Abstract

This study investigated the effect of task demand transitions at multiple levels of analysis including behavioral performance, subjective rating, and brain effective connectivity, while comparing human data to Adaptive Control of Thought-Rational (ACT-R) simulated data. Three stages of task demand were designed and performed sequentially (Low-High-Low) during AF-MATB tasks, and the differences in neural connectivity during workload transition were identified. The NASA Task Load Index (NASA-TLX) and the Instantaneous Self-Assessment (ISA) were used to measure the subjective mental workload that accompanies the hysteresis effect in the task demand transitions. The results found significant hysteresis effects on performance and various brain network measures such as outflow of the prefrontal cortex and connectivity magnitude. These findings would assist in clarifying the direction and strength of the Granger Causality under demand transitions. As a result, these findings involving the neural mechanisms of hysteresis effects in multitasking environments may be utilized in applications of neuroergonomics research. The ability to compare data derived from human participants to data gathered by the ACT-R model allows researchers to better account for hysteresis effects in neuro-cognitive models in the future.

Highlights

  • In society today, people are inundated with situations in which their cognitive capacity is tested by the need or want to perform well in multiple tasks all at once

  • This study investigated the effects of task demand transitions and the hysteresis effect that occurs at multiple levels of analysis

  • Mental workload ratings during the L3 condition are lower than the L1 condition which is consistent with previous findings (Hancock et al, 1995), even though the first and third trials were performed at an identical difficulty level

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Summary

Introduction

People are inundated with situations in which their cognitive capacity is tested by the need or want to perform well in multiple tasks all at once. A common example comes in the form of piloting an aircraft. A pilot is tasked with watching through windshield for obstructions, weather conditions, and runway conditions while monitoring airspeed, elevation, weather, fuel levels, and navigation information using monitoring equipment. Pilots must listen for auditory cues both from air traffic controllers as well as alarms such as ground proximity warnings. Pilots are often tasked with manually guiding the plane using a steering mechanism as well as controlling acceleration manually. The level of automation may change given the sophistication of the technology in individual airplanes, but within any flight system, multitasking is required of the pilot

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