A dataset of neonatal EEG recordings with seizure annotations

Neonatal seizures are a common emergency in the neonatal intensive care unit (NICU). There are many questions yet to be answered regarding the temporal/spatial characteristics of seizures from different pathologies, response to medication, effects on neurodevelopment and optimal detection. The dataset presented in this descriptor contains EEG recordings from human neonates, the visual interpretation of the EEG by the human experts, supporting clinical data and codes to assist access. Multi-channel EEG was recorded from 79 term neonates admitted to the NICU at the Helsinki University Hospital. The median recording duration was 74 min (IQR: 64 to 96 min). The presence of seizures in the EEGs was annotated independently by three experts. An average of 460 seizures were annotated per expert in the dataset; 39 neonates had seizures and 22 were seizure free, by consensus. The dataset can be used as a reference set of neonatal seizures, in studies of inter-observer agreement and for the development of automated methods of seizure detection and other EEG analyses.Peer reviewe

Cortical responses to tactile stimuli in preterm infants

Abstract The conventional assessment of preterm somatosensory functions using averaged cortical responses to electrical stimulation ignores the characteristic components of preterm somatosensory evoked responses (SERs). Our study aimed to systematically evaluate the occurrence and development of SERs after tactile stimulus in preterm infants. We analysed SERs performed during 45 electroencephalograms (EEGs) from 29 infants at the mean post-menstrual age of 30.7 weeks. Altogether 2,087 SERs were identified visually at single trial level from unfiltered signals capturing also their slowest components. We observed salient SERs with a high amplitude slow component at a high success rate after hand (95%) and foot (83%) stimuli. There was a clear developmental change in both the slow wave and the higher frequency components of the SERs. Infants with intraventricular haemorrhage (IVH; eleven infants) had initially normal SERs, but those with bilateral IVH later showed a developmental decrease in the ipsilateral SER occurrence after 30 weeks of post-menstrual age. Our study shows that tactile stimulus applied at bedside elicits salient SERs with a large slow component and an overriding fast oscillation, which are specific to the preterm period. Prior experimental research indicates that such SERs allow studying both subplate and cortical functions. Our present findings further suggest that they might offer a window to the emergence of neurodevelopmental sequalae after major structural brain lesions and, hence, an additional tool for both research and clinical neurophysiological evaluation of infants before term age.Peer reviewe

14 challenges and their solutions for conducting social neuroscience and longitudinal EEG research with infants.

The use of electroencephalography (EEG) to study infant brain development is a growing trend. In addition to classical longitudinal designs that study the development of neural, cognitive and behavioural functions, new areas of EEG application are emerging, such as novel social neuroscience paradigms using dual infant-adult EEG recordings. However, most of the experimental designs, analysis methods, as well as EEG hardware were originally developed for single-person adult research. When applied to study infant development, adult-based solutions often pose unique problems that may go unrecognised. Here, we identify 14 challenges that infant EEG researchers may encounter when designing new experiments, collecting data, and conducting data analysis. Challenges related to the experimental design are: (1) small sample size and data attrition, and (2) varying arousal in younger infants. Challenges related to data acquisition are: (3) determining the optimal location for reference and ground electrodes, (4) control of impedance when testing with the high-density sponge electrode nets, (5) poor fit of standard EEG caps to the varying infant head shapes, and (6) ensuring a high degree of temporal synchronisation between amplifiers and recording devices during dual-EEG acquisition. Challenges related to the analysis of longitudinal and social neuroscience datasets are: (7) developmental changes in head anatomy, (8) prevalence and diversity of infant myogenic artefacts, (9) a lack of stereotypical topography of eye movements needed for the ICA-based data cleaning, (10) and relatively high inter-individual variability of EEG responses in younger cohorts. Additional challenges for the analysis of dual EEG data are: (11) developmental shifts in canonical EEG rhythms and difficulties in differentiating true inter-personal synchrony from spurious synchrony due to (12) common intrinsic properties of the signal and (13) shared external perturbation. Finally, (14) there is a lack of test-retest reliability studies of infant EEG. We describe each of these challenges and suggest possible solutions. While we focus specifically on the social neuroscience and longitudinal research, many of the issues we raise are relevant for all fields of infant EEG research.This research was funded by an ESRC Transforming Social Sciences collaboration grant (ES/N006461/1) to VL and SW, and by ESRC FRL Fellowship (ES/N017560/1) to SW

