Fractality of Tics as a Quantitative Assessment Tool for Diagnosis of Tourette Syndrome
Tics manifest as brief, purposeless, and involuntary movements or noises that can be suppressed temporarily with effort. In 1998, Peterson and Leckman (P&L) hypothesized that the chaotic temporal nature of tics could possess an inherent fractality, that is, have neighbor-to-neighbor correlation at all levels of time scale. However, demonstrating this phenomenon has eluded researchers for more than two decades, primarily because of the challenges associated with estimating the scale-invariant, power law exponent-called the fractal dimension Df-from a fractional Brownian noise. Here, we confirm P&L's hypothesis and establish the fractality of tics by examining year-long tic time series dataset of children diagnosed with Tourette syndrome using one-dimensional random walk models. We find that Df increases from ~1.4 to 1.75 in order of decreasing tic severity, and is correlated with the conventional YGTTS total tic score (TTS) clinical measure (p-value = 0.03). We demonstrate Df to be a sensitive parameter in examining the effect of several tic suppression conditions on the tic time series. Our findings pave the way for utilizing the fractal nature of tics as a quantitative tool for estimating tic severity and treatment effectiveness, as well as a marker for differentiating typical from functional tics.