Falls are the leading cause of fatal and nonfatal injuries in older adults (age ? 65), yielding extremely high injury rates & severity. Older adults experience significant declines in cognitive function (esp. executive function) that affect their motor performance and contribute to increased fall risk. This study will determine how differences in functional capacity (strength), functional walking ability, and particularly executive function (EF) affect the mechanisms both young and older adults use to regulate their stepping behavior during complex walking tasks. In two separate experiments, we will use state-of-the-art virtual reality technologies to manipulate the cogni- tive demands of a walking task in both young and older adults. We will carefully measure both physical and cognitive function in our subjects. We will then directly and systematically manipulate the cognitive demands of the walking tasks by introducing targeted competing task goals subjects must try to accomplish. This design will allow us, for the first time, to very carefully and precisely directly relate age-related changes/differences in sub- jects' underlying physical and cognitive ability to differences in their performance on the walking tasks. Specifically, we will quantify how these adults regulate ?Goal-Relevant? stepping errors with respect to differ- ent specified goals of the walking task.
In Aim 1, we will determine how young and older healthy adults adapt their stepping strategies in the presence of spatial risk. Here, we will introduce a penalty and reward landscape to the treadmill space. Higher rewards (i.e. points) will be available closer to the penalty regions, creating conflict between increased spatial risk and increased reward.
In Aim 2, we will determine how healthy and fall-prone older adults modify their stepping strategies to accommodate changing task goals that directly mimic real-world situations. These changing task goals will oblige older adults to make real-time cognitive decisions about where to step that have conflicting risks and rewards.
In Aim 3, we will use data collected in the experiments of Aims 1 & 2 to determine how young and older healthy adults adapt their stride-to-stride anterior-posterior ground reaction forces to achieve the stepping strategies elicited. We hypothesize humans will actively exploit redun- dancies in the Force Impulse-Momentum Principle at each individual stride. Across all 3 Specific Aims, we will quantify how differences in physical and cognitive function directly affect the flexibility with which young and older adults can alter how they regulate their stepping movements from each step to the next. This R21 proposal is (scientifically) 'high risk' as it will be the first to systematically tie specific aspects of human decision making (executive function: EF) directly to the biomechanical outcomes of goal-directed move- ment (walking). This work will also uniquely identify how age-related declines in EF alter these strategies. How- ever, if successful, this work has great potential to be `high reward' because it will establish direct causal links between EF capacity and the control/regulation of walking movements that can be exploited to design evidence- based interventions to reduce fall risk in the elderly and/or other at-risk populations.
Falls, and the injuries that result from falls, are a major health care problem for millions of elderly and thousands of other patients with specific locomotor impairments. Determining how elderly individuals adapt their stepping movements when negotiating real-world-like situations that directly challenge their balance control and will significantly enhance and extend the lives of these individuals. The proposed work will apply novel state-of-the- art experimental and analytical / computational / cognitive approaches to directly address these critical issues.