14 challenges for conducting social neuroscience and longitudinal EEG research with infants

The use of electroencephalography (EEG) to study infant brain development is a growing trend. In addition to classical longitudinal designs that study the development of the neural, cognitive and behavioural function, new areas of EEG application are emerging, such as novel social neuroscience paradigms using dual infant-adult EEG recordings. However, most of the experimental designs, analysis methods, as well as EEG hardware were originally developed for single-person adult research. When applied to the study of infant development, adult-based solutions often pose unique problems that may go unrecognised. Here, we identify 14 challenges that infant EEG researchers may encounter when designing new experiments, collecting data, and conducting data analysis. Challenges related to the experimental design are: (1) small sample size and data attrition, and (2) varying arousal in younger infants. Challenges related to data acquisition are: (3) determining the optimal location for reference and ground electrodes, (4) control of impedance when testing with the high-density sponge electrode nets, (5) poor fit of standard EEG caps to the varying infant head shapes, and (6) ensuring a high degree of temporal synchronisation between amplifiers and recording devices during dual-EEG acquisition. Challenges related to the analysis of longitudinal and social neuroscience datasets are: (7) developmental changes in head anatomy, (8) prevalence and diversity of infant myogenic artefacts, (9) a lack of stereotypical topography of eye movements needed for the ICA-based data cleaning, (10) and relatively high inter-individual variability of EEG responses in younger cohorts. Additional challenges for the analysis of dual EEG data are: (11) developmental shifts in canonical EEG rhythms and difficulties in differentiating true inter-personal synchrony from spurious synchrony due to (12) common intrinsic properties of the signal and (13) shared external perturbation. Finally, (14) there is a lack of test-retest reliability studies of infant EEG. We describe each of these challenges and suggest possible solutions. While we focus specifically on the social neuroscience and longitudinal research, many of the issues we raise are relevant for all fields of infant EEG research

Neonatal EEG at scalp is focal and implies high skull conductivity in realistic neonatal head models

The potential improvements in spatial resolution of neonatal EEG used in source localization have been challenged by the insufficiencies in realistic neonatal head models. Our present study aimed at using empirical methods to indirectly estimate skull conductivity; the model parameter that is known to significantly affect the behavior of newborn scalp EEG and cause it to be markedly different from that of an adult. To this end, we used 64 channel EEG recordings to study the spatial specificity of scalp EEG by assessing the spatial decays in focal transients using both amplitudes and between-c'hannels linear correlations. The findings showed that these amplitudes and correlations decay within few centimeters from the reference channel/electrode, and that the nature of the decay is independent of the scalp area. This decay in newborn infants was found to be approximately three times faster than the corresponding decay in adult EEG analyzed from a set of 256 channel recordings. We then generated realistic head models using both finite and boundary element methods along with a manually segmented magnetic resonance images to study the spatial decays of scalp potentials produced by single dipole in the cortex. By comparing the spatial decays due to real and simulated EEG for different skull conductivities (from 0.003 to 0.3. S/m), we showed that a close match between the empirical and simulated decays was obtained when the selected skull conductivity for newborn was around 0.06-0.2. S/m. This is over an order of magnitude higher than the currently used values in adult head modeling. The results also showed that the neonatal scalp EEG is less smeared than that of an adult and this characteristic is the same across the entire scalp, including the fontanel region. These results indicate that a focal cortical activity is generally only registered by electrodes within few centimeters from the source. Hence, the conventional 10 to 20 channel neonatal EEG acquisition systems give a significantly spatially under sampled scalp EEG and may, consequently, give distorted pictures of focal brain activities. Such spatial specificity can only be reconciled by appreciating the anatomy of the neonatal head, especially the still unossified skull structure that needs to be modeled with higher conductivities than conventionally used in the adults

