Early development of sleep and brain functional connectivity in term-born and preterm infants

The proper development of sleep and sleep-wake rhythms during early neonatal life is crucial to lifelong neurological well-being. Recent data suggests that infants who have poor quality sleep demonstrate a risk for impaired neurocognitive outcomes. Sleep ontogenesis is a complex process, whereby alternations between rudimentary brain states-active vs. wake and active sleep vs. quiet sleep-mature during the last trimester of pregnancy. If the infant is born preterm, much of this process occurs in the neonatal intensive care unit, where environmental conditions might interfere with sleep. Functional brain connectivity (FC), which reflects the brain's ability to process and integrate information, may become impaired, with ensuing risks of compromised neurodevelopment. However, the specific mechanisms linking sleep ontogenesis to the emergence of FC are poorly understood and have received little investigation, mainly due to the challenges of studying causal links between developmental phenomena and assessing FC in newborn infants. Recent advancements in infant neuromonitoring and neuroimaging strategies will allow for the design of interventions to improve infant sleep quality and quantity. This review discusses how sleep and FC develop in early life, the dynamic relationship between sleep, preterm birth, and FC, and the challenges associated with understanding these processes. Impact Sleep in early life is essential for proper functional brain development, which is essential for the brain to integrate and process information. This process may be impaired in infants born preterm. The connection between preterm birth, early development of brain functional connectivity, and sleep is poorly understood. This review discusses how sleep and brain functional connectivity develop in early life, how these processes might become impaired, and the challenges associated with understanding these processes. Potential solutions to these challenges are presented to provide direction for future research.Peer reviewe

The functional role of dreaming in emotional processes

Dream experience (DE) represents a fascinating condition linked to emotional processes and the human inner world. Although the overlap between REM sleep and dreaming has been overcome, several studies point out that emotional and perceptually vivid contents are more frequent when reported upon awakenings from this sleep stage. Actually, it is well-known that REM sleep plays a pivotal role in the processing of salient and emotional waking-life experiences, strongly contributing to the emotional memory consolidation. In this vein, we highlighted that, to some extent, neuroimaging studies showed that the processes that regulate dreaming and emotional salience in sleep mentation share similar neural substrates of those controlling emotions during wakefulness. Furthermore, the research on EEG correlates of the presence/absence of DE and the results on EEG pattern related to the incorporated memories converged to assign a crucial role of REM theta oscillations in emotional re-processing. In particular, the theta activity is involved in memory processes during REM sleep as well as during the waking state, in line with the continuity hypothesis. Also, the gamma activity seems to be related to emotional processes and dream recall as well as to lucid dreams. Interestingly, similar EEG correlates of DE have been found in clinical samples when nightmares or dreams occur. Research on clinical samples revealed that promoting the rehearsal of frightening contents aimed to change them is a promising method to treat nightmares, and that lucid dreams are associated with an attenuation of nightmares. In this view, DE can defuse emotional traumatic memories when the emotional regulation and the fear extinction mechanisms are compromised by traumatic and frightening events. Finally, dreams could represent a sort of simulation of reality, providing the possibility to create a new scenario with emotional mastery elements to cope with dysphoric items included in nightmares. In addition, it could be hypothesized that the insertion of bizarre items besides traumatic memories might be functional to “impoverish” the negative charge of the experiences

Spotlight on dream recall. The ages of dreams

Brain and sleep maturation covary across different stages of life. At the same time, dream generation and dream recall are intrinsically dependent on the development of neural systems. The aim of this paper is to review the existing studies about dreaming in infancy, adulthood, and the elderly stage of life, assessing whether dream mentation may reflect changes of the underlying cerebral activity and cognitive processes. It should be mentioned that some evidence from childhood investigations, albeit still weak and contrasting, revealed a certain correlation between cognitive skills and specific features of dream reports. In this respect, infantile amnesia, confabulatory reports, dream-reality discerning, and limitation in language production and emotional comprehension should be considered as important confounding factors. Differently, growing evidence in adults suggests that the neurophysiological mechanisms underlying the encoding and retrieval of episodic memories may remain the same across different states of consciousness. More directly, some studies on adults point to shared neural mechanisms between waking cognition and corresponding dream features. A general decline in the dream recall frequency is commonly reported in the elderly, and it is explained in terms of a diminished interest in dreaming and in its emotional salience. Although empirical evidence is not yet available, an alternative hypothesis associates this reduction to an age-related cognitive decline. The state of the art of the existing knowledge is partially due to the variety of methods used to investigate dream experience. Very few studies in elderly and no investigations in childhood have been performed to understand whether dream recall is related to specific electrophysiological pattern at different ages. Most of all, the lack of longitudinal psychophysiological studies seems to be the main issue. As a main message, we suggest that future longitudinal studies should collect dream reports upon awakening from different sleep states and include neurobiological measures with cognitive performance

