Developmental changes in spontaneous electrocortical activity and network organization from early to late childhood

Frequency shift in topography of spontaneous brain rhythms from childhood to adulthood

It has been described that the frequency ranges at which theta, mu and alpha rhythms oscillate is increasing with age. The present report, by analyzing the spontaneous EEG, tries to demonstrate whether there is an increase with age in the frequency at which the cortical structures oscillate. A topographical approach was followed. The spontaneous EEG of one hundredand seventy subjects was recorded. The spectral power (from 0.5 to 45.5 Hz) was obtained by means of the Fast Fourier Transform. Correlations of spatial topographies among the different age groups showed that older groups presented the same topographical maps as younger groups, but oscillating at higher frequencies. The results suggest that the same brain areas oscillate at lower frequencies in children than in older groups, for a broad frequency range. This shift to a higher frequency with age would be a trend in spontaneous brain rhythm development.

Charting moment-to-moment brain signal variability from early to late childhood

Large-scale brain signals exhibit rich intermittent patterning, reflecting the fact that the cortex actively eschews fixed points in favor of itinerant wandering with frequent state transitions. Fluctuations in endogenous cortical activity occur at multiple time scales and index a dynamic repertoire of network states that are continuously explored, even in the absence of external sensory inputs. Here, we quantified such moment-to-moment brain signal variability at rest in a large, cross-sectional sample of children ranging in age from seven to eleven years. Our findings revealed a monotonic rise in the complexity of electroencephalogram (EEG) signals as measured by sample entropy, from the youngest to the oldest age cohort, across a range of time scales and spatial regions. From year to year, the greatest changes in intraindividual brain signal variability were recorded at electrodes covering the anterior cortical zones. These results provide converging evidence concerning the age-dependent expansion of functional cortical network states during a critical developmental period ranging from early to late childhood.

Maturation of the P3 and concurrent oscillatory processes during adolescence

OBJECTIVE

During adolescence event-related modulations of the neural response may increase. For slow event-related components, such as the P3, this developmental change may be masked due to increased amplitude levels of ongoing delta and theta oscillations in adolescents.

METHODS

In a cross-sectional study design, EEG was measured in 51 participants between 13 and 24years. A visual oddball paradigm was used to elicit the P3. Our analysis focused on fronto-parietal activations within the P3 time-window and the concurrent time-frequency characteristics in the delta (∼0.5-4Hz) and theta (∼4-7Hz) band.

RESULTS

The parietal P3 amplitude was similar across the investigated age range, while the amplitude at frontal regions increased with age. The pre-stimulus amplitudes of delta and theta oscillations declined with age, while post-stimulus amplitude enhancement and inter-trial phase coherence increased. These changes affected fronto-parietal electrode sites.

CONCLUSIONS

The parietal P3 maximum seemed comparable for adolescents and young adults. Detailed analysis revealed that within the P3 time-window brain maturation during adolescence may lead to reduced spontaneous slow-wave oscillations, increased amplitude modulation and time precision of event-related oscillations, and altered P3 scalp topography.

SIGNIFICANCE

Time-frequency analyses may help to distinguish selective neurodevelopmental changes within the P3 time window.

Toward Developmental Connectomics of the Human Brain

Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying structural and functional connectivity patterns of the developing brain. Normal brain development is characterized by continuous and significant network evolution throughout infancy, childhood, and adolescence, following specific maturational patterns. Disruption of these normal changes is associated with neuropsychiatric developmental disorders, such as autism spectrum disorders or attention-deficit hyperactivity disorder. In this review, we focused on the recent progresses regarding typical and atypical development of human brain networks from birth to early adulthood, using a connectomic approach. Specifically, by the time of birth, structural networks already exhibit adult-like organization, with global efficient small-world and modular structures, as well as hub regions and rich-clubs acting as communication backbones. During development, the structure networks are fine-tuned, with increased global integration and robustness and decreased local segregation, as well as the strengthening of the hubs. In parallel, functional networks undergo more dramatic changes during maturation, with both increased integration and segregation during development, as brain hubs shift from primary regions to high order functioning regions, and the organization of modules transitions from a local anatomical emphasis to a more distributed architecture. These findings suggest that structural networks develop earlier than functional networks; meanwhile functional networks demonstrate more dramatic maturational changes with the evolution of structural networks serving as the anatomical backbone. In this review, we also highlighted topologically disorganized characteristics in structural and functional brain networks in several major developmental neuropsychiatric disorders (e.g., autism spectrum disorders, attention-deficit hyperactivity disorder and developmental dyslexia). Collectively, we showed that delineation of the brain network from a connectomics perspective offers a unique and refreshing view of both normal development and neuropsychiatric disorders.