Studying connectivity in the neonatal EEG

In humans the few months surrounding birth comprise a developmentally critical period characterised by the growth of major neuronal networks as well as their initial tuning towards more functionally mature large-scale constellations. Proper wiring in the neonatal brain, especially during the last trimester of pregnancy and the first weeks of postnatal life, relies on the brain’s endogenous activity and remains critical throughout one’s life. Structural or functional abnormalities at the stage of early network formation may result in a neurological disorder later during maturation. Functional connectivity measures based on an infant electroencephalographic (EEG) time series may be used to monitor these processes. A neonatal EEG is temporally discrete and consists of events (e.g., spontaneous activity transients (SATs)) and the intervals between them (inter-SATs). During early maturation, communication between areas of the brain may be transmitted through two distinct mechanisms: synchronisation between neuronal oscillations and event co-occurrences. In this study, we proposed a novel algorithm capable of assessing the coupling on both of these levels. Our analysis of real data from preterm neonates using the proposed algorithm demonstrated its ability to effectively detect functional connectivity disruptions caused by brain lesions. Our results also suggest that SAT synchronisation represents the dominant means through which inter-areal cooperation occurs in an immature brain. Structural disturbances of the neuronal pathways in the brain carry a frequency selective effect on the functional connectivity decreasing at the event level. Next, we used mathematical models and computational simulations combined with real EEG data to analyse the propagation of electrical neuronal activity within the neonatal head. Our results show that the conductivity of the neonatal skull is much higher than that found in adults. This leads to greater focal spread of cortical signals towards the scalp and requires high-density electrode meshes for quality monitoring of neonatal brain activity. Additionally, we show that the specific structure of the neonatal skull fontanel does not represent a special pathway for the spread of electrical activity because of the overall high conductivity of the skull. Finally, we demonstrated that the choice of EEG recording montage may strongly affect the fidelity of non-redundant neuronal information registration as well as the output of functional connectivity analysis. Our simulations suggest that high-density EEG electrode arrays combined with mathematical transformations, such as the global average or current source density (CSD), provide more spatially accurate details about the underlying cortical activity and may yield results more robust against volume conduction effects. Furthermore, we provide clear instruction regarding how to optimise recording montages for different numbers of sensors.Lähikuukaudet ennen ja jälkeen syntymää ovat ihmisillä hermoston kehityksen kannalta kriittisiä vaiheita, joita luonnehtii mittavien hermostollisten verkostojen kasvu sekä niiden alustava virittäytyminen toiminnallisesti kypsiksi suuren mittakaavan yhteenliittymiksi. Vastasyntyneen aivojen koko loppuelämään vaikuttavien hermoverkostojen muodostuminen määräytyy ensimmäisten syntymän jälkeisten viikkojen mutta erityisesti raskauden viimeisen kolmanneksen aikaisen aivojen sisäsyntyisen aktiivisuuden mukaan. Rakenteelliset tai toiminnalliset epämuodostumat näiden varhaisten hermoverkostojen muodostumisvaiheessa voi johtaa neurologisiin häiriöihin myöhemmässä kypsymisessä. Varhaisen kehityksen vaiheita voidaan valvoa vastasyntyneillä mittaamalla hermoyhteyksien toiminnallista liittyvyyttä aivosähkökäyrien (EEG) aikasarjojen avuilla. Vastasyntyneen aivosähkökäyrä on ajallisesti epäjatkuva ja koostuu lyhytkestoisista spontaanin aktiivisuuden tapahtumista, SATeista (Spontaneous Activity Transients) sekä niiden välisistä ajanhetkistä, inter-SATeista. Varhaisessa hermostollisessa kypsymisessä aivoalueiden välinen yhteydenpito voi tapahtua kahdella eri mekanismilla: hermostollisten oskillaatioiden välisellä synkronisaatioilla ja tapahtumien samanaikaisuudella. Tässä tutkimuksessa me kehitimme uuden matemaattisen mallin, algoritmin, jolla voi arvioida näiden kahden mekanismin välistä kytkeytymistä. Vastasyntyneiden keskosten mittausdataan pohjautuva analyysimme osoitti, että kehittämämme algoritmi on toimiva väline aivovaurioiden aiheuttamien toiminnallisten liittyvyyskatkoksien havaitsemisessa. Tuloksemme osoittavat myös, että SAT-synkronisaatio on aivoalueiden pääasiallisin yhteydenpitokeino kypsymättömissä vastasyntyneen aivoissa. Hermostollisten yhteyksien rakenteelliset epämuodostumat heikentävät toiminnallista liittyvyyttä taajuuskohtaisesti tapahtumatasolla. Seuraavaksi me käytimme matemaattisia malleja ja tietokonesimulaatioita yhdistettynä varsinaiseen EEG-mittausdataan analysoidaksemme sähköisen hermostollisen aktiivisuuden leviämistä vastasyntyneen päässä. Tulostemme mukaan vastasyntyneen kallon sähkönjohtavuus on paljon korkeampi kuin aikuisilla ihmisillä. Tämä aiheuttaa aivokuoren signaalien suurempaa paikallista leviämistä päänahkaa kohti, minkä takia vastasyntyneen aivoaktiivisuuden luotettava rekisteröinti vaatii enemmän ja tiheämmin mittauselektrodeja kuin aikuisilla. Lisäksi todistimme, että vastasyntyneen kallon aukileet eivät muodosta erityistä reittiä sähköisen aktiivisuuden leviämiselle, kallon suuren johtavuuden takia. Lopuksi osoitimme, että EEG-mittausasetelman valinta voi vahvasti vaikuttaa ei-päällekkäisen hermostollisen datan mittaustarkkuuteen ja sitä seuraaviin liittyvyysanalyyseihin. Simulaatiomme mukaan suuritiheyksinen EEG-mittauselektrodiasetelma yhdistettynä matemaattisiin muunnoksiin, kuten virtalähdetiheyden (Current Source Density) globaalikeskiarvoon, tarjoavat spatiaalisesti tarkkoja yksityiskohtia alla sijaitsevasta aivokuoren aktiivisuudesta ja voi erottaa selkeästi sekundääristen virtatihentymien osuuden. Lisäksi laadimme selkeät ohjeet kuinka optimoida mittausasetelma eri elektrodimäärille

