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Updated: Sep 24, 2025

A Rat Model of Central Fatigue Using a Modified Multiple Platform Method
Published on: August 14, 2018
The effects of mental fatigue on effort allocation: Modeling and estimation
Zhide Wang1, Yanling Chang2, Brandon J Schmeichel3
1Department of Industrial and Systems Engineering.
Abstract:
Mental fatigue is usually accompanied by drops in task performance and reduced willingness for further exertion. A value-based theoretical account may help to explain such negative effects. In this view, mental fatigue influences perceived costs and rewards of exerting effort. However, no formal mathematical framework has yet been proposed to model and quantitatively estimate the effects of mental fatigue on subjective evaluations of effort expenditure, under possibly imperfect self-perceptions of internal fatigue states. We proposed a mathematical framework to model human cognitive effort allocations, assuming mental fatigue states are partially observable with semi-Markov dynamics. We modeled effort allocation decisions as a means to the goal of maximizing cumulative subjective values over a given time horizon. We developed an estimation method to identify subjective values and the hidden dynamics of mental fatigue, which can in future work be applied to self-reports, psychophysiological indices, and behavioral outcomes associated with fatigue. The modeling and estimation method was tested using a simulated n-back task under a free-choice paradigm, with model parameters fine-tuned from past studies. The proposed approach was able to recapitulate task performance and task engagement patterns observed under mental fatigue. This work advances a reward/cost trade-off account for explaining the exertion of mental effort and suggests new avenues for both theoretically and empirically relevant understandings of how cognitive operations are affected by mental fatigue. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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