Sleep Spindle-Related EEG Connectivity in Children with Attention-Deficit/Hyperactivity Disorder: An Exploratory Study

Attention-deficit/hyperactivity disorder (ADHD) is a neurobehavioral disorder with known brain abnormalities but no biomarkers to support clinical diagnosis. Recently, EEG analysis methods such as functional connectivity have rekindled interest in using EEG for ADHD diagnosis. Most studies have focused on resting-state EEG, while connectivity during sleep and spindle activity has been underexplored. Here we present the results of a preliminary study exploring spindle-related connectivity as a possible biomarker for ADHD. We compared sensor-space connectivity parameters in eight children with ADHD and nine age/sex-matched healthy controls during sleep, before, during, and after spindle activity in various frequency bands. All connectivity parameters were significantly different between the two groups in the delta and gamma bands, and Principal Component Analysis (PCA) in the gamma band distinguished ADHD from healthy subjects. Cluster coefficient and path length values in the sigma band were also significantly different between epochs, indicating different spindle-related brain activity in ADHD

Simulating human sleep spindle MEG and EEG from ion channel and circuit level dynamics

Although they form a unitary phenomenon, the relationship between extracranial M/EEG and transmembrane ion flows is understood only as a general principle rather than as a well-articulated and quantified causal chain.We present an integrated multiscale model, consisting of a neural simulation of thalamus and cortex during stage N2 sleep and a biophysical model projecting cortical current densities to M/EEG fields. Sleep spindles were generated through the interactions of local and distant network connections and intrinsic currents within thalamocortical circuits. 32,652 cortical neurons were mapped onto the cortical surface reconstructed from subjects' MRI, interconnected based on geodesic distances, and scaled-up to current dipole densities based on laminar recordings in humans. MRIs were used to generate a quasi-static electromagnetic model enabling simulated cortical activity to be projected to the M/EEG sensors.The simulated M/EEG spindles were similar in amplitude and topography to empirical examples in the same subjects. Simulated spindles with more core-dominant activity were more MEG weighted.Previous models lacked either spindle-generating thalamic neural dynamics or whole head biophysical modeling; the framework presented here is the first to simultaneously capture these disparate scales.This multiscale model provides a platform for the principled quantitative integration of existing information relevant to the generation of sleep spindles, and allows the implications of future findings to be explored. It provides a proof of principle for a methodological framework allowing large-scale integrative brain oscillations to be understood in terms of their underlying channels and synapses

Individual spindle detection and analysis in high-density recordings across the night and in thalamic stroke

Sleep spindles are thalamocortical oscillations associated with several behavioural and clinical phenomena. In clinical populations, spindle activity has been shown to be reduced in schizophrenia, as well as after thalamic stroke. Automatic spindle detection algorithms present the only feasible way to systematically examine individual spindle characteristics. We took an established algorithm for spindle detection, and adapted it to high-density EEG sleep recordings. To illustrate the detection and analysis procedure, we examined how spindle characteristics changed across the night and introduced a linear mixed model approach applied to individual spindles in adults (n = 9). Next we examined spindle characteristics between a group of paramedian thalamic stroke patients (n = 9) and matched controls. We found a high spindle incidence rate and that, from early to late in the night, individual spindle power increased with the duration and globality of spindles; despite decreases in spindle incidence and peak-to-peak amplitude. In stroke patients, we found that only left-sided damage reduced individual spindle power. Furthermore, reduction was specific to posterior/fast spindles. Altogether, we demonstrate how state-of-the-art spindle detection techniques, applied to high-density recordings, and analysed using advanced statistical approaches can yield novel insights into how both normal and pathological circumstances affect sleep

Waveform detection by deep learning reveals multi-area spindles that are selectively modulated by memory load

Sleep is generally considered to be a state of large-scale synchrony across thalamus and neocortex; however, recent work has challenged this idea by reporting isolated sleep rhythms such as slow oscillations and spindles. What is the spatial scale of sleep rhythms? To answer this question, we adapted deep learning algorithms initially developed for detecting earthquakes and gravitational waves in high-noise settings for analysis of neural recordings in sleep. We then studied sleep spindles in non-human primate electrocorticography (ECoG), human electroencephalogram (EEG), and clinical intracranial electroencephalogram (iEEG) recordings in the human. Within each recording type, we find widespread spindles occur much more frequently than previously reported. We then analyzed the spatiotemporal patterns of these large-scale, multi-area spindles and, in the EEG recordings, how spindle patterns change following a visual memory task. Our results reveal a potential role for widespread, multi-area spindles in consolidation of memories in networks widely distributed across primate cortex

Brain Activation Time-Locked to Sleep Spindles Associated With Human Cognitive Abilities

Simultaneous electroencephalography and functional magnetic resonance imaging (EEG–fMRI) studies have revealed brain activations time-locked to spindles. Yet, the functional significance of these spindle-related brain activations is not understood. EEG studies have shown that inter-individual differences in the electrophysiological characteristics of spindles (e.g., density, amplitude, duration) are highly correlated with “Reasoning” abilities (i.e., “fluid intelligence”; problem solving skills, the ability to employ logic, identify complex patterns), but not short-term memory (STM) or verbal abilities. Spindle-dependent reactivation of brain areas recruited during new learning suggests night-to-night variations reflect offline memory processing. However, the functional significance of stable, trait-like inter-individual differences in brain activations recruited during spindle events is unknown. Using EEG–fMRI sleep recordings, we found that a subset of brain activations time-locked to spindles were specifically related to Reasoning abilities but were unrelated to STM or verbal abilities. Thus, suggesting that individuals with higher fluid intelligence have greater activation of brain regions recruited during spontaneous spindle events. This may serve as a first step to further understand the function of sleep spindles and the brain activity which supports the capacity for Reasoning

