Beyond simple laboratory studies: Developing sophisticated models to study rich behavior

Maselli, Antonella; Gordon, Jeremy; Eluchans, Mattia; Lancia, Gian Luca; Thiery, Thomas; Moretti, Riccardo; Cisek, Paul; Pezzulo, Giovanni

doi:10.1016/j.plrev.2023.07.006

Cited by 26 publications

(6 citation statements)

References 208 publications

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“…More fundamentally, our study exemplifies how real-world tasks can be translated into controlled experimental paradigms, providing a new kind of testbed for theories and models developed in basic science using distilled tasks [60,61]. We believe such cross-pollination between fundamental cognitive science and real-world behavior will both enrich theoretical developments and enable new applications.…”

Section: Discussionmentioning

confidence: 70%

Should I Stay or Should I Go? Cognitive Modeling of Left-Turn Gap Acceptance Decisions in Human Drivers

2022

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Objective We aim to bridge the gap between naturalistic studies of driver behavior and modern cognitive and neuroscientific accounts of decision making by modeling the cognitive processes underlying left-turn gap acceptance by human drivers. Background Understanding decisions of human drivers is essential for the development of safe and efficient transportation systems. Current models of decision making in drivers provide little insight into the underlying cognitive processes. On the other hand, laboratory studies of abstract, highly controlled tasks point towards noisy evidence accumulation as a key mechanism governing decision making. However, it is unclear whether the cognitive processes implicated in these tasks are as paramount to decisions that are ingrained in more complex behaviors, such as driving. Results The drivers’ probability of accepting the available gap increased with the size of the gap; importantly, response time increased with time gap but not distance gap. The generalized drift-diffusion model explained the observed decision outcomes and response time distributions, as well as substantial individual differences in those. Through cross-validation, we demonstrate that the model not only explains the data, but also generalizes to out-of-sample conditions. Conclusion Our results suggest that dynamic evidence accumulation is an essential mechanism underlying left-turn gap acceptance decisions in human drivers, and exemplify how simple cognitive process models can help to understand human behavior in complex real-world tasks. Application Potential applications of our results include real-time prediction of human behavior by automated vehicles and simulating realistic human-like behaviors in virtual environments for automated vehicles.

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Section: Discussionmentioning

confidence: 70%

Should I Stay or Should I Go? Cognitive Modeling of Left-Turn Gap Acceptance Decisions in Human Drivers

2022

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“…Therefore, here more than anywhere, cognition must adhere to the less-is-more principle, while also having a body in action with which to do it. Second, research in sport also has the unique strength that it has made significant progress in understanding subjects in action, because these are de facto components of the research object (Maselli et al, 2023). Other research may have failed to identify off-loading and constraining, because its research relies on synthetic laboratory situations without a body in action to constrain or off-load.…”

Section: How Lime Advances Our Understanding Of Ecological Rationalitymentioning

confidence: 99%

Less-is-More and Embodiment – How the Body Simplifies Cognition

Friedrich,

Grove,

Iskra

et al. 2024

Preprint

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Less-is-more describes a principle underlying decision making. Embodiment, on the other hand, argues that the body plays an important role in processes that have classically been characterized as mental. We argue that decision making is facilitated by reducing the amount of mental computation (less-is-more) through the exploitation of the constant stream of rich sensorimotor information (embodiment), a concept we call LIME. LIME argues that, via embodiment, computation is ‘constrained’ by and ‘off-loaded’ into the body. Constraining involves the body reducing the input or generated options before they enter into mental computation. Off-loading involves the body or the environment performing the computation. LIME underlies cognition generally, but is most accessibly demonstrated in sport phenomena, and we use this domain to sketch out the breadth of this concept in four case studies. LIME connects first principles of cognition to real life phenomena, providing a mechanics to ecological rationality and naturalistic behavior.

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“…Historically, motor learning studies that zero in on natural behaviors have been sparse, often leaving a gap in our under-standing of adaptations in real-world settings instead of controlled lab environments 21 . In response, our study, aligning with the emerging trend of naturalistic experiments in motor learning and neuroscience 22 , aims to bridge this gap. We introduce a novel bimanual maze task that closely simulates real-world activities to deepen our understanding of how individuals learn and adapt to complex bimanual tasks.…”

Section: Introductionmentioning

confidence: 95%

Exploring Motor Skill Acquisition in Bimanual Coordination: Insights from Navigating a Novel Maze Task

Cienfuegos,

Maycock,

Naceri

et al. 2024

Preprint

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In this study, we introduce a novel maze task designed to investigate naturalistic motor learning in bimanual coordination. We developed and validated an extended set of movement primitives tailored to capture the full spectrum of scenarios encountered in a maze game. Over a three-day training period, we evaluated participants' performance using these primitives and a custom-developed software, enabling precise quantification of performance. Our methodology integrated the primitives with in-depth kinematic analyses and thorough thumb pressure assessments, charting the trajectory of participants' progression from novice to proficient stages. Results demonstrated consistent improvement in maze performance and significant adaptive changes in joint behaviors and strategic recalibrations in thumb pressure distribution. These findings highlight the central nervous system's adaptability in orchestrating sophisticated motor strategies and the crucial role of tactile feedback in precision tasks. The maze platform and setup emerge as a valuable foundation for future experiments, providing a tool for the exploration of motor learning and coordination dynamics. This research underscores the complexity of bimanual motor learning in naturalistic environments, enhancing our understanding of skill acquisition and task efficiency while emphasizing the necessity for further exploration and deeper investigation into these adaptive mechanisms.

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Beyond simple laboratory studies: Developing sophisticated models to study rich behavior

Cited by 26 publications

References 208 publications

Should I Stay or Should I Go? Cognitive Modeling of Left-Turn Gap Acceptance Decisions in Human Drivers

Should I Stay or Should I Go? Cognitive Modeling of Left-Turn Gap Acceptance Decisions in Human Drivers

Less-is-More and Embodiment – How the Body Simplifies Cognition

Exploring Motor Skill Acquisition in Bimanual Coordination: Insights from Navigating a Novel Maze Task

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