EEG profiles and associated neurodevelopmental outcomes after very preterm birth

The influence of very preterm birth on adolescent EEG connectivity, network organization and long-term outcome

OBJECTIVE

The aim of this study was to explore differences in functional connectivity and network organization between very preterm born adolescents and term born controls and to investigate if these differences might explain the relation between preterm birth and adverse long-term outcome.

METHODS

Forty-seven very preterm born adolescents (53% males) and 54 controls (54% males) with matching age, sex and parental educational levels underwent high-density electroencephalography (EEG) at 13 years of age. Long-term outcome was assessed by Intelligence Quotient (IQ), motor, attentional functioning and academic performance. Two minutes of EEG data were analysed within delta, theta, lower alpha, upper alpha and beta frequency bands. Within each frequency band, connectivity was assessed using the Phase Lag Index (PLI) and Amplitude Envelope Correlation, corrected for volume conduction (AEC-c). Brain networks were constructed using the minimum spanning tree method.

RESULTS

Very preterm born adolescents had stronger beta PLI connectivity and less differentiated network organization. Beta AEC-c and differentiation of AEC-c based networks were negatively associated with long-term outcomes. EEG measures did not mediate the relation between preterm birth and outcomes.

CONCLUSIONS

This study shows that very preterm born adolescents may have altered functional connectivity and brain network organization in the beta frequency band. Alterations in measures of functional connectivity and network topologies, especially its differentiating characteristics, were associated with neurodevelopmental functioning.

SIGNIFICANCE

The findings indicate that EEG connectivity and network analysis is a promising tool for investigating underlying mechanisms of impaired functioning.

Brain structure and function in the fourth decade of life after extremely low birth weight: An MRI and EEG study

OBJECTIVE

To examine potential long-term effects of extremely low birth weight (ELBW; ≤ 1000 g) on adult brain structure, brain function, and cognitive-behavioral performance.

METHODS

A subset of survivors from the prospectively-followed McMaster ELBW Cohort (n = 23, MBW = 816 g) and their peers born at normal birth weight (NBW; ≥ 2500 g; n = 14, MBW = 3361 g) provided T1-weighted magnetic resonance imaging (MRI) brain scans, resting electroencephalographic (EEG) recordings, and behavioral responses to a face-processing task in their early thirties.

RESULTS

Visual discrimination accuracy for human faces, resting EEG alpha power, and long-distance alpha coherence were lower in ELBW survivors than NBW adults, and volumes of white matter hypointensities (WMH) were higher. Across groups, face-processing performance was correlated positively with posterior EEG spectral power and long-distance alpha and theta coherence, and negatively with WMH. The associations between face-processing scores and parietal alpha power and theta coherence were reduced after adjustment for WMH.

CONCLUSIONS

Electrocortical activity, brain functional connectivity, and higher-order processing ability may be negatively affected by WMH burden, which is greater in adults born extremely preterm.

SIGNIFICANCE

Decrements in electrocortical activity and behavioral performance in adult ELBW survivors may be partly explained by increased WMH volumes in this vulnerable population.

Neurobiological perspective on the development of executive functions

Executive functions are a set of top-down cognitive processes necessary for emotional self-regulation and goal-directed behaviour supporting, among others, academic abilities. Premature infants are at high risk for subsequent cognitive, psychosocial, or behavioural problems even in the absence of medical complications and in spite of normal brain imaging. Given that this is a sensitive period of brain growth and maturation, these factors may place preterm infants at high risk for executive function dysfunction, disrupted long-term development, and lower academic achievements. Therefore, careful attention to interventions at this age is essential for intact executive functions and academic development.

Combining advanced MRI and EEG techniques better explains long-term motor outcome after very preterm birth

BACKGROUND

Preterm born children are at high risk for adverse motor neurodevelopment. The aim of this study was to establish the relationship between motor outcome and advanced magnetic resonance imaging (MRI) and electroencephalography (EEG) measures.

METHODS

In a prospective cohort study of 64 very preterm born children, the motor outcome was assessed at 9.83 (SD 0.70) years. Volumetric MRI, diffusion tensor imaging (DTI), and EEG were acquired at 10.85 (SD 0.49) years. We investigated associations between motor outcome and brain volumes (white matter, deep gray matter, cerebellum, and ventricles), white matter integrity (fractional anisotropy and mean, axial and radial diffusivity), and brain activity (upper alpha (A2) functional connectivity and relative A2 power). The independence of associations with motor outcome was investigated with a final model. For each technique, the measure with the strongest association was selected to avoid multicollinearity.

RESULTS

Ventricular volume, radial diffusivity, mean diffusivity, relative A2 power, and A2 functional connectivity were significantly correlated to motor outcome. The final model showed that ventricular volume and relative A2 power were independently associated with motor outcome (B = -9.42 × 10^-5, p = 0.027 and B = 28.9, p = 0.007, respectively).

CONCLUSIONS

This study suggests that a lasting interplay exists between brain structure and function that might underlie motor outcome at school age.

