Abstract
The field of enhancing skill acquisition, particularly in professions necessitating the mastery of a complex combination of physical and mental abilities, is rapidly progressing and amenable to novel training protocols involving both neuroimaging and neurostimulation. Aircraft piloting in particular is an ideal medium for testing new training protocols, because objective performance measures are well-understood and modern flight simulator programs are realistic and high-fidelity. Here, we describe the development of a flight simulator protocol that allows for the analysis of neurostimulation-enhanced skill acquisition both within and between subjects. A three-block design was created to collect data pre-training, during feedback training, and post-training while being recorded in an fMRI. The dual task consists of 30–45 s trials landing a plane on one of two runways, indicated by an arrow displayed on the simulator screen, while simultaneously responding to auditory stimuli played constantly during each trial with button presses. The landing task is presented at two difficulty levels in pseudorandom balanced order, modulated by wind speed and direction. Two auditory conditions, response and control (no response), are used for a two by two design. For the feedback training, subjects are provided with relevant measures of how well they are able to land on the specified runway as well as their accuracy in the auditory task. Subjects will be randomly assigned to tDCS stimulation or sham groups, with stim receiving 30 min of 1.5 mA high definition-tDCS to the right ventrolateral prefrontal cortex during the training block. Altogether, this novel combination of stimulation, neuroimaging, and dual-task training will allow for an in-depth, multi-factor analysis of cognitive workload, behavioral performance, neurostimulation effects, and learning of a complex mental and physical task.
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Mark, J., Ayaz, H., Callan, D. (2021). Developing a tDCS-Enhanced Dual-Task Flight Simulator for Evaluating Learning. In: Ayaz, H., Asgher, U. (eds) Advances in Neuroergonomics and Cognitive Engineering. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1201. Springer, Cham. https://doi.org/10.1007/978-3-030-51041-1_21
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