What changes in neural oscillations can reveal about developmental cognitive neuroscience: Language development as a case in point

Abstract

EEG is a primary method for studying temporally precise neuronal processes across the lifespan. Most of this work focuses on Event Related Potentials (ERPs); however, using time-locked time frequency analysis to decompose the EEG signal can identify and distinguish multiple changes in brain oscillations underlying cognition (Bastiaansen et al., 2010). Further this measure is thought to reflect changes in inter-neuronal communication more directly than ERPs (Nunez & Srinivasan, 2006). Although time frequency has elucidated cognitive processes in adults, applying it to cognitive development is still rare. Here, we review the basics of neuronal oscillations, some of what they reveal about adult cognitive function, and what little is known relating to children. We focus on language because it develops early and engages complex cortical networks. Additionally, because time frequency analysis of the EEG related to adult language comprehension has been incredibly informative, using similar methods with children will shed new light on current theories of language development and increase our understanding of how neural processes change over the lifespan. Our goal is to emphasize the power of this methodology and encourage its use throughout developmental cognitive neuroscience.

Developmental differences in the neural correlates supporting semantics and syntax during sentence processing

“…Changes in power do not depend on precise phase locking of the amplitude change across trials, as do ERPs, and therefore provide additional nonphase‐locked information which can substantially increase the information about cognitive processing that can be obtained from the EEG signal (Cohen, ). While ERPs and time frequency responses measure similar neural processes (Bastiaansen, Oostenveld, Jensen, & Hagoort, ; Davidson & Indefrey, ; Hagoort, Hald, Bastiaansen, & Petersson, ; Roehm, Bornkessel‐Schlesewsky, & Schlesewsky, ; Schneider et al, ), this nonphase‐locked information also identifies neural processes beyond those identified by ERP components alone (Bastiaansen & Hagoort, ; Bastiaansen et al, ; Maguire & Abel, ; Schneider & Maguire, ; Wang et al, ). Given the speed and complexity of auditory sentence comprehension, time frequency analysis can be a valuable method for identifying more subtle developmental differences in semantic and syntactic processing that may be averaged out with ERP analyses.…”

Neural oscillatory mechanisms during novel grammar learning underlying language analytical abilities

“…From a neurophysiological point of view, high-level cognitive functions such as language, necessarily depend on synchronised activity both between and within specific neural assemblies (Bressler, 1995;Bressler & Menon, 2010;Friederici & Singer, 2015;Maguire & Abel, 2013;Mesulam, 1998;W. Singer, 1993;Varela, Lachaux, Rodriguez, & Martinerie, 2001;Weiss & Mueller, 2003).…”

Electroencephalography theta differences between object nouns and action verbs when identifying semantic relations

“…For example, an increase in theta power may occur concurrently with a decrease in beta power during the same cognitive task. An increase in power is thought to relate to the activation of additional neural assemblies firing at the same frequency, also referred to as neuronal synchrony (Maguire & Abel, 2013;Nunez & Srinivasan, 2005). Similarly, a decrease in power is thought to correspond to decreased activation of neural assemblies within a frequency or neuronal desynchrony.…”