3D statistical parametric mapping of quiet sleep EEG in the first year of life

Normative longitudinal EEG recordings during sleep stage II in the first year of age

The electroencephalogram (EEG) is a fundamental diagnostic procedure that explores brain function. This manuscript describes the characteristics of a sample of healthy at-term infants. One hundred and three (103) infants from Mexico between 15 days and 12.5 months of age were recorded during physiological sleep. Referential EEG recordings were obtained using linked ear lobes as reference. The amplifier gain was 10,000, the bandwidth was set between 0.3 and 30 Hz, and the sample rate was 200 Hz. Sample windows of 2.56 s were marked for later quantitative analysis. To our knowledge, this is the first dataset of normal infants during the first year of age.

EEG effective connectivity during the first year of life mirrors brain synaptogenesis, myelination, and early right hemisphere predominance

INTRODUCTION

The maturation of electroencephalogram (EEG) effective connectivity in healthy infants during the first year of life is described.

METHODS

Participants: A cross-sectional sample of 125 healthy at-term infants, from 0 to 12 months of age, underwent EEG in a state of quiet sleep.

PROCEDURES

The EEG primary currents at the source were described with the sLoreta method. An unmixing algorithm was applied to reduce the leakage, and the isolated effective coherence, a direct and directed measurement of information flow, was calculated.

RESULTS AND DISCUSSION

Initially, the highest indices of connectivity are at the subcortical nuclei, continuing to the parietal lobe, predominantly the right hemisphere, then expanding to temporal, occipital, and finally the frontal areas, which is consistent with the myelination process. Age-related connectivity changes were mostly long-range and bilateral. Connections increased with age, mainly in the right hemisphere, while they mainly decreased in the left hemisphere. Increased connectivity from 20 to 30 Hz, mostly at the right hemisphere. These findings were consistent with right hemisphere predominance during the first three years of life. Theta and alpha connections showed the greatest changes with age. Strong connectivity was found between the parietal, temporal, and occipital regions to the frontal lobes, responsible for executive functions and consistent with behavioral development during the first year. The thalamus exchanges information bidirectionally with all cortical regions and frequency bands.

CONCLUSIONS

The maturation of EEG connectivity during the first year in healthy infants is very consistent with synaptogenesis, reductions in synaptogenesis, myelination, and functional and behavioral development.

A Quantitative EEG Toolbox for the MNI Neuroinformatics Ecosystem: Normative SPM of EEG Source Spectra

The Tomographic Quantitative Electroencephalography (qEEGt) toolbox is integrated with the Montreal Neurological Institute (MNI) Neuroinformatics Ecosystem as a docker into the Canadian Brain Imaging Research Platform (CBRAIN). qEEGt produces age-corrected normative Statistical Parametric Maps of EEG log source spectra testing compliance to a normative database. This toolbox was developed at the Cuban Neuroscience Center as part of the first wave of the Cuban Human Brain Mapping Project (CHBMP) and has been validated and used in different health systems for several decades. Incorporation into the MNI ecosystem now provides CBRAIN registered users access to its full functionality and is accompanied by a public release of the source code on GitHub and Zenodo repositories. Among other features are the calculation of EEG scalp spectra, and the estimation of their source spectra using the Variable Resolution Electrical Tomography (VARETA) source imaging. Crucially, this is completed by the evaluation of z spectra by means of the built-in age regression equations obtained from the CHBMP database (ages 5-87) to provide normative Statistical Parametric Mapping of EEG log source spectra. Different scalp and source visualization tools are also provided for evaluation of individual subjects prior to further post-processing. Openly releasing this software in the CBRAIN platform will facilitate the use of standardized qEEGt methods in different research and clinical settings. An updated precis of the methods is provided in Appendix I as a reference for the toolbox. qEEGt/CBRAIN is the first installment of instruments developed by the neuroinformatic platform of the Cuba-Canada-China (CCC) project.

