Abstract
Intra-participant variability in clinical conditions such as autistic spectrum disorder (ASD) is an important indicator of pathophysiological processing. The data reported here illustrate that trial-by-trial variability can be reliably measured from EEG, and that intra-participant EEG variability is significantly greater in those with ASD than in neuro-typical matched controls. EEG recorded at the scalp is a linear mixture of activity arising from muscle artifacts and numerous concurrent brain processes. To minimize these additional sources of variability, EEG data were subjected to two different methods of spatial filtering. (i) The data were decomposed using infomax independent component analysis, a method of blind source separation which un-mixes the EEG signal into components with maximally independent time-courses, and (ii) a surface Laplacian transform was performed (current source density interpolation) in order to reduce the effects of volume conduction. Data are presented from 13 high functioning adolescents with ASD without co-morbid ADHD, and 12 neuro-typical age-, IQ-, and gender-matched controls. Comparison of variability between the ASD and neuro-typical groups indicated that intra-participant variability of P1 latency and P1 amplitude was greater in the participants with ASD, and inter-trial α-band phase coherence was lower in the participants with ASD. These data support the suggestion that individuals with ASD are less able to synchronize the activity of stimulus-related cell assemblies than neuro-typical individuals, and provide empirical evidence in support of theories of increased neural noise in ASD.
Highlights
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that has been estimated to occur in 1.16% of children in the UK (Baird et al, 2006)
These analyses indicated that there was no difference in variability when measured from the current source density (CSD) interpolated data and the back-projected IC data, but the variables computed from the raw channels were significantly more variable than the variables computed from the spatially filtered sources
Having validated the use of CSD and independent component analysis (ICA) in this study, measures of single-trial variability were compared between the participants with and without ASD, with the finding that intra-participant variability was significantly greater in the participants with ASD than in the control group
Summary
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that has been estimated to occur in 1.16% of children in the UK (Baird et al, 2006). It is characterized by substantial difficulties in social cognition, interaction, and communication (APA, 1994). In addition to these core deficits, ASD is associated with a wide range of more general impairments in many cognitive domains including, executive function (Hill, 2004), memory (Bennetto et al, 1996), attention (Allen and Courchesne, 2001), and perception (Simmons et al, 2009). Enhanced and diminished perceptual sensitivity appear to co-occur, as Bertone et al (2005) have demonstrated enhanced first-order contrast perception and decreased secondorder contrast perception within the same group of participants
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