by social factors. Profuse evidence has shown how people deviate from traditional rational-choice predictions under different levels of social interactions. The emergence of prosocial decision making, defined as any action that is addressed to benefit another individual even at the expense of personal benefits, has been reported as an important example of such social influence. Furthermore, brain evidence has shown the involvement of structures such the prefrontal cortex, anterior insula and midcingulate cortex during decision settings in which a decision maker interacts with others under physical pain or distress or while being observed by others. Using a slightly modified version of the dictator game, we tested the hypothesis that the inclusion of another person into the decision setting increases prosocial decisions in young adults and that this increase is higher when the other person is associated with others in need. At the brain level, we hypothesized that the increase in prosocial decisions correlates with frontal theta activity as a marker of empathy saliency. The results showed that the inclusion of another person into the decision setting increased prosocial behavior only when this presence was associated with someone in need and that this was associated with an increase in frontocentral theta-oscillatory activity. These results suggest that the presence of someone in need enhances both empathy concerns and norm compliance, raising the participants’ prosocial decision making.

Patients Recovering from COVID-19 who Presented Anosmia During their Acute Episode have Behavioral, Functional, and Structural Brain Alterations

“…The results were presented in the figures depicting the posterior distribution of the parameters and the p MCMC derived from this analysis (p MCMC is a p-value derived by comparing the posterior distributions of the estimated parameters sampled via Markov Chain Monte Carlo; see section "Cognitive modeling" for details). Additionally, for testing behavioral indicators in the Reversal Learning Task, we employed non-parametric statistics (since these indicators generally have a non-normal distribution [39][40][41][42][43] ) and their respective effect size measures, together with mixed linear models.…”

Lateral Prefrontal Theta Oscillations Causally Drive a Computational Mechanism Underlying Conflict Expectation and Adaptation

“…62,65 Following these steps, we down-sampled EEG data to 1000 Hz and used a preprocessing pipeline developed for prior work. 30,31,34,[89][90][91][92] The EEG data was then filtered 0.1-45 Hz band-pass and segmented -0.5 to 1.5 seconds around the last TMS pulse. The independent component analysis (ICA) calculated in the first step removed components such as TMS-related artifacts, blinks, and eye movement.…”

“…14,28 Neurophysiological studies have remarked on the role of oscillatory activity in theta range in several aspects of cognitive control, including its deficit in pathologies. 7,[29][30][31][32][33][34] Oscillatory activity in the theta band over the frontal midline is associated with detecting, communicating, and implementing cognitive control. 29,35 Theta-band oscillations have been tied to adaptive control mechanisms during response conflict.…”

The effect of a cognitive training therapy based on stimulation of brain oscillations in patients with Mild Cognitive Impairment in a Chilean sample: study protocol for a randomised controlled trial

“…This continuous variable is sensitive to electrophysiological changes underlying cognitive processes as WM. It has been described in several works of our group and others [28, [42][43][44][45][46][47]. The primary timepoint for outcome measures will be three times: pre-intervention, 1 and 12 weeks post-intervention.…”