Choice history biases in dyadic decision making

A Ann Huang M Mathis Pink V Viktoria Zemliak A Artur Czeszumski P Peter König

Abstract

Abstract How do we interact with our environment and make decisions about the world around us? Empirical research using psychophysical tasks has demonstrated that our perceptual decisions are influenced by past choices, a phenomenon known as the “choice history bias” effect. This decision-making process suggests that the brain adapts to environmental uncertainties based on history. However, single-subject experiment task design is prevalent across the work on choice history bias, thus limiting the implications of the empirical evidence to individual decisions. Here, we explore the choice history bias effect using a dual-participant approach, where dyads perform a shared perceptual decision-making task. We first propose two competing hypotheses: the participants equally weigh their own and their partner’s decision history, or the participants do not weigh equally their own and their partner’s decision history. We then use a statistical modeling approach to fit generalized linear models to the choice data in a series of steps and arrive at a model that best fits the observed data. Our results indicated that the own and partner’s trial history cannot be treated independently. The findings suggest an interaction of actor and decision at 1-back, leading to a choice alternation bias after a partner’s decision in contrast to a choice repetition bias after an own decision. A similar effect is observed at 2-back, in addition to an additive choice repetition bias of similar size. The effects of actor and decision at 2-back do not depend on the properties of the 1-back trial. Together, these findings support the idea that the participants do not ignore their partner’s decisions but treat these qualitatively differently from their own.

Article Details

Volume / Issue Vol. 15, Issue 1
Published April 03, 2025
ISSN 2045-2322
Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (5)

A

Ann Huang

M

Mathis Pink

V

Viktoria Zemliak

A

Artur Czeszumski

P

Peter König