bioRxivNeurosciencePreprint
Environmental Demands Outweigh Age Effects in Cortical Dynamics During Walking
Danishta KauliD, Magda MustileiD, Mark DonoghueiD, Alexander E. I. BrownleeiD, Magdalena IetswaartiD, Gemma LearmonthiD
Abstract
Reduced visibility is a common contributor to falls in older adults, but the neural processes that support safe locomotion under low lighting are not well established. In this study, 22 young (mean age = 22.5) and 20 older (mean age = 70.9) adults walked along a pathway under bright, ambient and dark lighting conditions while stepping over expected and unexpected obstacles projected on the floor. Mobile electroencephalography (EEG), combined with motion capture, was used to quantify spectral power changes during obstacle crossing preparation and the post-crossing phases, relative to a standing baseline. We identified that reduced lighting conditions elicited a widespread increase in cortical engagement, predominantly in the alpha band, during both preparation and reset phases. Obstacle negotiation recruited a distributed sensorimotor network, with reduced theta-alpha-beta desynchronisation during preparation and a robust post-movement beta rebound during the post-crossing reset phase. Expectation effects were modest, with unexpected obstacles inducing greater transient alpha-beta desynchronisation relative to expected obstacles, suggesting additional cortical resources are recruited under uncertainty. Age effects were minimal and limited to reduced frontal alpha desynchronisation in older adults compared to young adults during the preparation phase, possibly reflecting differences in walking speed rather than differences in neural control. In conclusion, environmental features such as low lighting and obstacle presence exert a stronger influence on cortical dynamics during walking than age and expectation effects alone. This provides a foundation for future work examining how these processes may differ in older adults at increased risk of falls.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 0
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