The correlation between white-matter microstructure and the complexity of spontaneous brain activity: A difussion tensor imaging-MEG study

The advent of new signal processing methods, such as non-linear analysis techniques, represents a new perspective which adds further value to brain signals' analysis. Particularly, Lempel–Ziv's Complexity (LZC) has proven to be useful in exploring the complexity of the brain electromagnetic activity. However, an important problem is the lack of knowledge about the physiological determinants of these measures. Although acorrelation between complexity and connectivity has been proposed, this hypothesis was never tested in vivo. Thus, the correlation between the microstructure of the anatomic connectivity and the functional complexity of the brain needs to be inspected. In this study we analyzed the correlation between LZC and fractional anisotropy (FA), a scalar quantity derived from diffusion tensors that is particularly useful as an estimate of the functional integrity of myelinated axonal fibers, in a group of sixteen healthy adults (all female, mean age 65.56 ± 6.06 years, intervals 58–82). Our results showed a positive correlation between FA and LZC scores in regions including clusters in the splenium of the corpus callosum, cingulum, parahipocampal regions and the sagittal stratum. This study supports the notion of a positive correlation between the functional complexity of the brain and the microstructure of its anatomical connectivity. Our investigation proved that a combination of neuroanatomical and neurophysiological techniques may shed some light on the underlying physiological determinants of brain's oscillation

Non-REM dreaming in relation to the cyclic alternating pattern an exploratory study

Includes bibliographical references.Dreaming is yet to be studied in relation to sleep microstructure. By endeavouring to study mentation in relation to the finer neurophysiological processes underlying the rhythmicity of the sleep cycles, dream science stands to benefit from the wealth of knowledge of these processes. While relationships between dreaming and certain of these processes have been identified in the literature, a comprehensive study of dreaming in relation to all of the recognized components of the sleep microstructure is completely lacking. With this in mind, the main aim of this study was to examine sleep microstructure in relation to dreaming and determine whether there is any relationship between dream recall and the various types of phasic arousal phenomena during NREM sleep, as systematised within the global framework of the cyclic alternating pattern (CAP)

New neurophysiological and imaging methods for detection of microstructural changes in mild traumatic brain injury

Mild traumatic brain injury is a very common health problem. Although outcome is generally good, a significant proportion of patients have persistent symptoms or an incomplete functional recovery. The mechanisms of this are incompletely understood, but believed to include microstructural injuries that may be undetectable by presently used diagnostic tests. This thesis aims at exploring new diagnostic methods that could be utilised in examining mild traumatic brain injury. I study tested transcranial magnetic stimulation defined motor thresholds in a sample of chronic phase mild traumatic brain injury patients. Elevated motor thresholds were found compared to healthy controls, associated with altered excitability of the corticospinal tract. II study used transcranial magnetic stimulation combined with electroencephalography to probe responses of frontal brain regions. The employed method is reported to be sensitive to changes in excitability and connectivity of the brain. Differences were found between samples of fully recovered and persistently symptomatic patients with mild traumatic brain injury and healthy controls. On basis of this, transcranial magnetic stimulation and electroencephalography could be used to detect functional changes that are not paralleled by lesions on routine magnetic resonance imaging. III study compared diffusion tensor imaging based deterministic tractography and a newer method, based on constrained spherical deconvolution, automatic, deep learning based segmentation and probabilistic tractography. Participants were patients with symptomatic mild traumatic brain injury and healthy controls. The newer approach was able to find differences between the groups, while diffusion tensor method was not. This suggests the new approach may be more sensitive in detecting microstructural changes related to mild traumatic brain injury. These results show that mild traumatic brain injury can be associated with functional and structural changes in the absence of trauma-related findings on routine MRI. The methods evaluated may provide new ways to detect these changes.Uusia neurofysiologisia ja kuvantamismenetelmiä lievään aivovammaan liittyvien mikrorakenteellisten muutosten toteamisessa Lievä aivovamma on erittäin tavallinen. Toipuminen on yleensä hyvää, mutta osalle potilaista jää pitkäkestoisia oireita tai toimintakyvyn vajavuutta. Näiden syntymekanismia ei täysin ymmärretä, mutta ajatellaan sen voivan liittyä aivojen mikrorakenteellisiin muutoksiin, joiden toteamiseen nykyiset diagnostiset testit voivat olla riittämättömiä. Tämä väitöstutkimus selvittää uusia keinoja, joita voitaisiin hyödyntää lievän aivovamman arvioinnissa. I osatyössä tutkittiin transkraniaalisen magneettistimulaation avulla motorisia kynnyksiä. Tutkimusjoukkona oli lievän aivovamman saaneita, kroonisen vaiheen potilaita. Potilasjoukolla todettiin terveisiin verrokkeihin nähden korkeampia motorisia kynnyksiä, joka liittyy muutoksiin kortikospinaaliradan ärtyvyydessä. II osatyö hyödynsi transkraniaalista magneettistimulaatiota ja elektroenkefalografiaa frontaalisten aivoalueiden vasteiden tutkimisessa. Aiempien julkaisujen perusteella menetelmä on herkkä aivojen ärtyvyyden ja aivoalueiden välisten yhteyksien muutosten toteamisessa. Menetelmällä löydettiin eroja lievästä aivovammasta oireettomiksi toipuneista, pitkäkestoisesti oireilevista ja terveistä verrokeista koostuneiden osallistujajoukkojen välillä. Transkraniaalisen magneettistimulaation ja elektroenkefalografian yhdistelmällä saatetaan siten havaita toimin-nallisia muutoksia, joille ei ole vastinetta tavallisissa magneettikuvissa. III osatyössä verrattiin diffuusiotensorikuvantamista ja determinististä traktografiaa uudempaan menetelmään, joka perustui constrained spherical deconvolution -laskentaan, automaattiseen, syväoppimiseen perustuvaan segmentaatioon ja probabilistiseen traktografiaan. Tutkimusjoukkona oli lievän aivovamman saaneita, oireisia potilaita ja terveitä verrokkeja. Uudella menetelmällä löydettiin eroja ryhmien välillä, mutta vertailumenetelmällä eroja ei havaittu. Tällä perusteella uusi menetelmä vaikuttaa herkemmältä aivovammaan liittyvien mikrorakenteellisten muutosten toteamisessa. Tulokset osoittavat, että lievään aivovammaan voi liittyä toiminnallisia ja rakenteellisia muutoksia, vaikka tavanomaisen magneettikuvauksen löydös olisi normaali. Näiden muutosten toteaminen voi olla mahdollista arvioiduilla menetelmillä

