Recording and analyzing high-density event-related potentials with infants using the geodesic sensor net

M. H. Johnson, M. De Haan, A. Oliver, W. Smith, H. Hatzakis, L. A. Tucker, G. Csibra

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Abstract

This article provides an overview of the use of the Geodesic sensor net system for high-density event-related potential (ERP) recording in infants. Some advantages and disadvantages of the system, as applied to infants, are discussed. First, we illustrate that high-density data can be recorded from infants at comparable quality to that observed with conventional (low density) ERP methods. Second, we discuss ways to utilize the greater spatial information available by applying source separation and localization procedures. In particular, we focus on the application of one recent source separation method, Independent Component Analysis (ICA). Finally, we show that source localization can be applied to infant high-density data, although this entails adopting a number of assumptions that remain to be verified. In the future, with improved source separation algorithms, we suggest that single-trial or single-subject analyses may become feasible.

Original languageEnglish
Pages (from-to)295-323
Number of pages29
JournalDevelopmental Neuropsychology
Volume19
Issue number3
DOIs
Publication statusPublished - Jan 1 2001

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ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Developmental and Educational Psychology

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