Comparing self-other distinction across motor, cognitive and affective domains

Abstract

The self-other distinction (SOD) is a process by which humans disentangle self from other-related mental representations. This online study investigated two unresolved questions: (i) whether partially the same processes underpin SOD for motor, cognitive and affective representations, and (ii) whether SOD overlaps with domain-general cognitive control processes. Participants (N = 243) performed three SOD tasks (motor: automatic imitation inhibition (AIT); cognitive: visual perspective-taking (VPT); affective: emotional egocentricity bias (av-EEB) tasks) and two cognitive control tasks (Stroop and stop-signal reaction time (SSRT) tasks). Correlation analyses showed no associations among the motor, cognitive and affective SOD indexes. Similarly, distinct SOD clusters emerged in the hierarchical clustering dendrogram, indicating clear separations among SODs. However, the results of multidimensional scaling suggested a tendency towards two clusters, as evidenced by the proximity of AIT and VPT indexes in relation to EEB indexes. AIT spatial laterality and Stroop domain-general cognitive control confounded AIT and VPT indexes, albeit slightly differently depending on the analysis method used. SSRT showed neither associations with SODs nor with other domain-general indexes. These findings underscore the complexity of SOD processes and have notable implications for basic and applied research, e.g. in the domain of clinical disorders affected by deficiencies in SOD.

Keywords: automatic imitation; cognitive control; emotional egocentricity bias; self–other distinction; visual perspective-taking.

Figure 1.

Timeline of (a) an Experimental Trial; (b) a Base Trial. Note: A trial starts with an intertrial interval, followed by a frame depicting a static hand alongside a white fixation square. In the experimental trials (a), the next frame shows a lifted finger. In the base trials (b), the stimulus hand remained static and was additionally pixelated. In this case, an orange fixation square provides a cue for a finger response (group 1: middle finger, group 2: index finger lift). The trial ends with a 1520 ms inter-stimulus interval. The next trial starts only when both N and M keys are pressed. Adapted from [, fig. 1]; Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License.

Figure 2.

Timeline of an experimental congruent trial. Note: The trial starts with a fixation cross, followed by an inter-stimulus interval (ISI). The next frame indicates to the participants that they have to adopt another person’s perspective (she) and memorize the digit 2. After the second ISI, the participant sees a gender-matched avatar (e.g. a woman) facing the wall with the two red discs on it. The correct response is yes since the memorized digit 2 matches the number of discs the avatar can see. In this example, the participant and the avatar see the same number of discs (congruent condition). Adapted from [46], stimuli: Samson & Apperly, 2015, Figshare [59].

Figure 3.

Timeline of an experimental incongruent self-trial. Note. A trial starts with an intertrial interval, followed by a picture depicting an applauding crowd. The text on the top of the picture indicates that the paired fake participant MAPR82 is listening to sounds associated with this picture (in this case, of a positive valence). The real participant is listening to the sound of a woman being attacked (negative valence), making it an incongruent trial. After 3000 ms, the participant had to rate their feelings induced by the attack audio stimulation (self-rating). Based on the study by [47], adapted from https://psyarxiv.com/j7vec/, CC0 1.0 Universal.

Figure 4.

Results of the hierarchical cluster analysis. Note: The SSRT variable is not displayed on this graph due to its significant distance from other variables (53.99). Its exclusion is intentional to enhance graph clarity. In the provided dendrogram, a horizontal line is drawn at a height of 0.35. This cut-off was selected based on the largest vertical gaps between merges, indicating significant separations between clusters. By examining the dendrogram, it is evident that cutting at this height allows for the identification of distinct groups within the data.

Figure 5.

Results of the multidimensional scaling. Note: The SSRT score is not displayed on this graph due to its significant distance from other scores (Dim1: 49.49, Dim2: 0.004). Its exclusion is intentional to enhance graph clarity. hc_clusters = Clusters identified through hierarchical clustering analysis.