Translating MEG-based biomarkers to EEG-based outcome measures for Autism Spectrum Disorders

点击翻译按钮获取中文摘要

ABSTRACT / SUMMARY There is currently a clear need for objective brain based outcome measures for autism spectrum disorders (ASD). Outcome measures are measures that are used before a clinical or intervention trial begins, to get a baseline measure, and are then repeated at the end of the trial, to determine whether changes have occurred as a result of the intervention. Currently, the vast majority of outcome measures used in ASD treatment trials are based on behavioral measures, usually parental, and are therefore subjective by nature. Even in double blind trials, there is still risk of contamination of the measures from a placebo effect. Therefore, there is a clear need for objective outcome measures in the field. One such class of potential outcome measures is brain-based. Since the most oft-found clinical lab equipment is a simple 10-20 EEG system, the ideal brain-based outcome measures for ASD would use such a system. However, the vast majority of known biomarkers for ASD, that would in theory have outcome measure potential, are derived using equipment that is far too complex and expensive to replicate in clinical settings, and using paradigms that require a setup and analyses methods that are too complex to carry out clinically on a large number of subjects with high inter-subject variability. Here, we propose a novel approach to this problem. We propose to translate three biomarkers for ASD identified in our lab or by other groups using magnetoencephalography (MEG), to clinical EEG. The study will focus on MEG-based biomarkers already known to be associated with ASD diagnosis and severity, one in the auditory domain, one in the tactile domain, and one using a relatively novel analysis of resting state data. The translation to clinical EEG would be judiciously carried out, by combining MEG and EEG data collection, and then using a data driven approach to validate the results. We will also develop a user-friendly toolbox as part of the process, to standardize data analysis and make the process easily portable and uniform across multiple sites. The initial development will be carried out using 10 typically developing participants, and 10 ASD participants, using high density simultaneous EEG/MEG data collection. The results will then be validated using 15 new participants per group, and simultaneous “clinical EEG” (i.e. minimal sensor locations) and high-density MEG data collection. This proof of concept proposal will take place entirely onsite, and will form the basis for future offsite studies across multiple clinical settings, ideally in conjunction with ongoing clinical trials.