Journal of Psychological Science ›› 2022, Vol. 45 ›› Issue (1): 242-249.

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Causal Link and Weighting: The Eye Movement Model of Decision Making

  

  • Received:2020-04-06 Revised:2020-11-18 Online:2022-01-20 Published:2022-01-20
  • Contact: Hong-Zhi Liu

因果与权重:决策的眼动模型

刘洪志1,魏子晗2,盈嘉1,贺祉秋1,李东启1   

  1. 1. 南开大学
    2.
  • 通讯作者: 刘洪志

Abstract: Drift-diffusion models (DDMs), which are a type of process model, have shown promising potential in predicting the choices of consumer products, risky prospects, and intertemporal alternatives in recent years. The basic assumption underlying all DDMs is that preferences are constructed through a dynamic information acquisition process. Specifically, individuals’ preferences are formed by sampling from available alternatives until the evidence supporting one alternative is strong enough to induce a decision. Two key debates exist among different versions of DDMs. One is the issue of the causal link between gaze and decision. Certain DDMs assume that visual fixation process has a causal effect on choices, whereas other DDMs assume that fixation lengths are affected by the accumulated evidence of the alternatives. Such evidence produces a correlation between fixation lengths and choices without giving a causal role to fixations. The other key debate is the primacy/recency issue. Hence, incoming evidence is weighted more (recency) or less (primacy) than previously accumulated evidence. These two issues are unresolved and require further evidence. In the present study, we employed a gaze-contingent paradigm to manipulate participants’ gaze in a value-based binary food choice context. This paradigm involves endogenously manipulating the timing of decision s. By monitoring participants’ eye movements during decision-making, an experimenter can terminate participants’ deliberation and them to choose between two options the moment they fixate on a specific target option for a set amount of time. First, this gaze-contingent manipulation allowed us to examine the causal link between gaze patterns and choices. Therefore, we examined if participants’ choices were systematically biased toward the target options. Second, the gaze-contingent manipulation has different influences on the gaze time in various decision periods. Hence, we also investigated the dynamic changes of the decision evidence weighting to examine the primacy/recency assumption of DDMs. In the current study, we found that, first, participants’ value-based choices were systematically biased to the predetermined target options. Second, the relative time advantage and the last fixated option could significantly predict participants’ choices. Third, the gaze-contingent paradigm affected the gaze duration in the last third of the decision process. Fourth, causal mediation analysis revealed that the relative time advantage in the last third period could fully mediate the effect of target option on choices, i.e., the predetermined target options lead to longer duration on the target options in the last third period, thus making participants likely to choose the target options. Fifth, the results of the estimated parameters supported the recency assumption of DDMs, indicating that incoming evidence is weighted more than previously accumulated evidence. Results generally suggest that a causal link exists between gaze-contingent manipulation and value-based choices and that recent evidence is weighted more during the evidence accumulation process in DDMs. Moreover, findings revealed the mechanism of the gaze-contingent manipulation paradigm and the dynamic fixation process during this paradigm. This research helps clarify the two key issues of DDMs and deepens our understanding of the relationship between visual fixation and value-based choices.

Key words: eye-tracking, value-based choice, drift-diffusion model, causal link

摘要: 结合眼动注视的漂移扩散模型可很好描述个体的决策行为,但尚存在两个问题未得到解决:注视与决策的因果关系以及决策过程中累积证据的权重问题。本研究采用基于注视的操纵范式考察了基于价值的决策中注视与决策的关系,发现操纵被试对选项的注视时间可影响其选择,注视操纵主要影响决策后期时程,且模型参数估计结果更支持近因模型。研究结果支持了漂移扩散模型的近因假设,为今后的模型发展指明了新方向。

关键词: 眼动追踪技术, 基于价值的决策, 漂移扩散模型, 因果关系