Bilateral (but not unilateral) interaction creates and cements norms at the covert psychophysical level: A behavioral and an fMRI study

Abstract

Social norms, including values, beliefs and even perceptions about the world, are preserved and created through repeated interactions between individuals. However, whereas neuro-cognitive research on social norms has used the “unilateral influence” paradigm focusing on people’s reactions to extant standards, little is known about how our basic perceptions and judgments are shaped as new norms through bilateral interaction. Here, using a simple estimation task, we investigated the formation of perceptual norms using two experiments coupled with computational modeling. In the behavioral experiment, participants in dyads repeatedly estimated the number of dots on a screen and viewed each other’s answers. In the fMRI experiment, we manipulated the interaction process by pairing each participant with a computer agent which adjusted its estimations reciprocally to participants’ estimations (bilateral agent) or did not (unilateral). The results indicated that only the bilateral interaction yielded convergence of participants’ covert psychophysical functions (relations between subjective estimations and the actual number of dots) as well as overt behavioral responses within a pair. Bilateral interaction also increased the stability (reliability) of the covert function within each individual after interaction. Neural activity in the mentalizing network (right temporoparietal junction and dorsomedial prefrontal cortex) during interaction modulated the stabilization of the psychophysical function. These results imply that bilateral interaction helps people to cognitively anchor their views with each other. Such spontaneous perspective sharing can yield a shared covert “generative model” that enables endogenous agreement on totally new targets ― one of the key features of social norms.

Insights about the common generative rule underlying an information foraging task can be facilitated via collective search

“…This result indicates that the social interaction between decision makers played an essential role in developing insights about the generative rule. In other words, across-task learning may be achieved as a kind of collective intelligence, emerging through reciprocal interactions of learning with a partner, rather than one-way observational learning [34][35][36] .…”

“…However, to test this conjecture, we will need to develop a fine-grained computational model of trial-by-trial interaction processes and test its validity by manipulating the social process experimentally, for example by introducing artificial "bots" as interaction partners 36,39 . Future research incorporating these techniques seems promising for illuminating the interaction elements that are critical for across-task learning in groups.…”