Cortical Oscillations during Gait: Wouldn't Walking be so Automatic?

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.