EEG analytics for early detection of autism spectrum disorder: a data-driven approach

Autism spectrum disorder (ASD) is a complex and heterogeneous disorder, diagnosed on the basis of behavioral symptoms during the second year of life or later. Finding scalable biomarkers for early detection is challenging because of the variability in presentation of the disorder and the need for simple measurements that could be implemented routinely during well-baby checkups. EEG is a relatively easy-to-use, low cost brain measurement tool that is being increasingly explored as a potential clinical tool for monitoring atypical brain development. EEG measurements were collected from 99 infants with an older sibling diagnosed with ASD, and 89 low risk controls, beginning at 3 months of age and continuing until 36 months of age. Nonlinear features were computed from EEG signals and used as input to statistical learning methods. Prediction of the clinical diagnostic outcome of ASD or not ASD was highly accurate when using EEG measurements from as early as 3 months of age. Specificity, sensitivity and PPV were high, exceeding 95% at some ages. Prediction of ADOS calibrated severity scores for all infants in the study using only EEG data taken as early as 3 months of age was strongly correlated with the actual measured scores. This suggests that useful digital biomarkers might be extracted from EEG measurements.This research was supported by National Institute of Mental Health (NIMH) grant R21 MH 093753 (to WJB), National Institute on Deafness and Other Communication Disorders (NIDCD) grant R21 DC08647 (to HTF), NIDCD grant R01 DC 10290 (to HTF and CAN) and a grant from the Simons Foundation (to CAN, HTF, and WJB). We are especially grateful to the staff and students who worked on the study and to the families who participated. (R21 MH 093753 - National Institute of Mental Health (NIMH); R21 DC08647 - National Institute on Deafness and Other Communication Disorders (NIDCD); R01 DC 10290 - NIDCD; Simons Foundation)Published versio

Intracranial high-γ connectivity distinguishes wakefulness from sleep.

Neural synchrony in the γ-band is considered a fundamental process in cortical computation and communication and it has also been proposed as a crucial correlate of consciousness. However, the latter claim remains inconclusive, mainly due to methodological limitations, such as the spectral constraints of scalp-level electroencephalographic recordings or volume-conduction confounds. Here, we circumvented these caveats by comparing γ-band connectivity between two global states of consciousness via intracranial electroencephalography (iEEG), which provides the most reliable measurements of high-frequency activity in the human brain. Non-REM Sleep recordings were compared to passive-wakefulness recordings of the same duration in three subjects with surgically implanted electrodes. Signals were analyzed through the weighted Phase Lag Index connectivity measure and relevant graph theory metrics. We found that connectivity in the high-γ range (90-120 Hz), as well as relevant graph theory properties, were higher during wakefulness than during sleep and discriminated between conditions better than any other canonical frequency band. Our results constitute the first report of iEEG differences between wakefulness and sleep in the high-γ range at both local and distant sites, highlighting the utility of this technique in the search for the neural correlates of global states of consciousness