Quantitative EEG Tomography of Early Childhood Malnutrition

The goal of this study is to identify the quantitative electroencephalographic (qEEG) signature of early childhood malnutrition [protein-energy malnutrition (PEM)]. To this end, archival digital EEG recordings of 108 participants in the Barbados Nutrition Study (BNS) were recovered and cleaned of artifacts (46 children who suffered an episode of PEM limited to the first year of life) and 62 healthy controls). The participants of the still ongoing BNS were initially enrolled in 1973, and EEGs for both groups were recorded in 1977-1978 (at 5-11 years). Scalp and source EEG Z-spectra (to correct for age effects) were obtained by comparison with the normative Cuban Human Brain Mapping database. Differences between both groups in the z spectra (for all electrode locations and frequency bins) were assessed by t-tests with thresholds corrected for multiple comparisons by permutation tests. Four clusters of differences were found: (a) increased theta activity (3.91-5.86 Hz) in electrodes T4, O2, Pz and in the sources of the supplementary motor area (SMA); b) decreased alpha1 (8.59-8.98 Hz) in Fronto-central electrodes and sources of widespread bilateral prefrontal are; (c) increased alpha2 (11.33-12.50 Hz) in Temporo-parietal electrodes as well as in sources in Central-parietal areas of the right hemisphere; and (d) increased beta (13.67-18.36 Hz), in T4, T5 and P4 electrodes and decreased in the sources of bilateral occipital-temporal areas. Multivariate Item Response Theory of EEGs scored visually by experts revealed a neurophysiological latent variable which indicated excessive paroxysmal and focal abnormality activity in the PEM group. A robust biomarker construction procedure based on elastic-net regressions and 1000-cross-validations was used to: (i) select stable variables and (ii) calculate the area under ROC curves (AUC). Thus, qEEG differentiate between the two nutrition groups (PEM vs Control) performing as well as visual inspection of the EEG scored by experts (AUC = 0.83). Since PEM is a global public health problem with lifelong neurodevelopmental consequences, our finding of consistent differences between PEM and controls, both in qualitative and quantitative EEG analysis, suggest that this technology may be a source of scalable and affordable biomarkers for assessing the long-term brain impact of early PEM.

Unified Bayesian Estimator of EEG Reference at Infinity: rREST (Regularized Reference Electrode Standardization Technique)

The choice of reference for the electroencephalogram (EEG) is a long-lasting unsolved issue resulting in inconsistent usages and endless debates. Currently, both the average reference (AR) and the reference electrode standardization technique (REST) are two primary, apparently irreconcilable contenders. We propose a theoretical framework to resolve this reference issue by formulating both (a) estimation of potentials at infinity, and (b) determination of the reference, as a unified Bayesian linear inverse problem, which can be solved by maximum a posterior estimation. We find that AR and REST are very particular cases of this unified framework: AR results from biophysically non-informative prior; while REST utilizes the prior based on the EEG generative model. To allow for simultaneous denoising and reference estimation, we develop the regularized versions of AR and REST, named rAR and rREST, respectively. Both depend on a regularization parameter that is the noise to signal variance ratio. Traditional and new estimators are evaluated with this framework, by both simulations and analysis of real resting EEGs. Toward this end, we leverage the MRI and EEG data from 89 subjects which participated in the Cuban Human Brain Mapping Project. Generated artificial EEGs—with a known ground truth, show that relative error in estimating the EEG potentials at infinity is lowest for rREST. It also reveals that realistic volume conductor models improve the performances of REST and rREST. Importantly, for practical applications, it is shown that an average lead field gives the results comparable to the individual lead field. Finally, it is shown that the selection of the regularization parameter with Generalized Cross-Validation (GCV) is close to the “oracle” choice based on the ground truth. When evaluated with the real 89 resting state EEGs, rREST consistently yields the lowest GCV. This study provides a novel perspective to the EEG reference problem by means of a unified inverse solution framework. It may allow additional principled theoretical formulations and numerical evaluation of performance.

