Using virtual reality-based neurocognitive testing and eye tracking to study naturalistic cognitive-motor performance.

Natural human behavior arises from continuous interactions between the cognitive and motor domains. However, assessments of cognitive abilities are typically conducted using pen and paper tests, i.e., in isolation from "real life" cognitive-motor behavior and in artificial contexts. In the current study, we aimed to assess cognitive-motor task performance in a more naturalistic setting while recording multiple motor and eye tracking signals. Specifically, we aimed to (i) delineate the contribution of cognitive and motor components to overall task performance and (ii) probe for a link between cognitive-motor performance and pupil size. To that end, we used a virtual reality (VR) adaptation of a well-established neurocognitive test for executive functions, the 'Color Trails Test' (CTT). The VR-CTT involves performing 3D reaching movements to follow a trail of numbered targets. To tease apart the cognitive and motor components of task performance, we included two additional conditions: a condition where participants only used their eyes to perform the CTT task (using an eye tracking device), incurring reduced motor demands, and a condition where participants manually tracked visually-cued targets without numbers on them, incurring reduced cognitive demands. Our results from a group of 30 older adults (>65) showed that reducing cognitive demands shortened completion times more extensively than reducing motor demands. Conditions with higher cognitive demands had longer target search time, as well as decreased movement execution velocity and head-hand coordination. We found larger pupil sizes in the more cognitively demanding conditions, and an inverse correlation between pupil size and completion times across individuals in all task conditions. Lastly, we found a possible link between VR-CTT performance measures and clinical signatures of participants (fallers versus non-fallers). In summary, performance and pupil parameters were mainly dependent on task cognitive load, while maintaining systematic interindividual differences. We suggest that this paradigm opens the possibility for more detailed profiling of individual cognitive-motor performance capabilities in older adults and other at-risk populations.

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