Assessing the reliability of erp, ssvep, and oscillatory data methodology for visual paradigms in infant eeg

The field of electrophysiology currently lacks a toolset for assessing and understanding variability within infant EEG datasets. Although exploratory and confirmatory infant EEG research has provided researchers with several possible markers of development, we know very little about the reliability of these neural responses across development. The present study assesses the internal consistency of neural activation during visual attention to faces and/or objects across EEG method: (1) event-related potentials (ERPs); (2) steady-state visual evoked potentials (ssVEPs); and (3) measures of oscillatory alpha desynchronization and age group (6, 9, 12 months). Infants completed several EEG tasks resulting in the three separate neural indices of visual processing. Internal consistency was quantified using Cronbach’s alpha, a coefficient representing the consistency of items across observations, for each EEG measure and age group. Reliability analyses across conditions suggest that for the visual tasks used here, measures of infant ssVEP were more robust and reliable than measures of infant ERP and alpha desynchronization, although all were reliable depending on age. For ssVEP data, Cronbach’s alpha was highest for 12-month-olds (n=32; .87), then 9-month-olds (n=33; .82), then 6-month-olds (n=35; .80). The corresponding Cronbach’s alpha values for ERPs were .71, .52, and .65, respectively, and .68, .51, and .61, respectively for alpha desynchronization. These findings suggest that during infant visual processing recordings of ssVEPs may be more reliable than recordings of ERPs and EEG alpha desynchronization. However, this effect varies by age and several notable task and condition differences that may contribute to reliability will be discussed.