IMPACT

This is the first study that investigates the relationships between motor outcome and brain volumes, DTI, and brain function in preterm born children at school age. Ventricular volume and relative upper alpha power on EEG have an independent relation with motor outcome in preterm born children at school age. This suggests that there is a lasting interplay between structure and function that underlies adverse motor outcome.

Resting state EEG in youth with ASD: age, sex, and relation to phenotype

BACKGROUND

Identification of ASD biomarkers is a key priority for understanding etiology, facilitating early diagnosis, monitoring developmental trajectories, and targeting treatment efforts. Efforts have included exploration of resting state encephalography (EEG), which has a variety of relevant neurodevelopmental correlates and can be collected with minimal burden. However, EEG biomarkers may not be equally valid across the autism spectrum, as ASD is strikingly heterogeneous and individual differences may moderate EEG-behavior associations. Biological sex is a particularly important potential moderator, as females with ASD appear to differ from males with ASD in important ways that may influence biomarker accuracy.

METHODS

We examined effects of biological sex, age, and ASD diagnosis on resting state EEG among a large, sex-balanced sample of youth with (N = 142, 43% female) and without (N = 138, 49% female) ASD collected across four research sites. Absolute power was extracted across five frequency bands and nine brain regions, and effects of sex, age, and diagnosis were analyzed using mixed-effects linear regression models. Exploratory partial correlations were computed to examine EEG-behavior associations in ASD, with emphasis on possible sex differences in associations.

RESULTS

Decreased EEG power across multiple frequencies was associated with female sex and older age. Youth with ASD displayed decreased alpha power relative to peers without ASD, suggesting increased neural activation during rest. Associations between EEG and behavior varied by sex. Whereas power across various frequencies correlated with social skills, nonverbal IQ, and repetitive behavior for males with ASD, no such associations were observed for females with ASD.

CONCLUSIONS

Research using EEG as a possible ASD biomarker must consider individual differences among participants, as these features influence baseline EEG measures and moderate associations between EEG and important behavioral outcomes. Failure to consider factors such as biological sex in such research risks defining biomarkers that misrepresent females with ASD, hindering understanding of the neurobiology, development, and intervention response of this important population.

Early Diagnosis of Brain Injury in Premature Infants Based on Amplitude-Integrated EEG Scoring System

Analyzing and discussing the relationship between brain injury in preterm infants and related risk factors can provide evidence for perinatal prevention and early intervention of brain injury in preterm infants, thereby improving the quality of life of preterm infants. This paper selects term preterm infants diagnosed with preterm infant asphyxia in the NICU of a university's First Affiliated Hospital from January 2018 to February 2019 as the research object. In addition, healthy term infants born at the same time in the obstetric department of this hospital are selected as the control group. Both groups of premature infants were monitored for brain function within 6 hours after birth. The aEEG results range from background activity (continuous normal voltage, discontinuous normal voltage, burst suppression, continuous low voltage, and plateau) and sleep-wake cycle (no sleep-wake cycle, immature, and mature sleep-wake cycle) to epileptic activity (single seizures, recurrent seizures, and status epilepticus), three aspects to judge. Statistical analysis uses SPSS 17.0 software. Amplitude-integrated EEG is a simplified form of continuous EEG recording. The trace of the trace represents the voltage change signal of the entire EEG background activity, which can reflect the EEG amplitude, frequency, burst-inhibition, and other pieces of information. aEEG can reflect the degree of HIE lesions in premature infants and the long-term prognosis. It is easy to operate and effective in diagnosis and can be continuously monitored. It is worthy of clinical popularization. There is a good correlation between the expression of EEG and biomarkers. Combining multiple methods can diagnose HIE earlier and evaluate the prognosis.

The degree of prematurity affects functional brain activity in preterm born children at school-age: An EEG study

Prematurely born children are at higher risk for long-term adverse motor and cognitive outcomes. The aim of this paper was to compare quantitative measures derived from electroencephalography (EEG) between extremely (EP) and very prematurely (VP) born children at 9-10 years of age. Fifty-five children born <32 weeks' of gestation underwent EEG at 9-10 years of age and were assessed for motor development and cognitive outcome. Relative frequency power and functional connectivity, as measured by the Phase Lag Index (PLI), were calculated for all frequency bands. Per subject, power spectrum and functional connectivity results were averaged over all channels and pairwise PLI values to explore differences in global frequency power and functional connectivity between EP and VP children. Brain networks were constructed for the upper alpha frequency band using the Minimum Spanning Tree method and were compared between EP and VP children. In addition, the relationships between upper alpha quantitative EEG results and cognitive and motor outcomes were investigated. Relative power and functional connectivity were significantly higher in VP than EP children in the upper alpha frequency band, and VP children had more integrated networks. A strong positive correlation was found between relative upper alpha power and motor outcome whilst controlling for gestational age, age during EEG recording, and gender (ρ = 0.493, p = 0.004). These results suggest that 9-10 years after birth, the effects of the degree of prematurity can be observed in terms of alterations in functional brain activity and that motor deficits are associated with decreases in relative upper alpha power.