Identifying the signature of prospective motor control in children with autism
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Identifying the signature of prospective motor control in children with autism. / Cavallo, Andrea; Romeo, Luca; Ansuini, Caterina; Battaglia, Francesca; Nobili, Lino; Pontil, Massimiliano; Panzeri, Stefano; Becchio, Cristina.
In: SCI REP-UK, Vol. 11, No. 1, 3165, 04.02.2021.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - Identifying the signature of prospective motor control in children with autism
AU - Cavallo, Andrea
AU - Romeo, Luca
AU - Ansuini, Caterina
AU - Battaglia, Francesca
AU - Nobili, Lino
AU - Pontil, Massimiliano
AU - Panzeri, Stefano
AU - Becchio, Cristina
PY - 2021/2/4
Y1 - 2021/2/4
N2 - Failure to develop prospective motor control has been proposed to be a core phenotypic marker of autism spectrum disorders (ASD). However, whether genuine differences in prospective motor control permit discriminating between ASD and non-ASD profiles over and above individual differences in motor output remains unclear. Here, we combined high precision measures of hand movement kinematics and rigorous machine learning analyses to determine the true power of prospective movement data to differentiate children with autism and typically developing children. Our results show that while movement is unique to each individual, variations in the kinematic patterning of sequential grasping movements genuinely differentiate children with autism from typically developing children. These findings provide quantitative evidence for a prospective motor control impairment in autism and indicate the potential to draw inferences about autism on the basis of movement kinematics.
AB - Failure to develop prospective motor control has been proposed to be a core phenotypic marker of autism spectrum disorders (ASD). However, whether genuine differences in prospective motor control permit discriminating between ASD and non-ASD profiles over and above individual differences in motor output remains unclear. Here, we combined high precision measures of hand movement kinematics and rigorous machine learning analyses to determine the true power of prospective movement data to differentiate children with autism and typically developing children. Our results show that while movement is unique to each individual, variations in the kinematic patterning of sequential grasping movements genuinely differentiate children with autism from typically developing children. These findings provide quantitative evidence for a prospective motor control impairment in autism and indicate the potential to draw inferences about autism on the basis of movement kinematics.
U2 - 10.1038/s41598-021-82374-2
DO - 10.1038/s41598-021-82374-2
M3 - SCORING: Journal article
C2 - 33542311
VL - 11
JO - SCI REP-UK
JF - SCI REP-UK
SN - 2045-2322
IS - 1
M1 - 3165
ER -