Faculty Mentor

Emil Iacob, PhD

Location

Russell Union Ballroom

If Other was choses above, please indicate your topic area here:

Psychology/ behavioral science

Type of Research

On-going

Session Format

Oral Presentation

College

College of Science & Mathematics

Department

Mathematical sciences.

Abstract

This research evaluates the theoretical foundations of recent embodied and enacted decision- making models(Baker., et al  2022) , specifically investigating whether "urgency" serves as a domain-general mechanism for reward-rate maximization. Across three experiments using a reward-performance contingency, we compare traditional decision-making frameworks with urgency-based theories to determine how participants navigate task demands and whether optimality assumptions hold (Reynaud, et al 2020). A primary focus involves testing whether motor excitability increases directly with evidence, or if "higher-level" deliberation occurs in parallel with se Using the Generalized Drift-Diffusion Model (GDDM) framework via PyDDM  (Shinn, et al 2020), we will assess participant preferences for urgency- based strategies. By critically re-examining long-held perspectives on optimality (Evans, et al 2018) and the necessity of optimal control in embodied cognition (Mangalam, 2025), this work contributes to the evolving discourse on how action and deliberation intertwine during choice.

References

Baker S-A, Griffith T, Lepora NF (2022) Degenerate boundaries for multiple-alternative decisions. Nat Commun 13:5066. https://doi.org/10.1038/s41467-022-32741-y Evans NJ, Bennett AJ, Brown SD (2019) Optimal or not; depends on the task. Psychon Bull Rev 26:1027–1034. https://doi.org/10.3758/s13423-018-1536-4 Mangalam M (2025) The myth of optimality in human movement science. Neuroscience & Biobehavioral Reviews 178:106352. https://doi.org/10.1016/j.neubiorev.2025.106352Reynaud AJ, Saleri Lunazzi C, Thura D (2020) Humans sacrifice decision-making for action execution when a demanding control of movement is required. Journal of Neurophysiology 124:497–509. https://doi.org/10.1152/jn.00220.2020 Shinn M, Lam NH, Murray JD (2020) A flexible framework for simulating and fitting generalized drift-diffusion models. eLife 9:e56938. https://doi.org/10.7554/eLife.56938 PyDDM - A generalized drift diffusion model simulator — PyDDM 0.9.0 documentation. https://pyddm.readthedocs.io/en/stable/. Accessed 11 Feb 2026

Program Description

.

DOI

10.20429/GS4.2026.030

Start Date

4-23-2026 2:15 PM

End Date

4-23-2026 2:30 PM

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Apr 23rd, 2:15 PM Apr 23rd, 2:30 PM

Assessing Decision Making Under Risk and Dynamic Task Environments in Humans

Russell Union Ballroom

This research evaluates the theoretical foundations of recent embodied and enacted decision- making models(Baker., et al  2022) , specifically investigating whether "urgency" serves as a domain-general mechanism for reward-rate maximization. Across three experiments using a reward-performance contingency, we compare traditional decision-making frameworks with urgency-based theories to determine how participants navigate task demands and whether optimality assumptions hold (Reynaud, et al 2020). A primary focus involves testing whether motor excitability increases directly with evidence, or if "higher-level" deliberation occurs in parallel with se Using the Generalized Drift-Diffusion Model (GDDM) framework via PyDDM  (Shinn, et al 2020), we will assess participant preferences for urgency- based strategies. By critically re-examining long-held perspectives on optimality (Evans, et al 2018) and the necessity of optimal control in embodied cognition (Mangalam, 2025), this work contributes to the evolving discourse on how action and deliberation intertwine during choice.

References

Baker S-A, Griffith T, Lepora NF (2022) Degenerate boundaries for multiple-alternative decisions. Nat Commun 13:5066. https://doi.org/10.1038/s41467-022-32741-y Evans NJ, Bennett AJ, Brown SD (2019) Optimal or not; depends on the task. Psychon Bull Rev 26:1027–1034. https://doi.org/10.3758/s13423-018-1536-4 Mangalam M (2025) The myth of optimality in human movement science. Neuroscience & Biobehavioral Reviews 178:106352. https://doi.org/10.1016/j.neubiorev.2025.106352Reynaud AJ, Saleri Lunazzi C, Thura D (2020) Humans sacrifice decision-making for action execution when a demanding control of movement is required. Journal of Neurophysiology 124:497–509. https://doi.org/10.1152/jn.00220.2020 Shinn M, Lam NH, Murray JD (2020) A flexible framework for simulating and fitting generalized drift-diffusion models. eLife 9:e56938. https://doi.org/10.7554/eLife.56938 PyDDM - A generalized drift diffusion model simulator — PyDDM 0.9.0 documentation. https://pyddm.readthedocs.io/en/stable/. Accessed 11 Feb 2026