Abstract

During infancy, the human brain rapidly expands in size and complexity as neural networks mature and new information is incorporated at an accelerating pace. Recently, it was shown that single electrode EEG in preterms at birth exhibits scale-invariant intermittent bursts. Yet, it is currently not known whether the normal infant brain, in particular, the cortex maintains a distinct dynamical state during development that is characterized by scale-invariant spatial as well as temporal aspects. Here we employ dense-array EEG recordings acquired from the same infants at 6 and 12 months of age to characterize brain activity during an auditory oddball task. We show that suprathreshold events organize as spatiotemporal clusters whose size and duration are power-law distributed, the hallmark of neuronal avalanches. Time series of local suprathreshold EEG events display significant long-range temporal correlations (LRTCs). No differences were found between 6 and 12 months, demonstrating stability of avalanche dynamics and LRTCs during the first year after birth. These findings demonstrate that the infant brain is characterized by distinct spatiotemporal dynamical aspects that are in line with expectations of a critical cortical state. We suggest that critical state dynamics, which theory and experiments have shown to be beneficial for numerous aspects of information processing, are maintained by the infant brain to process an increasingly complex environment during development.

Highlights

  • Studies on early human development, in both preterm and term newborns, have revealed structural aspects of early human brain growth using magnetic resonance imaging (MRI) (Kostović and Judaš 2006; Hüppi et al 1998; Kostović and Judaš 2008), diffusion tensor imaging (DTI) (Hüppi and Dubois 2006), and histological preparations (Kostović and Judaš 2006, 2008)

  • In order to find the best model for describing these distributions, we calculated the parameters using the maximum likelihood estimation (MLE) method (Clauset et al 2009) for each model and rejected inappropriate models based on P values

  • We found robust evidence of the stability of neuronal avalanches in early infancy

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Summary

Introduction

Studies on early human development, in both preterm and term newborns, have revealed structural aspects of early human brain growth using magnetic resonance imaging (MRI) (Kostović and Judaš 2006; Hüppi et al 1998; Kostović and Judaš 2008), diffusion tensor imaging (DTI) (Hüppi and Dubois 2006), and histological preparations (Kostović and Judaš 2006, 2008). Converging quantitative EEG and volumetric MRI analyses demonstrating significant correlation between early higher brain activity levels and increased brain volumes in preterm newborns (Benders et al 2015), support the idea that neuronal growth and survival is sensitive to early network activity. Homeostasis and dynamical regulation of brain networks require detection of scale-invariant neuronal bursts of activity. Deviations from scale-invariant neuronal activity tracks recovery from the burst suppression induced by hypoxia and predicts recovery from early hypoxic insult (Iyer et al 2015). This suggests that measures of scale-invariant dynamics may serve as potential biomarkers for early detection of concurrent risk and/or disease in infants

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