Dynamic scene processing in humans

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When someone crosses the street at a busy intersection this person has to simultaneously process a multitude of elements, many of which are dynamic. The person must be able to perceive when the cars are moving in a collision path and must be able to avoid pedestrians in the crowd. Many of these events are happening simultaneously. The person must process all of this information, make decisions about what is happening around and subsequently physically respond in a congruent fashion to avoid a catastrophic outcome. A similar analogy can be made for sports where situations can sometimes be even more demanding then the above example. Regardless of how critical these activities may be in our daily lives, we still know relatively little about how we process this type of information, as it is inherently complex. The program I propose for my NSERC discovery grant is to build a better understanding of how we process dynamic scenes and how conditions may affect this processing. The short-term objectives of my research program are: 1) To determine the fundamental role of stereoscopy on dynamic scene processing. 2) To determine the impact of increased physiological (i.e. fatigue) load on the learning functions for dynamic scene processing. 3) To determine the impact of increased motor load on the learning functions for dynamic scene processing. 4) To determine what are the distinguishing factors between elite-performance populations, such as professional, high-level amateur athletes, and non-athletic subjects for perceptual-cognitive learning and transfer. 5) To assess the changes in brain activity as a function of training on these tasks with EEG measures. Long-term objectives are: 1) Build a better understanding of the different elements used for processing socially relevant complex dynamic scenes such as pedestrian-crowd movements or sports activities. 2) Establish whether training programs using isolated dynamics such as 3D-MOT are superior to other types of learning such as video gaming training for processing dynamic complex scenes. 3) Establish the extent of transferability from training programs to more general abilities related to daily-activities. 4) Compare different elite-performance populations to determine whether the differences seen in elite-athletes learning can also be observed for other populations such as air force pilots, professional drivers or anyone that has to make rapid decisions with information coming from multiple simultaneous sources in an attempt to assess whether the fundamental mechanisms involved in expertise-related demands are common across a broader spectrum of human activities 5) Develop knowledge that will also lead to new and improved methodologies and licensing with a variety of partners to allow further job opportunities to our HQP within and outside of academia. The projects proposed are feasible and a direct continuation with my previous NSERC-funded research. This program has been very successful in producing HQP training and it is anticipated to continue to be successful in this regard.