Thumbs up or thumbs down? Effects of neuroticism and depressive symptoms on psychophysiological responses to social evaluation in healthy students

Abstract

The effects of neuroticism and depressive symptoms on psychophysiological responses in a social judgment task were examined in a sample of 101 healthy young adults. Participants performed a social judgment task in which they had to predict whether or not a virtual peer presented on a computer screen liked them. After the prediction, the actual judgment was shown, and behavioral, electrocortical, and cardiac responses to this judgment were measured. The feedback-related negativity (FRN) was largest after unexpected feedback. The largest P3 was found after the expected “like” judgments, and cardiac deceleration was largest following unexpected “do not like” judgments. Both the P3 and cardiac deceleration were affected by gender—that is, only males showed differential P3 responses to social judgments, and males showed stronger cardiac decelerations. Time–frequency analyses were performed to explore theta and delta oscillations. Theta oscillations were largest following unexpected outcomes and correlated with FRN amplitudes. Delta oscillations were largest following expected “like” judgments and correlated with P3 amplitudes. Self-reported trait neuroticism was significantly related to social evaluative predictions and cardiac reactivity to social feedback, but not to the electrocortical responses. That is, higher neuroticism scores were associated with a more negative prediction bias and with smaller cardiac responses to judgments for which a positive outcome was predicted. Depressive symptoms did not affect the behavioral and psychophysiological responses in this study. The results confirmed the differential sensitivities of various outcome measures to different psychological processes, but the found individual differences could only partly be ascribed to the collected subjective measures.

A comparison of the electrocortical response to monetary and social reward

“…Using a different social task, Sun and Yu (2014) also found a larger RewP in response to acceptance relative to rejection feedback. Finally, van der Veen et al (2016) found that during a social task a larger RewP was elicited by acceptance feedback that was unexpected relative to expected. These data suggest that a RewP is elicited by both non-social (e.g.…”

“…However, another investigation reported a greater RewP in 16 to 17 year-old girls compared with boys ( Santesso et al , 2011 ), while others have found no sex differences ( Foti and Hajcak, 2009 ; Bress et al , 2012 ). The limited studies that have examined sex differences in the social RewP have also been mixed: one reported a greater social RewP in young adult women compared with men ( van der Veen et al , 2016 ) and another reported no sex difference in the RewP in 10 to 15 year-old children ( Kujawa et al , 2014 ). To further examine this issue, this study tested for sex differences in the monetary and social RewP.…”

When the outcome is different than expected: Subjective expectancy shapes reward prediction error at the FRN level

“…Likewise, Soder and Potts () and Talmi et al () both reported ERP results suggesting that the FRN reflects an unsigned RPE rather than a signed RPE and that it has similar spatiotemporal properties and is even functionally equivalent for both worse‐ and better‐than‐expected outcomes. Recently, van der Veen and collaborators () showed that unexpected social judgments yielded larger FRNs when compared to correctly predicted ones. This result likewise suggests that the FRN is sensitive to salience rather than signed RPEs.…”

“…In the former situation, it is postulated that the outcome (i.e., feedback) is especially informative for the participants because it allows them to improve learning and adapt behavior accordingly, while this is less the case in the latter situation (Frank, Seeberger, & O'Reilly, 2004;Sambrook & Goslin, 2015;Walsh & Anderson, 2012). At slight variance with this theory, the salience prediction error account (Alexander & Brown, 2011;Oliveira, McDonald, & Goodman, 2007) suggests that the medial prefrontal cortex and, more specifically, the dorsal anterior cingulate cortex (ACC), which is thought to be the main intracranial generator of the FRN (Gehring & Willoughby, 2002;Miltner et al, 1997;Yeung, Holroyd, & Cohen, 2004), is sensitive to mismatches regardless of their sign, thereby responding equally strongly to better-thanexpected or worse-than-expected outcomes since they are both salient (Hauser et al, 2014;Soder & Potts, 2018;Talmi, Atkinson, & El-Deredy, 2013; van der Veen, van der Molen, van der Molen, & Franken, 2016). The question thus remains unsolved whether the FRN codes for a signed or an unsigned RPE.…”

Social dimension and complexity differentially influence brain responses during feedback processing

“…Thereby, effects of social evaluation (acceptance vs. rejection) and expectancy (expected vs. unexpected outcomes) were manipulated. Early feedback evaluation (FRN component) was mostly sensitive to expectancy violations (Dekkers, Van Der Molen, Gunther Moor, Van Der Veen, & Van Der Molen, 2015; Van Der Molen, Dekkers, Westenberg, Van Der Veen, & Van Der Molen, 2016;Van Der Veen, Van Der Molen, Van Der Molen, & Franken, 2016), while later ERP processing stages (P300 component) reflected expected acceptance judgements (Van Der Veen, Van Der Molen, Sahibdin, & Franken, 2014; or general expectancy effects (Dekkers et al, 2015). In task versions that omitted the expectancy manipulation, early feedback evaluation was also reflecting acceptance vs. rejection judgements (Kujawa et al, 2014;Sun & Yu, 2014).…”