Objective Measures of Imitation and Movement End-Point Re-Enactment in Autism

Background:

Imitation is a complex behavior required for social learning. Difficulties in imitating others have been well-documented within ASD populations, but have been largely based on subjective reporting. We developed an approach obtaining objective measures through the use of a computerised kinematics assessment tool (CKAT) which made it possible to compare for imitation for separate measures and also with an alternative form of social learning: movement end-point re-enactment (MER).

Objectives:  

Using objective measures, we aimed to determine whether an imitative deficit was present in ASD adolescents when compared to typically developing peers, and  if such a deficit existed, whether this was specific to imitation of temporal or spatial aspects of the action, and to bodily imitation only or MER also.

Methods:

Stimuli consisted of two sets – action imitation (AI), showing an actor drawing the same shapes on a touch-screen laptop; and MER, showing a dot ‘drawing’ shapes across the laptop screen.  Participants were instructed to reproduce the movements that they had watched by drawing with a stylus on a touch-screen laptop as if using pen-and-paper.  Drawing conditions were: 3 shapes (circle, square, triangle); 3 sizes (big, medium, small) and 3 speeds (fast, medium, slow).  General motor skills were also assessed through a CKAT battery measuring tracking, tracing and aiming abilities, as well as parental questionnaires regarding DCD tendencies and ASD severity. Participants were age (11-17) and IQ matched (ASD n = 16; TD n = 24).

Results:

An ANCOVA [between-subjects: group (ASD, TD); covariate: age, WASI-verbal, WASI-performance] revealed a significant main effect of group for both AI path length (F(1, 35) = 11.38, p = .002, h_p² = .25) and duration (F(1, 35) = 4.38, p = .044, h_p² = .11) and for MER path length (F(1, 35) = 5.62, p = .023, h_p² = .14).  Furthermore, a principal components analysis (PCA) with varimax rotation on the 21 items of imitation, motor abilities and individual differences yielded a 4-factor solution explaining 77% of variance.  Factor 1 – Imitation Ability, accounted for 49.7% of variance; Factor 2 – Motor Ability and Age, for an additional 13.0%; Factor 3 – Verbal IQ, for a further 8.0%; and finally Factor 4 – Performance IQ, for 5.9%.  SRS and DCD scores loaded both on Factors 1 and 3.

Conclusions:  

Participants with autism performed more poorly than controls on both types of copying task (MER and AI) and for both measures (path length and duration) after controlling for age and IQ.  In a PCA, all copying measures loaded onto a single factor, being highly intercorrelated. However, this copying ability was distinct from age, IQ and measured motor control, supporting the hypothesis that it represents a separate construct. Our results provide strong evidence for a specific social learning deficit in autism but suggest that it is not confined to imitation.