Modelling neonatal electroencephalogram time series

Creating a model for brain activity is a highly complex task; this is especially true in modelling neonatal electroencephalogram (EEG) signals. Whereas previous work is motivated by improving seizure detection, this research focuses on describing the development of these complicated multivariate signals. Using data collected from inpatients at University College London Hospital at different degrees of prematurity, we propose a model for background and somatosensory response neonatal EEG sig- nals and subsequently make inferences about the observed EEG signals using this model. We construct a univariate model for neonatal EEG by analysing the second order prop- erties of these signals, taking into account time segments which have time-heterogeneous second order properties. To do so we utilise time, frequency and time-frequency domain methods. The presented univariate model is combined with a time domain correlation structure to generate a multivariate representation which is possible, in part, due to the resolution of the data. Furthermore, the parameters and signal components are best described by taking into account not only the age at which testing occurred, but also the age at which an infant was born. This research has attempted to create a model that is not only descriptive of somatosensory responses, but also applicable in other avenues of similar research. We propose to use generalised linear models to describe the age dependence of the ob- served time series, and use these models to simulate EEG observations. When modelling characteristics of the estimated parameters, all models require the age pairing - age at birth and age at test - as variables. Combined with an appropriate time domain corre- lation structure, this allows us to achieve suitable estimates of observed signal structure. The model class presented is a flexible and accurate representation of neonatal back- ground and somatosensory response electroencephalogram signals, and can be used to describe similar multivariate observations

Variability of head tissues’ conductivities and their impact in electrical brain activity research

The presented thesis endeavoured to establish the impact that the variability in electrical conductivity of human head tissues has on electrical brain imaging research, particularly transcranial direct current stimulation (tDCS) and electroencephalography (EEG). A systematic meta-analysis was firstly conducted to determine the consistency of reported measurements, revealing significant deviations in electrical conductivity measurements predominantly for the scalp, skull, GM, and WM. Found to be of particular importance was the variability of skull conductivity, which consists of multiple layers and bone compositions, each with differing conductivity. Moreover, the conductivity of the skull was suggested to decline with participant age and hypothesised to correspondingly impact tDCS induced fields. As expected, the propositioned decline in the equivalent (homogeneous) skull conductivity as a function of age resulted in reduced tDCS fields. A further EEG analysis also revealed, neglecting the presence of adult sutures and deviation in proportion of spongiform and compact bone distribution throughout the skull, ensued significant errors in EEG forward and inverse solutions. Thus, incorporating geometrically accurate and precise volume conductors of the skull was considered as essential for EEG forward analysis and source localisation and tDCS application. This was an overarching conclusion of the presented thesis. Individualised head models, particularly of the skull, accounting for participant age, the presence of sutures and deviation in bone composition distribution are imperative for electrical brain imaging. Additionally, it was shown that in vivo, individualised measurements of skull conductivity are further required to fully understand the relationship between conductivity and participant demographics, suture closure, bone compositions, skull thickness and additional factors