Chunk #16 — Changes in Frontal EEG Coherence across Infancy Predict Cognitive Abilities at Age 3: The Mediating Role of Attentional Control — EEG Coherence and the Estimation of Neural Networks
EEG is a noninvasive methodology for assessing brain activity in infants and young children. The EEG signal is recorded from the scalp and is composed of multiple sine waves cycling at different frequencies. Fourier analysis decomposes the EEG into these different sine waves and estimates the spectral power at each frequency (Bell & Cuevas, 2012). EEG power is theorized to reflect the number of neurons that discharge synchronously from a particular neuronal population (Klimesch, 1999; Pizzagalli, 2007) and is an indicator of localized neural activity. A neural network can be estimated using EEG by analyzing the temporal correlations of the activity at different scalp locations. EEG coherence is the frequency-dependent squared cross-correlation of the electrical signals at two sites (Thatcher, 2012), and reflects the consistency of their phase relationship. Coherence values range from zero to one: when the phase relationship remains constant (over a specified period of time) then coherence values approach one; if there is no relation in phase (i.e., moment-to-moment changes) then coherence values approach zero. Oscillatory activity at two spatially separated sites that is near constant in
