Predictive simulations of postural control: exploring the role of signal noise and neural delays in Parkinson’s disease

Postural instability is one of the key motor symptoms of Parkinson’s disease (PD), which worsens with disease progression, leading to an increased fall risk. The complex internal processes of postural control and the elements causing this instability due to PD are still not fully understood. Predictive neuromusculoskeletal simulations can help to gain insights into internal postural control processes and their correlations, which cannot be measured directly. In this paper, we investigated the influence of increased motor signal noise and neural delays on the postural control of quiet upright standing and the resulting sway parameters using a previously published postural control model following assumptions that higher signal noise and neural delays lead to postural impairments in PD. Simulation results were compared to experimental motion capture data from 31 individuals with PD and 31 age- and sex-matched healthy control participants. We found that both higher signal noise and increased neural delays led to an adapted postural control behavior that can be associated with PD. The variations in sway parameters showed high agreement with the previously measured experimental data and the differences between individuals with and without PD. However, further investigation into additional movement tasks is necessary to strengthen these findings.