The effects of mental fatigue on effort allocation: Modeling and estimation

Area of Science:

• Cognitive Psychology
• Computational Neuroscience
• Decision Science

Background:

• Mental fatigue typically reduces task performance and motivation.
• Existing theories suggest fatigue impacts perceived effort costs and rewards.
• A formal mathematical model for fatigue's effect on effort allocation is lacking.

Purpose of the Study:

• To propose a mathematical framework for modeling cognitive effort allocation under mental fatigue.
• To develop an estimation method for subjective values and fatigue dynamics.
• To quantitatively assess the impact of imperfect self-perception of fatigue on effort decisions.

Main Methods:

• Developed a mathematical framework assuming partially observable mental fatigue states with semi-Markov dynamics.
• Modeled effort allocation as maximizing cumulative subjective values over a time horizon.
• Tested the framework using a simulated n-back task under a free-choice paradigm.

Main Results:

• The proposed model successfully recapitulated observed patterns of task performance and engagement under mental fatigue.
• The estimation method could identify subjective values and hidden fatigue dynamics.
• The framework provides a quantitative approach to understanding fatigue's influence on effort.

Conclusions:

• Advances a reward/cost trade-off account for mental effort exertion.
• Offers a novel computational approach to studying mental fatigue.
• Suggests new theoretical and empirical avenues for understanding cognitive operations affected by fatigue.