Effects of Correcting for Prematurity on Executive Function Scores of Children Born Very Preterm at School Age.

OBJECTIVE: To investigate whether correction for prematurity affects executive function scores in school-aged children born very preterm. STUDY DESIGN: Executive functions were assessed with standardized neuropsychological tests in 142 children born very preterm (born at ≤32 weeks of gestational age or with a birth weight of ≤1500 g) and 391 control children, aged 7-13 years. Four-month age bands were established from the data of control children. Differences between uncorrected and corrected scores were compared against zero difference and between very preterm children born before and after 28 weeks of gestation. Regression models were used to compare the uncorrected and corrected scores of children born very preterm with control children. RESULTS: For all executive functions, significant, larger-than-zero differences between uncorrected and corrected scores were apparent in children born very preterm. Mean differences ranged from 0.04 to 0.18 SDs. Weak evidence was found that the effect of age correction is more pronounced in very preterm children born before 28 weeks of gestation than in those born after 28 weeks. Differences in executive function scores between children born very preterm and control children were attenuated if scores were corrected for prematurity. CONCLUSIONS: Test scores based on corrected rather than uncorrected age may more accurately determine the developmental stage of very preterm children's executive functions at school age. Potential consequences for clinical and research practice need to be discussed in the future.

Neural correlates of memory recovery: Preliminary findings in children and adolescents with acquired brain injury.

BACKGROUND: After acquired brain injury (ABI), patients show various neurological impairments and outcome is difficult to predict. Identifying biomarkers of recovery could provide prognostic information about a patient's neural potential for recovery and improve our understanding of neural reorganization. In healthy subjects, sleep slow wave activity (SWA, EEG spectral power 1-4.5 Hz) has been linked to neuroplastic processes such as learning and brain maturation. Therefore, we suggest that SWA might be a suitable measure to investigate neural reorganization underlying memory recovery. OBJECTIVES: In the present study, we used SWA to investigate neural correlates of recovery of function in ten paediatric patients with ABI (age range 7-15 years). METHODS: We recorded high-density EEG (128 electrodes) during sleep at the beginning and end of rehabilitation. We used sleep EEG data of 52 typically developing children to calculate age-normalized values for individual patients. In patients, we also assessed every-day life memory impairment at the beginning and end of rehabilitation. RESULTS: In the course of rehabilitation, memory recovery was paralleled by longitudinal changes in SWA over posterior parietal brain areas. SWA over left prefrontal and occipital brain areas at the beginning of rehabilitation predicted memory recovery. CONCLUSIONS: We show that longitudinal sleep-EEG measurements are feasible in the clinical setting. While posterior parietal and prefrontal brain areas are known to belong to the memory "core network", occipital brain areas have never been related to memory. While we have to remain cautious in interpreting preliminary findings, we suggest that SWA is a promising measure to investigate neural reorganization.

High-Density Electroencephalographic Recordings During Sleep in Children and Adolescents With Acquired Brain Injury.

BACKGROUND: Acquired brain injuries (ABI) such as traumatic brain injury (TBI) or stroke can result in motor, language, or cognitive impairments. Although a considerable number of studies have investigated functional recovery, underlying brain reorganization remains poorly understood. Accumulating evidence indicates that plastic processes in the brain are linked to changes in electroencephalographic (EEG) slow wave activity (SWA) during deep sleep (EEG spectral power 1-4.5 Hz). OBJECTIVE: We investigated sleep SWA in children and adolescents with ABI. METHODS: We used high-density EEG (128 electrodes) to record sleep in 22 young patients with ABI (age range = 4-16 years). We compared patients to 52 previously measured typically developing children and adolescents (age range = 4-16 years). RESULTS: The pattern of alterations in SWA differed between particular patient groups. In patients with bilateral stroke, SWA was globally reduced across the entire scalp. Patients with unilateral stroke showed a local reduction in SWA over lesion areas and an increase over perilesional and contralateral brain areas. In patients with severe TBI, we found a reduction in SWA over the midline and an increase over lateral brain areas. We found no consistent pattern in patients with mild to moderate TBI. CONCLUSIONS: Sleep SWA seems to be a sensitive measure to assess individual alterations in neural activity after ABI. Deviations from age norms might indirectly indicate plastic processes that have occurred since injury. Improving our understanding of neural activity after ABI could optimize clinical prognosis and guide the development of novel therapeutic interventions.

Developmental trajectories of EEG sleep slow wave activity as a marker for motor skill development during adolescence: a pilot study.

Reliable markers for brain maturation are important to identify neural deviations that eventually predict the development of mental illnesses. Recent studies have proposed topographical EEG-derived slow wave activity (SWA) during NREM sleep as a mirror of cortical development. However, studies about the longitudinal stability as well as the relationship with behavioral skills are needed before SWA topography may be considered such a reliable marker. We examined six subjects longitudinally (over 5.1 years) using high-density EEG and a visuomotor learning task. All subjects showed a steady increase of SWA at a frontal electrode and a decrease in central electrodes. Despite these large changes in EEG power, SWA topography was relatively stable within each subject during development indicating individual trait-like characteristics. Moreover, the SWA changes in the central cluster were related to the development of specific visuomotor skills. Taken together with the previous work in this domain, our results suggest that EEG sleep SWA represents a marker for motor skill development and further supports the idea that SWA mirrors cortical development during childhood and adolescence.

