Academic journal article Cognitive, Affective and Behavioral Neuroscience

Empathy and Feedback Processing in Active and Observational Learning

Academic journal article Cognitive, Affective and Behavioral Neuroscience

Empathy and Feedback Processing in Active and Observational Learning

Article excerpt

Published online: 11 July 2013

# Psychonomic Society, Inc. 2013

Abstract The feedback-related negativity (FRN) and the P300 have been related to the processing of one's own and other individuals' feedback during both active and observa- tional learning. The aim of the present study was to elucidate the role of trait-empathic responding with regard to the mod- ulation of the neural correlates of observational learning in particular. Thirty-four healthy participants completed an ac- tive and an observational learning task. On both tasks, the participants' aim was to maximize their monetary gain by choosing from two stimuli the one that showed the higher probability of reward. Participants gained insight into the stimulus--reward contingencies according to monetary feed- back presented after they had made an active choice or by observing the choices of a virtual partner. Participants showed a general improvement in learning performance on both learn- ing tasks. P200, FRN, and P300 amplitudes were larger during active, as compared with observational, learning. Further- more, nonreward elicited a significantly more negative FRN than did reward in the active learning task, while only a trend was observed for observational learning. Distinct subcompo- nents of trait cognitive empathy were related to poorer perfor- mance and smaller P300 amplitudes for observational learning only. Taken together, both the learning performance and event-related potentials during observational learning are af- fected by different aspects of trait cognitive empathy, and certain types of observational learning may actually be disrupted by a higher tendency to understand and adopt other people's perspectives.

Keywords FRN . Cognitive empathy . Affective empathy . Anterior cingulate cortex (ACC)

In everyday life, we constantly monitor our behavior and adapt our actions following performance errors. Depending on the social, monetary, or other type of feedback we receive from our environment, we can either feel encour- aged or discouraged to continue with a specific behavior. According to the reinforcement learning theory (Holroyd & Coles, 2002), reward-based learning is driven by the dopa- mine (DA) system. A dopaminergic prediction error signal originates in the midbrain and is reflected by an increase of activity for positive and a reduction for negative prediction errors. This signal is projected to the anterior cingulate cortex (ACC), where activation increases, for unexpected outcomes are supposed to underlie action selection (Schultz, 1998, 2001; Schultz, Dayan, & Montague, 1997).

In humans, the analysis of event-related potentials (ERPs) yielded a negative feedback-locked component, the so-called feedback-related negativity (FRN), which has been associated with the processing of unexpected negative performance feed- back (Bellebaum & Daum, 2008; Hajcak, Holroyd, Moser, & Simons, 2005; Hajcak, Moser, Holroyd, & Simons, 2007; Holroyd, Nieuwenhuis, Yeung, & Cohen, 2003; Yasuda, Sato, Miyawaki, Kumano, & Kuboki, 2004) and is generated in the ACC (Gehring & Willoughby, 2002). Typically, the process- ing of feedback stimuli also evokes a later, positive ERP component termed P300, modulated by the probability of stimulus occurrence (Hajcak et al., 2005) and by task rele- vance (Polich, 2007), with enhanced amplitudes for infrequent stimuli and more motivationally salient tasks (Carrillo-de-la- Pena & Cadaveira, 2000; Pfabigan, Alexopoulos, Bauer, & Sailer, 2011). The role of the P300 in the context of feedback processing is as yet unclear. While some authors reported larger P300 amplitudes for positive than for negative, for unexpected than for expected, and for larger than for smaller outcomes (Hajcak et al., 2005; Leng & Zhou, 2010;Maetal., 2011; Yeung & Sanfey, 2004), others could, for example, not find P300 amplitude modulations by feedback valence (Sato et al., 2005; Yeung & Sanfey, 2004). …

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