Interstride Variation in EEG Power Spectra of Younger and Older Adults Walking at a Range of Gait Speeds.

Interstride variability in theta power decreased with faster walking speeds in posterior parietal cortex.

• Participants walked at speeds ranging from 0.25 to 1.0 m/s on a treadmill while EEG was recorded.
• Theta power (4-8 Hz) interstride variability showed a significant speed-dependent reduction specifically in posterior parietal cortex.
• This effect was not observed in sensorimotor cortex for theta power.
• The finding suggests faster walking speeds are associated with more consistent posterior parietal theta activity.

Interstride variability in alpha and beta power decreased with faster walking speeds in both sensorimotor and posterior parietal cortex.

• Alpha (8-13 Hz) and beta (13-30 Hz) power variability showed speed-dependent reductions across both cortical regions of interest.
• Walking speeds ranged from 0.25 to 1.0 m/s.
• Both sensorimotor cortex and posterior parietal cortex were examined for their roles in motor action and sensory processing.
• The pattern was consistent with the hypothesis that faster walking is associated with greater gait automaticity.

Older adults had less interstride EEG variability than younger adults, primarily in alpha and beta frequency bands.

• Contrary to the hypothesis that older adults would show more interstride variability due to reduced gait automaticity, older adults exhibited less variability.
• The age-related difference was most prominent in alpha and beta power, not theta.
• Both younger and older adults were recruited and walked across the same range of gait speeds (0.25–1.0 m/s).
• The authors interpret this as suggesting that older adults' reduced automaticity of gait may be unrelated to electrical brain activity variability.

Broadband increases in interstride phase alignment of electrocortical activity were observed across the gait cycle.

• Interstride phasic alignment of electrocortical activity was analyzed across the full gait cycle.
• Phase alignment increased across a broad frequency range during walking.
• This finding indicates that EEG signals are rhythmically entrained to the gait cycle in a consistent manner across strides.

Older higher-functioning adults had greater interstride phase alignment in gamma frequency (30–50 Hz) than younger adults in parietal cortex.

• Gamma band (30–50 Hz) phase alignment was specifically elevated in older higher-functioning adults compared to younger adults.
• This effect was localized to parietal cortex.
• The distinction was made between higher- and lower-functioning older adults, suggesting functional status moderates the neural walking signature.
• This finding contrasts with the reduced alpha and beta variability seen in older adults overall.

The study design involved recruiting both younger and older adults to walk at a range of speeds (0.25–1.0 m/s) while EEG was recorded, focusing on sensorimotor and posterior parietal cortices.

• EEG was used to measure brain activity during walking to quantify interstride variability.
• The regions of interest were sensorimotor cortex (motor action) and posterior parietal cortex (sensory processing).
• Theta, alpha, and beta power interstride variability were the primary neural outcome measures.
• Interstride phase alignment was also computed as an additional neural measure across the gait cycle.

The authors hypothesized that EEG power variability would decrease at faster walking speeds and that older adults would show greater variability than younger adults, but only the speed hypothesis was confirmed.

• The speed hypothesis (variability decreases at faster speeds) was confirmed for theta in posterior parietal cortex and for alpha and beta in both regions.
• The age hypothesis (older adults show more variability due to reduced automaticity) was not confirmed; older adults showed less variability.
• These results suggest that the automaticity of gait is greater at faster walking speeds.
• The authors conclude that older adults' reduced automaticity of gait 'may be unrelated to electrical brain activity.'