Psychology Brown Bag: Grasping the world from a cockpit: investigating embodied neural mechanisms underlying human performance in aviation context.

Dr. Mariateresa Sestito, Wright State University, Presentation title: Grasping the world from a cockpit: investigating embodied neural mechanisms underlying human performance in aviation context. 

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

Mariateresa Sestito, Jeff Nador, John Flach, Assaf Harel

ABSTRACT

In the current work, we present a neuroergonomic approach that combines insights from ecological psychology and embodied cognition with a neurophysiological framework to explain patterns of human performance across a variety of aviation contexts. The field of aviation provides a unique opportunity to investigate how perception, action and cognition interact in complex yet controlled ecologically valid environments. We suggest that the Mirror Neuron (MN) system (Rizzolatti and Craighero 2004) can be used as a neural correlate of the interaction between an agent and the environment (Gibson, 1969) and thus provide key insights to understanding complex behavior. MN 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). Further, reflecting the direct coupling between perception and action the MN system is automatic and implicit and thus 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. 

To illustrate the utility of our framework, I will present a recent study from our lab using an EEG measure of the MN system to quantify and assess flight expertise. Mu rhythms or sensorimotor 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 over the motor cortex. A person suppresses mu wave patterns when he or she performs a motor action. Moreover, the mu wave is 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 want to investigate if there is a difference between pilots and novices in the sensorimotor activity (mu suppression) when asked to make judgments in a landing scenario. According to the hypothesis, brain activity is expected to be modulated based on participants’ attunement (flight expertise) to a given environment (aerial view of a runaway), and the related task (landing an airplane).

BIO

Mariateresa Sestito received her Ph.D. in Neuroscience from the University of Parma Italy in 2014. She earned a MS in Neuropsychology and Rehabilitation in 2007, and became a board certified Psychologist in 2009. Mariateresa holds a Light Sport Airplanes certificate, and she is currently working toward getting her Private Pilot License in U.S.  

In previous research projects at the Department of Neuroscience Parma, Mariateresa studied the neurophysiological correlates of emotion perception and phenomenology in Schizophrenia. During her postdoc at the French National Center for Scientific Research (CNRS) in Lyon France, she investigated the neural mechanisms underlying decision making, motivation and reward processing in patients with neurological and psychiatric illnesses.

Mariateresa’s current postdoc at the Human Neuroscience and Visual Cognition Lab at Wright State is focused on aviation psychology. She is especially interested in the application of the embodied cognition approach to human performance and human-machine interface design.