Ontogeny of EEG During the First Year: An Integrative Monthly Analysis of Neural Oscillatory Rhythms

• In Event: Poster Session 07
  In Poster Session: PS 07 Topic - Biological Processes: Neuroscience and Genetics

Abstract

Ontogenetic changes in neural oscillatory activity are hypothesized to reflect underlying developing brain networks (e.g., synaptic pruning, myelination, reorganization). Transient interactions among neural rhythms (e.g., delta, theta, alpha, beta) are critical for the coordination of cognitive and affective processes (Jensen & Colgin, 2007). Current developmental analyses of EEG rhythms typically focus on a single rhythm cross-sectionally or at a particular age using one of a variety of contexts to measure resting-state (or baseline) activity. This approach precludes integrative analysis of co-occurring oscillations and associated ontogenetic changes in oscillatory activity.

The present longitudinal study examined multiple oscillatory rhythms all within a developmental time course. Our aims are (1) to characterize cross-context stability in resting-state EEG activity from 5 to 12 months of age; (2) to identify and compare month-to-month consistency/change in resting-state oscillatory measures; and (3) to use an integrative approach by examining multiple neural oscillatory rhythms and their interrelations (theta/beta power ratio; delta-beta power coupling). These neural signatures are essential for understanding brain processes involved in early critical self-regulatory processes; thus, our findings provide the foundation for future brain-behavior analyses.

Forty-seven typically developing infants (24 girls) were assessed monthly from 5 to 12 months of age. At each laboratory visit, resting-state EEG activity was recorded during two 60-s baseline conditions: (1) Live: a research assistant manipulated a “ball popper” toy; and (2) Video: a cartoon video clip was played. Data collection, processing, and editing are complete. Data screening (e.g., outliers) is underway for EEG power measures for the following rhythms: delta (1-2 Hz), theta (3-5 Hz), alpha (6-9 Hz), and beta (12-18 Hz). Data analysis will commence in October with sufficient time for presentation at April’s conference.

Measures of cross-frequency power coupling are conceptualized to reflect integration among oscillatory rhythms as opposed to the “balancing” of rhythmic activity represented by power ratios (Huang et al., 2016). Our analyses will focus on theta/beta power ratio and delta-beta power coupling. Only a few studies have examined either measure during early development; this will be the first developmental analysis of both inter-rhythm measures. Delta-beta power coupling is theorized to reflect functional interactions between subcortical and cortical activity (Knyazev, 2007), and has been examined in relation to emotion reactivity and self-regulatory processes during infancy (Brooker et al., 2016). Similarly, the theta/beta ratio is hypothesized to indicate cognitive-motivational systems balance via bottom-up subcortical excitatory input (theta activity) and top-down cortical inhibitory input (beta; Schutter et al., 2017). The theta/beta ratio has not been examined during infancy, but is inversely associated regulation and attentional control in children (e.g., Perone et al., 2018).

Based on the limited literature, we anticipate that neural oscillation parameters will exhibit different longitudinal patterns that will vary as a function of spatial topography and resting-state context. As the first longitudinal analysis, it is unknown whether stability or growth will be captured during the first postnatal year. Regardless of the specific patterns, the findings that emerge from this integrative analysis will be informative to the field, providing a foundation for future brain-behavior analyses.

Authors

• Kimberly Cuevas, University of Connecticut
  Presenting Author

• Zhe Wang, Texas A&M University - College Station
  Non-Presenting Author

• Lauren Bryant, University of Connecticut
  Non-Presenting Author

• Martha Ann Bell, Virginia Polytechnic Institute and State University
  Non-Presenting Author