Title:
Neuroadaptive Training Approaches To Enhance Skill Acquisition in Flight Simulators
Speaker:
Jesse Mark, PhD Candidate
School of Biomedical Engineering, Science and Health Systems
Drexel University
Advisor:
Hasan Ayaz, PhD
Associate Professor
School of Biomedical Engineering, Science and Health systems
Drexel University
Details:
Traditional methods used to determine a person’s mastery in a skill both during and after learning usually measure their performance, but fail to assess their mental effort, which is a crucial complementary factor that reflects how hard the brain is working to meet task demands. Absent this knowledge, it is possible to rate vastly differing performers to be at the same level, even if one is highly skilled but distracted and the other is inexperienced and pushing their limits. This gap in proper appraisal can be filled in by task-related central nervous system activity via neurophysiological measures. With a holistic, integrated estimation of the level of expertise, training can be optimized to a learner’s unique needs. Therefore, by utilizing neuroscientific principles and taking advantage of functional neuroimaging using a closed loop system, we can adapt training paradigms to individuals; this is called neuroadaptive training. The goal of neuroadaptive training is to increase the speed and effectiveness of learning by monitoring and modulating the trainee’s level of mental workload. Aviation is a domain ideal for testing neuroadaptive training as it is a complex task, requiring highly coordinated fine motor control, perceptual and cognitive processing, as well as focused practice to achieve high proficiency.
To acquire objective measures of task-related mental effort, neurophysiological monitoring modalities can be employed such as functional near-infrared spectroscopy (fNIRS), electroencephalography (EEG), and functional magnetic resonance imaging (fMRI). These are non-invasive in both a physical sense—able to record from the brain and body with sensors temporarily placed externally with no lasting effects—and a psychological sense, as they are minimally intrusive and do not interfere with task performance. fMRI can provide high spatial resolution, full brain imaging, that offers precise and localized visualizations of neuronal activation. fNIRS and EEG are wearable, and potentially wireless and mobile, uniquely suiting them for monitoring brain activity in ecologically valid environments. Moreover, transcranial direct current stimulation (tDCS) is a non-invasive, wearable, lightweight and portable, yet highly effective, neuromodulation modality. These mobile neuroimaging and neurostimulation systems can be taken outside of the lab into the field, consistent with the neuroergonomic approach.
This dissertation aims to develop novel neuroadaptive training using scalable wearable neuroimaging (fNIRS, EEG) and neurostimulation (tDCS). First, we validate the brain and body correlates of mental workload using a highly multimodal neurophysiological imaging suite on six foundational cognitive domains involved in flight including attention and working memory. Next, we develop a new passive neuroadaptive training protocol melding both neuroimaging and performance measures to accelerate skill acquisition in a flight simulator. Finally, we tested an active neuroadaptive training approach to enhance skill development in a simulator using electrical neurostimulation and concurrent neuroimaging. These new neuroadaptive training methods integrating neuroimaging and neurostimulation can optimize the learning of complex skills to each individual’s unique needs, and set the foundation to be expanded and assessed for efficacy in diverse fields in the future.