Interactive rhythmic auditory stimulation reinstates natural 1/f timing in gait of Parkinson's patients

Abstract

Parkinson's disease (PD) and basal ganglia dysfunction impair movement timing, which leads to gait instability and falls. Parkinsonian gait consists of random, disconnected stride times--rather than the 1/f structure observed in healthy gait--and this randomness of stride times (low fractal scaling) predicts falling. Walking with fixed-tempo Rhythmic Auditory Stimulation (RAS) can improve many aspects of gait timing; however, it lowers fractal scaling (away from healthy 1/f structure) and requires attention. Here we show that interactive rhythmic auditory stimulation reestablishes healthy gait dynamics in PD patients. In the experiment, PD patients and healthy participants walked with a) no auditory stimulation, b) fixed-tempo RAS, and c) interactive rhythmic auditory stimulation. The interactive system used foot sensors and nonlinear oscillators to track and mutually entrain with the human's step timing. Patients consistently synchronized with the interactive system, their fractal scaling returned to levels of healthy participants, and their gait felt more stable to them. Patients and healthy participants rarely synchronized with fixed-tempo RAS, and when they did synchronize their fractal scaling declined from healthy 1/f levels. Five minutes after removing the interactive rhythmic stimulation, the PD patients' gait retained high fractal scaling, suggesting that the interaction stabilized the internal rhythm generating system and reintegrated timing networks. The experiment demonstrates that complex interaction is important in the (re)emergence of 1/f structure in human behavior and that interactive rhythmic auditory stimulation is a promising therapeutic tool for improving gait of PD patients.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1. WalkMate overview.

A) Schematic depiction of the WalkMate system. B) The computer's timing system used nonlinear oscillators and was organized hierarchically in two modules. Module 1 mutually entrained the gait frequencies of the computer and the participant. Module 2 adjusted the relative phase difference between the computer's auditory onset and the participant's step contact to a target phase difference [more details in the Materials and Methods section].

Figure 2. Examples of two trials.

On the left, the stride times of one leg are plotted against trial time. On the right, the DFA technique plots the average fluctuation per box size. Using DFA, a scaling exponent α≈0.5 corresponds to rough and unpredictable white noise; α≈1.0 corresponds to 1/f-like noise and long-range correlations . The mean and SD of stride times are similar in both trials, but the fractal scaling differs considerably. During the Silent condition (A), the PD patient's strides are unpredictable and akin to white noise, whereas during interactive rhythmic stimulation (B), the stride fluctuations have a 1/f-like structure.

Figure 3. DFA fractal-scaling exponent results by condition.

A) Parkinson's patients during rhythmic treatment, B) healthy participants during rhythmic treatment, and C) Parkinson's patients carry-over effect during a silent trial five minutes after the rhythmic treatment. The cueing conditions are unassisted Silent Control; interactive WalkMate rhythmic auditory stimulation; and Fixed-tempo rhythmic auditory stimulation (RAS). Error bars represent ± SEM. *p<.05; n.s. = non-significant.