Local changes in computational non-rapid eye movement sleep depth in infants

OBJECTIVE

Deep NREM sleep and its hallmark EEG phenomenon slow wave activity (SWA) are under homeostatic control in adults. SWA is also locally regulated as it increases in the brain areas that have been used intensively. Moreover, in children, SWA is a marker of cortical maturation. In the present study the local properties of NREM sleep depth were evaluated using the quantitative mean frequency method. We aimed to study if age is related to NREM sleep depth in young infants. In addition, we studied if young infants have local differences in their NREM sleep.

METHODS

Ambulatory over-night polysomnographies were recorded in 59 healthy and full-term infants at the age of one month. The infants were divided into two age groups (<44 weeks and ≥44 weeks) to allow maturational evaluations.

RESULTS

The quantitative sleep depth analysis showed differences between the age groups. In addition, there were local sleep depth differences within the age groups.

CONCLUSIONS

The sleep depth change with age is most likely related to cortical maturation, whereas the local sleep depth gradients might also reflect the use-dependent properties of SWA.

SIGNIFICANCE

The results support the idea that young infants have frontal cortical processing.

Clinical neuroimaging in the preterm infant: Diagnosis and prognosis

Perinatal care advances emerging over the past twenty years have helped to diminish the mortality and severe neurological morbidity of extremely and very preterm neonates (e.g., cystic Periventricular Leukomalacia [c-PVL] and Germinal Matrix Hemorrhage - Intraventricular Hemorrhage [GMH-IVH grade 3-4/4]; 22 to < 32 weeks of gestational age, GA). However, motor and/or cognitive disabilities associated with mild-to-moderate white and gray matter injury are frequently present in this population (e.g., non-cystic Periventricular Leukomalacia [non-cystic PVL], neuronal-axonal injury and GMH-IVH grade 1-2/4). Brain research studies using magnetic resonance imaging (MRI) report that 50% to 80% of extremely and very preterm neonates have diffuse white matter abnormalities (WMA) which correspond to only the minimum grade of severity. Nevertheless, mild-to-moderate diffuse WMA has also been associated with significant affectations of motor and cognitive activities. Due to increased neonatal survival and the intrinsic characteristics of diffuse WMA, there is a growing need to study the brain of the premature infant using non-invasive neuroimaging techniques sensitive to microscopic and/or diffuse lesions. This emerging need has led the scientific community to try to bridge the gap between concepts or ideas from different methodologies and approaches; for instance, neuropathology, neuroimaging and clinical findings. This is evident from the combination of intense pre-clinical and clinicopathologic research along with neonatal neurology and quantitative neuroimaging research. In the following review, we explore literature relating the most frequently observed neuropathological patterns with the recent neuroimaging findings in preterm newborns and infants with perinatal brain injury. Specifically, we focus our discussions on the use of neuroimaging to aid diagnosis, measure morphometric brain damage, and track long-term neurodevelopmental outcomes.

Mapping changes in cortical activity during sleep in the first 4 years of life

A coherent body of evidence supports the notion that sleep is a local and use-dependent process. Significant changes in brain morphology and function occur in the first years of life, revealing a postero-anterior trajectory of cortical maturation. On this basis, a recent study demonstrated that regional cortical maturation between early childhood and late adolescence is reflected in regional changes of sleep slow wave activity (SWA) during non-rapid eye movement (NREM) sleep. Our hypothesis is that changes of electroencephalogram (EEG) rhythms during sleep from birth to childhood are also mirrored by parallel regional changes in the EEG rhythms of sleep according to the assumption of a postero-anterior gradient in cortical maturation. We studied all-night EEG of 39 healthy, full-term, infants and children aged between 0 and 48 months, evaluating regional differences in NREM sleep. We confirmed the strictly local nature of sleep with frequency-specific regional differences. Specifically, we found a general shift of maxima of the upper alpha activity from occipital to prefrontal regions, expressed mainly by the ~11 Hz frequency. This shift corresponds to a postero-anterior trajectory of the so-called 'slow spindles'. The theta and alpha EEG activity of the frontal cortex exhibits a clear, positive, correlation with age. We conclude that specific local differences during NREM sleep, parallel cortical maturation also in the first 4 years of life.