Increased intra-participant variability in children with autistic spectrum disorder: Evidence from single trial analyses of evoked EEG.

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 minimise 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 (ICA), 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 thirteen high functioning adolescents with ASD without co-morbid ADHD, and twelve 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 synchronise 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.

Abstract licence: CC BY

1. 12.

   Reduced neural synchronization of gamma-band MEG oscillations in first-degree relatives of children with autism · 2008

2. 38.

   LIMO EEG: A Toolbox for Hierarchical LInear MOdeling of ElectroEncephaloGraphic Data · 2011

38 more references, whose wording the paper’s licence keeps private.

• Atypical intrinsic neural timescale in autism · 2019

• Developmental pathways to autism: A review of prospective studies of infants at risk · 2014

• A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study · 2012

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.