Fig 1.
Cortical and subcortical sensory motor loops involved in reactive balance control.
A) At low balance difficulty, reactive balance control is primarily mediated through subcortical sensorimotor circuits (red) at an earlier latency (λbs). B) At higher balance difficulty, cortical sensorimotor circuits (blue) contribute to the balance-correcting muscle activity at longer latency (λc).
Fig 2.
Electroencephalography (EEG) processing pipeline.
Raw EEG is preprocessed, non-neural artifacts are removed, and remaining brain components are further analyzed in electrode space to quantify perturbation evoked cortical N1 and sensorimotor β activity.
Fig 3.
Perturbation-evoked muscle activity increases as balance challenge increases.
A) Exemplar participant at all three perturbation magnitudes: small (light green), medium (green), and large (dark green). B) group averaged data for each time bin. *p<0.05.
Fig 4.
Single loop muscle sensorimotor response model (mSRM) A) mSRM schematic and reconstruction of exemplar participant data (Participant 02) at each perturbation magnitude. mSRM reconstructs balance-correcting muscle activity as the weighted sum of delayed center of mass kinematics. B) group mSRM parameters for CoM acceleration (ka1), velocity (kv1), and displacement (kd1) gains as well as time delay (λbs). *p<0.05.
Fig 5.
Double loop hierarchical sensorimotor response model (hSRM) A) hSRM schematic and reconstruction of exemplar participant data (Participant 02) at each perturbation magnitude. hSRM adds an additional, longer-latency, cortical feedback loop (blue lines) to the single-latency mSRM (red lines) B) group hSRM parameters for the cortical feedback loop CoM acceleration (ka2) and time delay (λc). *p<0.05.
Fig 6.
Perturbation-evoked cortical activity as balance challenge increases.
Exemplar participants at all three perturbation magnitudes: small (light green), medium (green), and large (dark green).
Fig 7.
Single loop cortical sensorimotor response model (cSRM) A) cSRM schematic and reconstruction of exemplar participant EEG data (Participant 02) at each perturbation magnitude. cSRM reconstructs either perturbation-evoked cortical N1 (plotted negative up) or sensorimotor β activity as the weighted sum of delayed CoM kinematics. B) group cSRM parameters for CoM acceleration feedback gain (ka1) and the associated time delay (τc). *p<0.05.
Fig 8.
Double loop hierarchical sensorimotor response model (hSRM) using recorded N1 as a predictor of muscle activity.
A) hSRM schematic and reconstruction of exemplar participant data (Participant 02) at each perturbation magnitude. hSRM adds an additional, longer-latency, cortical feedback loop (blue lines) to the single-latency mSRM (red lines) B) group hSRM parameters for the cortical feedback loop using N1 (kCz) as a predictor of muscle activity. *p<0.05.
Fig 9.
Double loop hierarchical sensorimotor response model (hSRM) using recorded β activity as a predictor of muscle activity.
A) hSRM schematic and reconstruction of exemplar participant data (Participant 02) at each perturbation magnitude. B) group hSRM parameters for the cortical feedback loop using β (kβ) as a predictor of muscle activity. *p<0.05.