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Elizabeth Torres; Signatures of motor output variability across a spectrum of neurological disorders reveal severity levels and unexpected ties. Journal of Vision 2015;15(12):641. doi: 10.1167/15.12.641.
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© ARVO (1962-2015); The Authors (2016-present)
In recent work we have uncovered minute fluctuations in the speed of pointing motions of individuals with Autism Spectrum Disorders (ASD) (Torres et al 2013, Wu et al 2014). During the movement segments towards a visual target, we detected in their hand motions excess fluctuations absent in typical controls. The human eye has limited capacity to detect these types of fluctuations at millisecond time scales during intentional movements. Their frequencies also escape the observer diagnosing the disorder, so abnormal patterns of motor variations are not even considered a core issue when diagnosing or treating ASD. We have detected them with proper instrumentation and new analytics, thus taking a radically different approach to ASD and providing objective metrics to characterize the noise-to-signal patterns present in these motions as they naturally unfold during perceptual and decision-making tasks. Here we present additional metrics to characterize this subtle form of intentional tremor in ASD in relation to patients with different degrees off severity in Parkinson’s disease (PD), Essential Tremor (ET) and de-afferentation. The former two are disorders on a spectrum where tremor is visibly affecting the person. The third one is a specific loss of proprioception whereby the person can no longer sense kinesthetically the returning stream of movements intentionally produced. We characterize the similarities and the differences between individuals with ASD and these different subject types. The results from this work provide evidence that the fluctuations in the motor output variability that are often considered noise and discarded are in fact a rich signal useful to better understand, detect, subtype and track disorders on a broad spectrum.
Meeting abstract presented at VSS 2015
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