High-density electroencephalographic recordings during sleep in children with disorders of consciousness.

INTRODUCTION: A large number of studies have investigated neural correlates of consciousness in adults. However, knowledge about brain function in children with disorders of consciousness (DOC) is very limited. We suggest that EEG recordings during sleep are a promising approach. In healthy adults as well as in children, it has been shown that the activity of sleep slow waves (EEG spectral power 1-4.5 Hz), the primary characteristic of deep sleep, is dependent on use during previous wakefulness. Thus the regulation of slow wave activity (SWA) provides indirect insights into brain function during wakefulness. METHODS: In the present study, we investigated high-density EEG recordings during sleep in ten healthy children and in ten children with acquired brain injury, including five children with DOC and five children with acquired brain injury without DOC. We used the build-up of SWA to quantify SWA regulation. RESULTS: Children with DOC showed a global reduction in the SWA build-up when compared to both, healthy children and children with acquired brain injury without DOC. This reduction was most pronounced over parietal brain areas. Comparisons within the group of children with DOC revealed that the parietal SWA build-up was the lowest in patients showing poor outcome. Longitudinal measurements during the recovery period showed an increase in parietal SWA build-up from the first to the second sleep recording. CONCLUSIONS: Our results suggest that the reduced parietal SWA regulation may represent a characteristic topographical marker for brain network dysfunction in children with DOC. In the future, the regulation of SWA might be used as a complementary assessment in adult and paediatric patients with DOC.

Methods in pediatric sleep research and sleep medicine.

Several methods are used to evaluate sleep in infants, children, and adolescents including: Questionnaires and diaries, actigraphy, polysomnography, and electroencephalography which are well established. Novel approaches such as high-density electroencephalography, simultaneous electroencephalography-functional magnetic resonance imaging and nonpharmacological methods aiming for a modulation of sleep are currently only used for research. These approaches might become valuable methods for clinical application in the future. The purpose of this review is to present an overview of current methods and their respective fields of application and to report available rules and recommendations for their use.

Sleep slow-wave activity reveals developmental changes in experience-dependent plasticity.

Experience-dependent plasticity, the ability of the brain to constantly adapt to an ever-changing environment, has been suggested to be highest during childhood and to decline thereafter. However, empirical evidence for this is rather scarce. Slow-wave activity (SWA; EEG activity of 1-4.5 Hz) during deep sleep can be used as a marker of experience-dependent plasticity. For example, performing a visuomotor adaptation task in adults increased SWA during subsequent sleep over a locally restricted region of the right parietal cortex, which is known to be involved in visuomotor adaptation. Here, we investigated whether local experience-dependent changes in SWA vary as a function of brain maturation. Three age groups (children, adolescents, and adults) participated in a high-density EEG study with two conditions (baseline and adaptation) of a visuomotor learning task. Compared with the baseline condition, sleep SWA was increased after visuomotor adaptation in a cluster of eight electrodes over the right parietal cortex. The local boost in SWA was highest in children. Baseline SWA in the parietal cluster and right parietal gray matter volume, which both indicate region-specific maturation, were significantly correlated with the local increase in SWA. Our findings indicate that processes of brain maturation favor experience-dependent plasticity and determine how sensitive a specific brain region is for learning experiences. Moreover, our data confirm that SWA is a highly sensitive tool to map maturational differences in experience-dependent plasticity.

Electroencephalogram approximate entropy influenced by both age and sleep.

The use of information-based measures to assess changes in conscious state is an increasingly popular topic. Though recent results have seemed to justify the merits of such methods, little has been done to investigate the applicability of such measures to children. For our work, we used the approximate entropy (ApEn), a measure previously shown to correlate with changes in conscious state when applied to the electroencephalogram (EEG), and sought to confirm whether previously reported trends in adult ApEn values across wake and sleep were present in children. Besides validating the prior findings that ApEn decreases from wake to sleep (including wake, rapid eye movement (REM) sleep, and non-REM sleep) in adults, we found that previously reported ApEn decreases across vigilance states in adults were also present in children (ApEn trends for both age groups: wake > REM sleep > non-REM sleep). When comparing ApEn values between age groups, adults had significantly larger ApEn values than children during wakefulness. After the application of an 8 Hz high-pass filter to the EEG signal, ApEn values were recalculated. The number of electrodes with significant vigilance state effects dropped from all 109 electrodes with the original 1 Hz filter to 1 electrode with the 8 Hz filter. The number of electrodes with significant age effects dropped from 10 to 4. Our results support the notion that ApEn can reliably distinguish between vigilance states, with low-frequency sleep-related oscillations implicated as the driver of changes between vigilance states. We suggest that the observed differences between adult and child ApEn values during wake may reflect differences in connectivity between age groups, a factor which may be important in the use of EEG to measure consciousness.