14 challenges and their solutions for conducting social neuroscience and longitudinal EEG research with infants |
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| Affiliation: | 1. Department of Psychology, University of Cambridge, Cambridge, UK;2. Division of Psychology, Nanyang Technological University, Singapore;3. School of Psychology, University of East London, London, UK;1. Department of Psychology, University of Connecticut, United States;2. Department of Human Development and Quantitative Methodology, University of Maryland, College Park, United States;1. Department of Human Development, Washington State University, USA;2. Department of Psychology, Washington State University, USA;1. Neuroscience Center, University of Helsinki, Helsinki, Finland;2. Department of Children’s Clinical Neurophysiology, HUS Medical Imaging Center and Children’s Hospital, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland;1. Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA;2. Department of Psychology, New York University, New York, NY 10003, USA;3. Department of Pediatrics, Columbia University Medical Center, New York, NY 10032, USA;1. Department of Psychology, Lancaster University, Bailrigg, UK;2. Department of Experimental Psychology, Downing Site, Downing Street, University of Cambridge, Cambridge, UK;3. School of Mathematics, University of Edinburgh, Edinburgh, UK;4. Department of Mathematics and Statistics, Lancaster University, Bailrigg, UK;5. School of Psychology, The University of Waikato, New Zealand |
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| Abstract: | The use of electroencephalography (EEG) to study infant brain development is a growing trend. In addition to classical longitudinal designs that study the development of neural, cognitive and behavioural functions, new areas of EEG application are emerging, such as novel social neuroscience paradigms using dual infant-adult EEG recordings. However, most of the experimental designs, analysis methods, as well as EEG hardware were originally developed for single-person adult research. When applied to study infant development, adult-based solutions often pose unique problems that may go unrecognised. Here, we identify 14 challenges that infant EEG researchers may encounter when designing new experiments, collecting data, and conducting data analysis. Challenges related to the experimental design are: (1) small sample size and data attrition, and (2) varying arousal in younger infants. Challenges related to data acquisition are: (3) determining the optimal location for reference and ground electrodes, (4) control of impedance when testing with the high-density sponge electrode nets, (5) poor fit of standard EEG caps to the varying infant head shapes, and (6) ensuring a high degree of temporal synchronisation between amplifiers and recording devices during dual-EEG acquisition. Challenges related to the analysis of longitudinal and social neuroscience datasets are: (7) developmental changes in head anatomy, (8) prevalence and diversity of infant myogenic artefacts, (9) a lack of stereotypical topography of eye movements needed for the ICA-based data cleaning, (10) and relatively high inter-individual variability of EEG responses in younger cohorts. Additional challenges for the analysis of dual EEG data are: (11) developmental shifts in canonical EEG rhythms and difficulties in differentiating true inter-personal synchrony from spurious synchrony due to (12) common intrinsic properties of the signal and (13) shared external perturbation. Finally, (14) there is a lack of test-retest reliability studies of infant EEG. We describe each of these challenges and suggest possible solutions. While we focus specifically on the social neuroscience and longitudinal research, many of the issues we raise are relevant for all fields of infant EEG research. |
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| Keywords: | Infant Electroencephalography (EEG) Longitudinal design Methodology Social neuroscience |
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