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Area of Science:

  • Neuroscience
  • Biomechanics
  • Human Motor Control

Background:

  • Gait is typically automatic but requires cortical adaptation to environmental demands.
  • Electroencephalography (EEG) is suitable for studying cortical activity during real locomotion.
  • Gait initiation involves significant motor and cognitive cortical control.

Purpose of the Study:

  • To investigate cortical neural synchronization/desynchronization patterns during gait using EEG.
  • To analyze brain activity during challenging gait tasks (e.g., obstacle crossing, dual tasks).
  • To explore the role of different cortical areas, including prefrontal and parietal cortex, in gait control.

Main Methods:

  • Utilized electroencephalography (EEG) to record brain activity during locomotion.
  • Employed time-frequency analysis to examine induced changes in EEG activity across different frequency bands.
  • Compared spectral patterns during stabilized gait versus more demanding attentional tasks.

Main Results:

  • EEG analysis revealed changes in cortical neural synchronization/desynchronization during gait.
  • Specific spectral patterns correlated with gait context and task difficulty.
  • Demanding attentional tasks engaged cortical areas beyond the sensorimotor cortex, such as prefrontal and posterior parietal cortex.

Conclusions:

  • Cortical activity, particularly through EEG spectral patterns, reflects gait control mechanisms.
  • Non-sensorimotor cortical areas are significantly involved in complex gait adaptations.
  • Decoding EEG signals during gait is essential for developing brain-computer interfaces for artificial locomotion.