Gaze bias differences capture individual choice behaviour

Thomas, Armin W.; Molter, Felix; Krajbich, Ian; Heekeren, Hauke R.; Mohr, Peter N. C.

doi:10.1038/s41562-019-0584-8

Cited by 78 publications

(147 citation statements)

References 77 publications

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“…The model has four parameters (v, γ, σ, τ ). By default, uninformative, uniform priors between sensible limits (derived from earlier applications to four different datasets; Thomas et al, 2019) are placed on all parameters:…”

Section: Gaze-weighted Linear Accumulator Model Detailsmentioning

confidence: 99%

“…Hierarchical parameter estimation details. For hierarchical models, individual parameters are assumed to be drawn from Truncated Normal distributions, parameterized by mean and standard deviation, over which weakly informative, Truncated Normal priors are assumed (based on the distribution of group level parameter estimates obtained from four different datasets in Thomas et al 2019;see Figs. 2, A2 and A3 and Table A1): Figure 2 .…”

Section: Gaze-weighted Linear Accumulator Model Detailsmentioning

confidence: 99%

“…Our first example is based on the study by Thomas et al (2019). Here, the authors study the association between gaze allocation and choice behaviour on the level of the individual.…”

Section: Example 1: Individual Level Data and Model Comparisonmentioning

confidence: 99%

“…between gaze allocation and choice behaviour (Smith & Krajbich, 2018;Thomas, Molter, Krajbich, Heekeren, & Mohr, 2019) as well as individual differences in the decision mechanisms used (Ashby et al, 2016). Yet, the majority of model-based investigations of the relationship between gaze allocation and choice behaviour were focused on the group level, disregarding differences between individuals.…”

mentioning

confidence: 99%

“…With the Gaze-weighted linear accumulator model (GLAM; Thomas et al, 2019), we have proposed an analytical tool that allows the model-based investigation of the relationship between gaze allocation and choice behaviour at the level of the individual, in choice situations involving more than two alternatives, solely requiring participants' choice, response time (RT) and gaze data, in addition to estimates of the items' values.…”

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confidence: 99%

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GLAMbox: A Python toolbox for investigating the association between gaze allocation and decision behaviour

Molter¹,

Thomas²,

Heekeren³

et al. 2019

Preprint

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Recent empirical findings have indicated that gaze allocation plays a crucial role in simple decision behaviour. Many of these findings point towards an influence of gaze allocation onto the speed of evidence accumulation in an accumulation-to-bound decision process (resulting in generally higher choice probabilities for items that have been looked at longer). Further, researchers have shown that the strength of the association between gaze and choice behaviour is highly variable between individuals, encouraging future work to study this association on the individual level. However, only few decision models exist that easily allow studying the gaze-choice association on the individual level, due to the high cost of developing and implementing them. The model space is particularly scarce for choice sets with more than two choice alternatives. Here, we present GLAMbox, a Python-based toolbox that is built upon PyMC3 and allows the easy application of the gaze-weighted linear accumulator model (GLAM) to experimental choice data. The GLAM assumes gaze-dependent evidence accumulation in a linear stochastic race that extends to decision scenarios with many choice alternatives. GLAMbox enables Bayesian parameter estimation of the GLAM for individual, pooled or hierarchical models, provides an easy-to-use interface to predict choice behaviour and visualize choice data, and benefits from all of PyMC3's Bayesian statistical modeling functionality. Further documentation, resources and the toolbox itself are available at https://github.com/glamlab/glambox.A plethora of empirical findings has established an association between gaze allocation and decision behaviour on the group-level. For example, in value-based decision making, it was repeatedly shown that longer gaze towards one option is associated with a higher choice probability for that option (

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Section: Gaze-weighted Linear Accumulator Model Detailsmentioning

confidence: 99%

Section: Gaze-weighted Linear Accumulator Model Detailsmentioning

confidence: 99%

“…Our first example is based on the study by Thomas et al (2019). Here, the authors study the association between gaze allocation and choice behaviour on the level of the individual.…”

Section: Example 1: Individual Level Data and Model Comparisonmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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GLAMbox: A Python toolbox for investigating the association between gaze allocation and decision behaviour

Molter¹,

Thomas²,

Heekeren³

et al. 2019

Preprint

Self Cite

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To covet what we see: Autistic traits modulate the relationship between looking and choosing

Hedger

Chakrabarti

2020

Autism Research

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Behavioral studies indicate that autistic traits predict reduced gaze toward social stimuli. Moreover, experiments that require participants to make an explicit choice between stimuli indicate reduced preferences for social stimuli in individuals with high autistic traits. These observations, in combination, fit with the idea that gaze is actively involved in the formation of choices—gaze toward a stimulus increases the likelihood of its subsequent selection. Although these aspects of gaze and choice behavior have been well characterized separately, it remains unclear how autistic traits affect the relationship between gaze and socially relevant choices. In a choice‐based eye‐tracking paradigm, we observed that autistic traits predict less frequent and delayed selection of social stimuli. Critically, eye tracking revealed novel phenomena underlying these choice behaviors: first, the relationship between gaze and choice behavior was weaker in individuals with high autistic traits—an increase in gaze to a stimulus was associated with a smaller increase in choice probability. Second, time‐series analyses revealed that gaze became predictive of choice behaviors at longer latencies in observers with high autistic traits. This dissociation between gaze and choice in individuals with high autistic traits may reflect wider atypicalities in value coding. Such atypicalities may predict the development of atypical social behaviors associated with the autism phenotype. Lay Summary When presented with multiple stimuli to choose from, we tend to look more toward the stimuli we later choose. Here, we found that this relationship between looking and choosing was reduced in individuals with high autistic traits. These data indicate that autistic traits may be associated with atypical processing of value, which may contribute to the reduced preferences for social stimuli exhibited by individuals with autism.

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Choice Repetition Bias in Intertemporal Choice: An Eye‐Tracking Study

Senftleben,

Schoemann,

Scherbaum

2024

Behavioral Decision Making

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Intertemporal choices (i.e., the choice between a sooner available but smaller reward and a later available but larger reward) were initially thought to reflect stable preferences for immediate or delayed rewards. However, recently, it has been shown that intertemporal choices are influenced by factors such as context variables and attentional processes. Here, we investigate if another factor, the choice repetition bias, affects decision making and attentional processes in intertemporal choice. The choice repetition bias is characterized by the tendency to repeat previous choices and to be slower when switching to an alternative choice. In a series of two experiments (including a preregistered, eye‐tracking study), we find that the choice repetition bias exists in intertemporal choice. We also find tentative support for an early attentional bias towards the favored attribute dimension of the previous choice; however, this effect disappears when taking the whole decision process into account. This finding raises interesting questions about the cognitive processes underlying the choice repetition bias. In addition, we successfully replicate other attentional effects from the intertemporal choice literature (e.g., more fixations on monetary dimension, gaze cascade effect).

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Gaze bias differences capture individual choice behaviour

Cited by 78 publications

References 77 publications

GLAMbox: A Python toolbox for investigating the association between gaze allocation and decision behaviour

GLAMbox: A Python toolbox for investigating the association between gaze allocation and decision behaviour

To covet what we see: Autistic traits modulate the relationship between looking and choosing

Choice Repetition Bias in Intertemporal Choice: An Eye‐Tracking Study

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