Characterization of Noise Signatures of Involuntary Head Motion in the Autism Brain Imaging Data Exchange Repository

Abstract

The variability inherently present in biophysical data is partly contributed by disparate sampling resolutions across instrumentations. This poses a potential problem for statistical inference using pooled data in open access repositories. Such repositories combine data collected from multiple research sites using variable sampling resolutions. One example is the Autism Brain Imaging Data Exchange repository containing thousands of imaging and demographic records from participants in the spectrum of autism and age-matched neurotypical controls. Further, statistical analyses of groups from different diagnoses and demographics may be challenging, owing to the disparate number of participants across different clinical subgroups. In this paper, we examine the noise signatures of head motion data extracted from resting state fMRI data harnessed under different sampling resolutions. We characterize the quality of the noise in the variability of the raw linear and angular speeds for different clinical phenotypes in relation to age-matched controls. Further, we use bootstrapping methods to ensure compatible group sizes for statistical comparison and report the ranges of physical involuntary head excursions of these groups. We conclude that different sampling rates do affect the quality of noise in the variability of head motion data and, consequently, the type of random process appropriate to characterize the time series data. Further, given a qualitative range of noise, from pink to brown noise, it is possible to characterize different clinical subtypes and distinguish them in relation to ranges of neurotypical controls. These results may be of relevance to the pre-processing stages of the pipeline of analyses of resting state fMRI data, whereby head motion enters the criteria to clean imaging data from motion artifacts.

Aging with Autism Departs Greatly from Typical Aging

“…Across all sites of ABIDE, informed consent was obtained from all participants and/or their legal guardians. The following method have been published previously in various papers [16][17][18], but we provide them here as well to facilitate the flow of the paper. All datasets included in this study are from the Autism Brain Imaging Data Exchange (ABIDE) databases: ABIDE I (http://fcon_1000.projects.nitrc.org/indi/abide/abide_I.html) and ABIDE II (http://fcon_1000.projects.nitrc.org/indi/abide/abide_II.html).…”

“…the model also proposes that studying autism across these levels may help us stratify the heterogeneity of autism across aging. Over years of peer reviewed work, using this model has served to reveal several stochastic features of voluntary [2,14], spontaneous [15], involuntary [15][16][17][18] and autonomic [19,20] motions, offering classification power in autism and other neuropsychiatric and neurological conditions (e.g., schizophrenia [21], Parkinson's disease [22][23][24][25], neuropathies [26] and impairments of the nervous systems due to traumatic brain injury inducing coma [27] or stroke [28]). [29], with permission from Elsevier).…”

Hidden Aspects of the Research-ADOS are Bound to Affect Autism Science

“…The ADOS score data from ABIBE were divided into the male and female participants to ascertain (1) if the distributions of the total and sub-scores were symmetric (test for normality) and (2) if they had statistically different overall scores comprising social, communication and stereotypical, repetitive motions that could distinguish the two phenotypes. The motivation for this comparison emerged from physiological (somatic-sensory-motor) metrics that can automatically distinguish males from females of the ABIDE repository [40; 41] and from distinction based on motor patterns derived from natural voluntary behaviors [26; 51]. These patterns can also automatically separate females/males with ASD from females/males with AS (from the subset of ABIDE with a DSM-IV classification) [41].…”

“…The results from the analyses revealed that the research-grade ADOS scores reported by researchers in ABIDE generate non-normal distributions that change shape and (scale) dispersion for the total score and across all the sub-scores, for each of the ADOS-G and ADOS-2 tests. The scores confound males and females (unlike the ABIDE physiological data from the exact same participants, which distinguishes males vs. females and ASD vs. AS [5; 40; 41]). More alarmingly, the ADOS-G and ADOS-2 revealed fundamentally different diagnoses for AS individuals under DSM-IV criteria.…”

“…We present the distribution of participants in Figure 3 comprising clinical records from ABIDE I and II. Preliminary results from this work involving involuntary head motions during resting state in fMRI studies were published elsewhere [5; 40; 41]. Here we focus on the nature of the distributions of the ADOS scores, assumed to be symmetric by the ADOS manual and by reliability-validity tests commonly used in clinical Psychology to validate this diagnostic tool driving basic scientific research, e.g.…”