Gazing into a discrete world:Mixture models of cognition & behaviour

This thesis titled Gazing into a Discrete World presents perspectives on modeling human behavior, focusing on alternative sources of data such as eye-tracking and response times, with a special focus dedicated to substantive questions about qualitative patterns in individual differences and development. Further, it advocates for a closer alignment between design and analysis of experiments, and their theoretical underpinnings. The thesis is structured into three distinct parts. The first part delves into identifying and analyzing discrete behavioral patterns, particularly through eye movement data, emphasising model-based approaches for understanding visual attention. The second part addresses challenges in empirical research, with a focus on developmental psychology, offering remedies for imperfections and methodological advancements. The third part focuses on making correct inferences under uncertainty, highlighting the significance of Bayesian methods and developing openly available software tools for applied researchers.The thesis contributes with advancements in integration of eye-tracking into cognitive-behavioral modeling, improvements in developmental psychology research, and provides openly available Bayesian tools

Gazing into a discrete world:Mixture models of cognition & behaviour

This thesis titled Gazing into a Discrete World presents perspectives on modeling human behavior, focusing on alternative sources of data such as eye-tracking and response times, with a special focus dedicated to substantive questions about qualitative patterns in individual differences and development. Further, it advocates for a closer alignment between design and analysis of experiments, and their theoretical underpinnings. The thesis is structured into three distinct parts. The first part delves into identifying and analyzing discrete behavioral patterns, particularly through eye movement data, emphasising model-based approaches for understanding visual attention. The second part addresses challenges in empirical research, with a focus on developmental psychology, offering remedies for imperfections and methodological advancements. The third part focuses on making correct inferences under uncertainty, highlighting the significance of Bayesian methods and developing openly available software tools for applied researchers.The thesis contributes with advancements in integration of eye-tracking into cognitive-behavioral modeling, improvements in developmental psychology research, and provides openly available Bayesian tools

Characterising eye movement events with an unsupervised hidden markov model

Eye-tracking allows researchers to infer cognitive processes from eye movements that are classified into distinct events. Parsing the events is typically done by algorithms. Here we aim at developing an unsupervised, generative model that can be fitted to eye-movement data using maximum likelihood estimation. This approach allows hypothesis testing about fitted models, next to being a method for classification. We developed gazeHMM, an algorithm that uses a hidden Markov model as a generative model, has few critical parameters to be set by users, and does not require human coded data as input. The algorithm classifies gaze data into fixations, saccades, and optionally postsaccadic oscillations and smooth pursuits. We evaluated gazeHMM’s performance in a simulation study, showing that it successfully recovered hidden Markov model parameters and hidden states. Parameters were less well recovered when we included a smooth pursuit state and/or added even small noise to simulated data. We applied generative models with different numbers of events to benchmark data. Comparing them indicated that hidden Markov models with more events than expected had most likely generated the data. We also applied the full algorithm to benchmark data and assessed its similarity to human coding and other algorithms. For static stimuli, gazeHMM showed high similarity and outperformed other algorithms in this regard. For dynamic stimuli, gazeHMM tended to rapidly switch between fixations and smooth pursuits but still displayed higher similarity than most other algorithms. Concluding that gazeHMM can be used in practice, we recommend parsing smooth pursuits only for exploratory purposes. Future hidden Markov model algorithms could use covariates to better capture eye movement processes and explicitly model event durations to classify smooth pursuits more accurately

Limited scope for group coordination in stylistic variations of kolam art

In large, complex societies, assorting with others with similar social norms or behaviors can facilitate successful coordination and cooperation. The ability to recognize others with shared norms or behaviors is thus assumed to be under selection. As a medium of communication, human art might reflect fitness-relevant information on shared norms and behaviors of other individuals thus facilitating successful coordination and cooperation.Distinctive styles or patterns of artistic design could signify migration history, different groups with a shared interaction history due to spatial proximity, as well as individual-level expertise and preferences. In addition, cultural boundaries may be even more pronounced in a highly diverse and socially stratified society. In the current study, we focus on a large corpus of an artistic tradition called kolam that is produced by women from Tamil Nadu in South India (N = 3,139 kolam drawings from 192 women) to test whether stylistic variations in art can be mapped onto caste boundaries, migration and neighborhoods. Since the kolam art system with its sequential drawing decisions can be described by a Markov process, we characterize variation in styles of art due to different facets of an artist's identity and the group affiliations, via hierarchical Bayesian statistical models.Our results reveal that stylistic variations in kolam art only weakly map onto caste boundaries, neighborhoods, and regional origin. In fact, stylistic variations or patterns in art are dominated by artist-level variation and artist expertise. Our results illustrate that although art can be a medium of communication, it is not necessarily marked by group affiliation. Rather, artistic behaviour in this context seems to be primarily a behavioral domain within which individuals carve out a unique niche for themselves to differentiate themselves from others. Our findings inform discussions on the evolutionary role of art for group coordination by encouraging researchers to use systematic methods to measure the mapping between specific objects or styles onto groups

Hidden Markov Models of Evidence Accumulation in Speeded Decision Tasks

Speeded decision tasks are usually modeled within the evidence accumulation framework, enabling inferences on latent cognitive parameters, and capturing dependencies between the observed response times and accuracy. An example is the speed-accuracy trade-off, where people sacrifice speed for accuracy (or vice versa). Different views on this phenomenon lead to the idea that participants may not be able to control this trade-off on a continuum, but rather switch between distinct states (Dutilh, et al., 2010).Hidden Markov models are used to account for switching between distinct states. However, combining evidence accumulation models with a hidden Markov structure is a challenging problem, as evidence accumulation models typically come with identification and computational issues that make them challenging on their own. Thus, hidden Markov models have not used the evidence accumulation framework, giving up on the inference on the latent cognitive parameters, or capturing potential dependencies between response times and accuracy within the states.This article presents a model that uses an evidence accumulation model as part of a hidden Markov structure. This model is considered as a proof of principle that evidence accumulation models can be combined with Markov switching models. As such, the article considers a very simple case of a simplified Linear Ballistic Accumulation. An extensive simulation study was conducted to validate the model's implementation according to principles of robust Bayesian workflow. Example reanalysis of data from Dutilh, et al. (2010) demonstrates the application of the new model. The article concludes with limitations and future extensions or alternatives to the model and its application

A Consensus-Based Transparency Checklist

We present a consensus-based checklist to improve and document the transparency of research reports in social and behavioural research. An accompanying online application allows users to complete the form and generate a report that they can submit with their manuscript or post to a public repository

Author Correction: A consensus-based transparency checklist.

An amendment to this paper has been published and can be accessed via a link at the top of the paper