Emily S Kuschner1,2, Mina Kim3, Luke Bloy3, Marissa Dipiero3, J Christopher Edgar3, Timothy P L Roberts3. 1. Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, 2716 South Street, 5th Floor, Room 5251, Philadelphia, PA, 19146, USA. kuschnere@chop.edu. 2. Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. kuschnere@chop.edu. 3. Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, 2716 South Street, 5th Floor, Room 5251, Philadelphia, PA, 19146, USA.
Abstract
BACKGROUND: Neuroimaging research on individuals who have autism spectrum disorder (ASD) has historically been limited primarily to those with age-appropriate cognitive and language performance. Children with limited abilities are frequently excluded from such neuroscience research given anticipated barriers like tolerating the loud sounds associated with magnetic resonance imaging and remaining still during data collection. To better understand brain function across the full range of ASD there is a need to (1) include individuals with limited cognitive and language performance in neuroimaging research (non-sedated, awake) and (2) improve data quality across the performance range. The purpose of this study was to develop, implement, and test the feasibility of a clinical/behavioral and technical protocol for obtaining magnetoencephalography (MEG) data. Participants were 38 children with ASD (8-12 years) meeting the study definition of minimally verbal/nonverbal language. MEG data were obtained during a passive pure-tone auditory task. RESULTS: Based on stakeholder feedback, the MEG Protocol for Low-language/cognitive Ability Neuroimaging (MEG-PLAN) was developed, integrating clinical/behavioral and technical components to be implemented by an interdisciplinary team (clinicians, behavior specialists, scientists, and technologists). Using MEG-PLAN, a 74% success rate was achieved for acquiring MEG data, with a 71% success rate for evaluable and analyzable data. Exploratory analyses suggested nonverbal IQ and adaptive skills were related to reaching the point of acquirable data. No differences in group characteristics were observed between those with acquirable versus evaluable/analyzable data. Examination of data quality (evaluable trial count) was acceptable. Moreover, results were reproducible, with high intraclass correlation coefficients for pure-tone auditory latency. CONCLUSIONS: Children who have ASD who are minimally verbal/nonverbal, and often have co-occurring cognitive impairments, can be effectively and comfortably supported to complete an electrophysiological exam that yields valid and reproducible results. MEG-PLAN is a protocol that can be disseminated and implemented across research teams and adapted across technologies and neurodevelopmental disorders to collect electrophysiology and neuroimaging data in previously understudied groups of individuals.
BACKGROUND: Neuroimaging research on individuals who have autism spectrum disorder (ASD) has historically been limited primarily to those with age-appropriate cognitive and language performance. Children with limited abilities are frequently excluded from such neuroscience research given anticipated barriers like tolerating the loud sounds associated with magnetic resonance imaging and remaining still during data collection. To better understand brain function across the full range of ASD there is a need to (1) include individuals with limited cognitive and language performance in neuroimaging research (non-sedated, awake) and (2) improve data quality across the performance range. The purpose of this study was to develop, implement, and test the feasibility of a clinical/behavioral and technical protocol for obtaining magnetoencephalography (MEG) data. Participants were 38 children with ASD (8-12 years) meeting the study definition of minimally verbal/nonverbal language. MEG data were obtained during a passive pure-tone auditory task. RESULTS: Based on stakeholder feedback, the MEG Protocol for Low-language/cognitive Ability Neuroimaging (MEG-PLAN) was developed, integrating clinical/behavioral and technical components to be implemented by an interdisciplinary team (clinicians, behavior specialists, scientists, and technologists). Using MEG-PLAN, a 74% success rate was achieved for acquiring MEG data, with a 71% success rate for evaluable and analyzable data. Exploratory analyses suggested nonverbal IQ and adaptive skills were related to reaching the point of acquirable data. No differences in group characteristics were observed between those with acquirable versus evaluable/analyzable data. Examination of data quality (evaluable trial count) was acceptable. Moreover, results were reproducible, with high intraclass correlation coefficients for pure-tone auditory latency. CONCLUSIONS: Children who have ASD who are minimally verbal/nonverbal, and often have co-occurring cognitive impairments, can be effectively and comfortably supported to complete an electrophysiological exam that yields valid and reproducible results. MEG-PLAN is a protocol that can be disseminated and implemented across research teams and adapted across technologies and neurodevelopmental disorders to collect electrophysiology and neuroimaging data in previously understudied groups of individuals.
Authors: Timothy P L Roberts; Sarah Y Khan; Mike Rey; Justin F Monroe; Katelyn Cannon; Lisa Blaskey; Sarah Woldoff; Saba Qasmieh; Mike Gandal; Gwen L Schmidt; Deborah M Zarnow; Susan E Levy; J Christopher Edgar Journal: Autism Res Date: 2010-02 Impact factor: 5.216
Authors: Sara Jane Webb; Raphael Bernier; Heather A Henderson; Mark H Johnson; Emily J H Jones; Matthew D Lerner; James C McPartland; Charles A Nelson; Donald C Rojas; Jeanne Townsend; Marissa Westerfield Journal: J Autism Dev Disord Date: 2015-02
Authors: Carly Demopoulos; Nina Yu; Jennifer Tripp; Nayara Mota; Anne N Brandes-Aitken; Shivani S Desai; Susanna S Hill; Ashley D Antovich; Julia Harris; Susanne Honma; Danielle Mizuiri; Srikantan S Nagarajan; Elysa J Marco Journal: Front Hum Neurosci Date: 2017-05-26 Impact factor: 3.169
Authors: J D Lewis; A C Evans; J R Pruett; K Botteron; L Zwaigenbaum; A Estes; G Gerig; L Collins; P Kostopoulos; R McKinstry; S Dager; S Paterson; R T Schultz; M Styner; H Hazlett; J Piven Journal: Transl Psychiatry Date: 2014-05-06 Impact factor: 6.222