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Grasping the world from a cockpit: investigating embodied neural mechanisms underlying human performance and ergonomics in aviation context

Mariateresa Sestito1*, Jeff Nador1, John Flach1 and Assaf Harel1
  • 1 Wright State University, United States

The current work introduces a novel neuroergonomic approach to the study of human factors in aviation, combining theoretical concepts from the field of ecological psychology with current neuroscientific research. In line with the original conception of neuroergonomics (Parasuraman and Wilson 2008), we suggest that knowledge of brain function and structure can be harnessed to optimize the way operators interact with or control dynamic systems, and specifically, the interactions between pilots, their aircraft and their environment. As such, a neuroergonomic approach has distinct advantages in an aviation context: it can be used to enhance the process of HMI design, it can provide implicit measures that objectively quantify the interaction between pilot and aircraft, and these in turn, can be ultimately utilized to guide training and enable expert performance (Harel, 2016). Human flight performance provides a rich example of how perception, action and cognition interact in complex yet relatively controlled ecologically-valid environments. As such, it offers a unique opportunity to investigate the real-world interaction between an agent and the environment (Gibson, 1979), hence providing key insights to understanding complex behavior. We suggest that a key neural correlate of this interactive process is the Mirror Neuron system (Rizzolatti and Craighero 2004). Mirror Neuron activity underlies motor simulation of the observed actions, and therefore can be used to assess experience and skills involved with task-relevant actions – like flying an airplane (Callan et al., 2012; 2013). As the Mirror Neuron system reflects the direct coupling between perception and action, the automatic and implicit nature of this neural substrate can be harnessed to improve human factors, design, and ergonomics (Sestito et al., under review). The potential areas of study and applications of our approach involve: (1) enhancing flight training by isolating specific agent-environment relations; (2) tracking training progression based on behavioral and brain signatures related to flight expertise; and (3) ecological inspired design of next generation human-machine interfaces in flight decks. We present preliminary neurophysiological data from an ongoing study that utilizes EEG as a measure of brain activity. We focus on Mu rhythm as an EEG marker of the Mirror Neuron system (Hobson and Bishop 2017). Mu rhythms are synchronized patterns of electrical activity involving large numbers of neurons in the part of the brain that controls voluntary movement. These patterns can be measured by EEG at a frequency of 8–13 Hz and observed over the motor cortex. Mu wave patterns are suppressed whenever a person performs a motor action (Kuhlman, 1978). Notably, the mu wave is also suppressed when one observes another person performing a motor action: for this reason, these neurophysiological responses are regarded as an EEG correlate of the Mirror Neuron System (Hobson and Bishop 2017). In this study, we aim to uncover the extent to which the Mu-suppression as an index for pilot’s experience with their surroundings. We investigate if there is a difference between pilots and novices in the sensorimotor activity (mu suppression) when asked to make simple judgments in a landing scenario. According to our suggested framework, brain activity will be modulated based on participants’ attunement (flight expertise) to a given environment (aerial view of a runaway), and the related task (landing an airplane). Sensorimotor activity manifested in pilots reflects the presence of specific motor chains at a brain level related to flight expertise – that is, the motor acts that typically a pilot executes in-flight on the flight controls (Iacoboni et al. 2005; Callan et al. 2012; 2013). The investigation of brain signatures of flight expertise is essential for developing novel flight training and instructional techniques. Such a neuroergonomic approach to training indeed, presents two main advantages: (1) it can provide an implicit measure of training progress, and (2) it can reveal what information is utilized by the trainee rather than assume in a top-down fashion what the trainee should know or is doing at a certain point in time. Moreover, this neuroergonomic approach can be utilized to optimally design Human-Machine Interfaces supporting training. Such a neuroscientifically-inspired design approach utilizes such action-perception mechanisms present at the neural level, to represent potential actions in the cockpit. This will prompt the pilot to the take the proper action in given circumstances, minimizing deviations from the target behavior – i.e. human error – hence ultimately improving flight safety.

References

Callan, D. E., Gamez, M., Cassel, D. B., Terzibas, C., Callan, A., Kawato, M., and Sato, M. A. 2012. Dynamic visuomotor transformation involved with remote flying of a plane utilizes the ‘Mirror Neuron’system. PloS one 7(4): e33873.
Callan, D. E., Terzibas, C., Cassel, D. B., Callan, A., Kawato, M., and Sato, M. A. 2013. Differential activation of brain regions involved with error-feedback and imitation based motor simulation when observing self and an expert's actions in pilots and non-pilots on a complex glider landing task. Neuroimage 72: 55-68.
Gibson, J.J. 1979. The ecological approach to visual perception. Boston: Houghton Mifflin.
Harel, A. 2016. What is special about expertise? Visual expertise reveals the interactive nature of real-world object recognition. Neuropsychologia 83: 88-99.
Hobson, H. M., and Bishop, D. V. 2017. The interpretation of mu suppression as an index of mirror neuron activity: past, present and future. Royal Society Open Science 4(3): 160662.
Iacoboni, M., Molnar-Szakacs, I., Gallese, V., Buccino, G., Mazziotta, J. C., and Rizzolatti, G. 2005. Grasping the intentions of others with one's own mirror neuron system. PLoS Biol 3(3): e79.
Kuhlman, W. N. 1978. Functional topography of the human mu rhythm. Electroencephalography and clinical neurophysiology 44(1) 83-93.
Parasuraman, R., and Wilson, G. F. 2008. Putting the brain to work: Neuroergonomics past, present, and future. Human Factors: The Journal of the Human Factors and Ergonomics Society 50(3) 468-474.
Rizzolatti, G., and Craighero, L. 2004. The mirror-neuron system. Annu. Rev. Neurosci. 27: 169-192.
Sestito M., Flach J., Harel A. (under review). Grasping the world from a cockpit: perspectives on embodied neural mechanisms underlying human performance and ergonomics in aviation context.

Keywords: affordances, Embodied Cognition, human performance, EEG, Flight expertise, mu rhythm suppression, Perception, Mirror Neurons

Conference: 2nd International Neuroergonomics Conference, Philadelphia, PA, United States, 27 Jun - 29 Jun, 2018.

Presentation Type: Oral Presentation

Topic: Neuroergonomics

Citation: Sestito M, Nador J, Flach J and Harel A (2019). Grasping the world from a cockpit: investigating embodied neural mechanisms underlying human performance and ergonomics in aviation context. Conference Abstract: 2nd International Neuroergonomics Conference. doi: 10.3389/conf.fnhum.2018.227.00033

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Received: 02 Apr 2018; Published Online: 27 Sep 2019.

* Correspondence: Dr. Mariateresa Sestito, Wright State University, Dayton, United States, m.sestito5869a@ordpsicologier.it