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

Título :
Characterization of Noise Signatures of Involuntary Head Motion in the Autism Brain Imaging Data Exchange Repository
Autor :
Caballero, Carla  
Mistry, Sejal  
Vero, Joe
Torres, Elizabeth
Editor :
Frontiers
Departamento:
Departamentos de la UMH::Ciencias del Deporte
Fecha de publicación:
2018
URI :
https://hdl.handle.net/11000/34262
Resumen :
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 themin 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.
Palabras clave/Materias:
autism
Asperger’s
noise
stochastic process
head motion
resting-state fMRI
Área de conocimiento :
CDU: Bellas artes: Diversiones. Espectáculos. Cine. Teatro. Danza. Juegos.Deportes
Tipo de documento :
info:eu-repo/semantics/article
Derechos de acceso:
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
DOI :
https://doi.org/10.3389/fnint.2018.00007
Aparece en las colecciones:
Artículos Ciencias del Deporte



Creative Commons La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.