Exploring Mismatch Negativity Processing in Autism Spectrum Disorder during an Auditory Odd-Ball Task: Evidence from the EU-AIMS LEAP Cohort.

Poster Presentation
Saturday, May 12, 2018: 11:30 AM-1:30 PM
Hall Grote Zaal (de Doelen ICC Rotterdam)
J. Ahmad1, P. Garces2, D. V. Crawley1, C. L. Ellis3, E. Kong1, E. J. Jones4, J. Cooke1, A. San Jose Caceres1, J. Tillmann5, T. Charman6, J. K. Buitelaar7, B. Oranje8, D. G. Murphy9,10, G. Dumas11, L. Mason4 and E. Loth1,12, (1)Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom, (2)Neuroscience, Ophthalmology, and Rare Diseases (NORD) Roche Pharma Research and Early Development. Roche Innovation Center Basel, Hoffmann-La Roche, Basel, Switzerland, (3)Social, Genetic and Developmental Psychiatry Centre, Kings College London, London, United Kingdom, (4)Centre for Brain and Cognitive Development, Birkbeck, University of London, London, United Kingdom, (5)Institute of Psychiatry Psychology & Neuroscience, London, United Kingdom, (6)Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom, (7)Radboud University Medical Center Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands, (8)Department of Psychiatry, Brain Center Rudolf Magnus, NICHE Lab, University Medical Center Utrecht, Utrecht, Netherlands, (9)Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom, (10)Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom, (11)Human Genetics and Cognitive Functions Unit, Institut Pasteur, Paris, France, (12)Forensic and Neurodevelopmental Sciences, The Sackler Institute for Translational Neurodevelopmental Sciences, IoPPN, King's College London, London, United Kingdom, London, United Kingdom

The mismatch negativity (MMN) is an ERP component thought to index neural prediction, calculated by subtracting the average response to a standard repeating tone from a rarer deviant. Prior attempts at examining the MMN in ASD have been inconsistent, indicating either smaller, larger, earlier, later, or no group differences in MMN components. Critically, sample sizes have been small (approximately 10-35 per group), and the clinical profile of participants has varied. These inconsistencies may be due to methodological differences (including lack of power) and/or the existence of different ASD subgroups – given the recognition of the clinical and etiological heterogeneity of ASD. Recent investigations of MMN have been framed within the predictive coding hypothesis, which suggests that the brain matches incoming stimuli against expectation. According to this account, participants with ASD should show a smaller MMN, since increased sensory drive may lead to standard tones being processed more similarly to deviants.


  1. In a large heterogeneous sample (N= 519) we aim to test differences in the MMN between the ASD and control groups overall, and split age groups (adults, adolescents, children),
  2. To identify potential subgroups of ASD with MMN abnormalities using normative modeling.
  3. To correlate MMN markers with ASD symptomatology (social interactions, repetitive behaviours, and sensory processing).


The project included participants from the EU-AIMS LEAP study. Participants passively listened to an auditory oddball stream, consisting of standards (1000Hz, 50ms), and 3 deviant types, each with a probability of 6% (duration (1000Hz, 100ms), frequency (1500Hz, 50ms), and combined frequency + duration deviants (1500Hz and 100ms)). The MMN was analysed at Fz. After extensive quality control and preprocessing, N=257 individuals with ASD/ASD-ID, and N=193 individuals with TD/ID were retained for analysis (6-30; IQ 50-148). Case control differences, and normative modelling with Gaussian Processes were conducted to quantify ASD participant’s deviation from the age relevant TD model mean.


Contrary to expectations, ASD participants scored similarly to controls in respects to each MMN types [for amplitude and peak latency all Fs<.58, ps>.27]. When analyses were split by age groups (adults, adolescents, and children) or by testing site, all comparisons remained non-significant [MMN components: ps>0.07]. The MMN amplitude and latency did not correlate with ASD symptomatology [rs<.08, ps>.65], but the MMN peak correlated with age: younger participants had a larger MMN [p= 9.5192E-8, r=.25]. Normative modelling revealed the percentage of ASD participants with values within +- 1 SD of the TD mean (71.20%), less than 1-2SD (9.72%), less than 2SD (3.50%), greater than 1-2SD (13.61%), and more than 2SD (1.95%).


To our awareness, this is the largest study of an oddball task in ASD. We found no evidence for abnormalities in ASD on the MMN –this was consistent when moderating variables (e.g. age, or inter-site variability) were considered. Future analysis will investigate differences in higher-level predictions, more sensitive measures of onset latency, and a scalp-wide effects. Furthermore, oscillatory time-frequency analysis will be conducted.