Implication de la connectivité anatomique dans les caractéristiques des fuseaux de sommeil

Le sommeil est un état de conscience distinct de l’éveil et nécessaire à diverses fonctions du cerveau allant de la métabolisation des déchets dans le système nerveux central jusqu’à la plasticité cérébrale, la mémoire et la performance cognitive. Les fuseaux de sommeil (FS), ces oscillations fusiformes ayant une fréquence qui varie entre 12 et 16 Hz, constituent un marqueur de synchronie neuronale principalement observé dans le sommeil lent. Ils font partie de ces oscillations qui ont été associées à la préservation du sommeil, la consolidation en mémoire et à l’intelligence. Les FS montrent une très grande variabilité intra- et interindividuelle quant à leurs caractéristiques, celles-ci étant d’ailleurs influencées par des facteurs tels que l’âge et le sexe. Les mécanismes neurophysiologiques impliqués dans ces variations demeurent toutefois méconnus à ce jour. Il a été démontré que la génération et la propagation des FS dépendent de la communication entre le thalamus et le cortex et reposeraient sur les fibres de matière blanche (MB) du cerveau. Le but de cette thèse est donc d’investiguer l’implication de la connectivité anatomique par l’analyse de la MB du cerveau, dans la variabilité interindividuelle des caractéristiques des FS. Nous évaluerons également si les différences d’âge et de sexe dans les caractéristiques des FS peuvent être expliquées par la MB. La première étude a évalué si l’intégrité de la MB du cerveau pouvait expliquer les changements d’amplitude et de densité des FS au cours du vieillissement. Une meilleure intégrité de la MB dans les principaux faisceaux connectant le thalamus au cortex frontal a été associée à une plus grande amplitude des FS et de l’activité électroencéphalographique dans la bande de fréquences sigma. Ces résultats ont été observés exclusivement chez les sujets jeunes, suggérant que d’autres facteurs pourraient expliquer les changements de FS au cours du vieillissement. La deuxième étude avait, quant à elle, pour but d’évaluer si la longueur des faisceaux de fibres thalamo-corticales (TC) prédisait la variation interindividuelle de la fréquence et de l’amplitude des FS. Il a été démontré que de plus courts faisceaux de fibres entre le thalamus et les régions frontales prédisaient une fréquence des FS plus rapide. De plus, une analyse de médiation a permis de démontrer que la différence sexuelle observée pour la fréquence des FS était complètement expliquée par l’effet indirect du sexe sur la longueur des faisceaux de fibres de MB. Nos résultats suggèrent donc que l’amplitude et la fréquence des FS reflèteraient des aspects spécifiques des projections de MB sous-jacentes à la boucle TC. De fait, l’amplitude des FS a été associée à l’intégrité des connexions neuronales et à la synchronie des décharges électriques alors que la fréquence des FS a été associée au temps requis à l’influx nerveux pour parcourir la boucle TC et à des mesures quantitatives des projections entre le thalamus et le cortex cérébral. Cette thèse propose donc une première hypothèse neuroanatomique tentant d’expliquer les variations interindividuelles et sexuelles des caractéristiques des FS.Sleep is a state of consciousness distinct from waking and necessary in multiple brain functions ranging from the metabolism of waste products in the central nervous system to brain plasticity, memory, and cognition. Sleep spindles (SS), these fusiform oscillations with a frequency which varies between 12 and 16 Hz, constitute a marker of neuronal synchrony prominently observed during non-rapid eye movement sleep. SS are one of these brain oscillations associated with sleep maintenance, memory consolidation, and intelligence. SS characteristics show an important intra- and inter-individual variability, and are known to be affected by factors such as age and sex. However, the neurophysiological mechanisms implicated in this variability are yet to be discovered. The generation and the propagation of SS depend on the communication between the thalamus and the cerebral cortex which rely on white matter (WM) fibre bundles. The goal of this thesis is to investigate the implication of the anatomical connectivity as assessed through WM, in the inter-individual variability of SS characteristics. We will also evaluate whether the age and sex differences in SS characteristics could be explained by the WM. The first study evaluated whether WM integrity could explain age-related changes in SS amplitude and density. Increased WM integrity in the main WM tracts connecting the thalamus to the frontal cortex was associated with an increased SS amplitude and electroencephalographic signal power in the sigma frequency band. These results were observed exclusively in young subjects suggesting that other factors could explain age-related changes in SS. The second study aimed at evaluating whether the length of the thalamo-cortical (TC) fiber bundles would predict the inter-individual variability of SS frequency and amplitude. We found that shorter fiber bundles between the thalamus and the frontal regions of the brain predicted a faster SS frequency. Moreover, a mediation analysis showed that the sex-related differences in SS frequency was completely explained by the indirect effect of sex on the length of the WM fiber bundles. Our results suggest that SS amplitude and frequency reflect specific aspect of the WM projections underlying the TC loop. Indeed, SS amplitude was associated with the integrity of neuronal connections and the synchrony of nerve impulses, whereas SS frequency was associated with the timing of the nerve impulses in the TC loop and to quantitative measures of WM projections between the thalamus and the cerebral cortex. This thesis therefore brings a first neuroanatomical hypothesis in explaining the inter-individual and sex-related variability of SS characteristics

Spatiotemporal characteristics of sleep spindles depend on cortical location

Since their discovery almost one century ago, sleep spindles, 0.5–2 s long bursts of oscillatory activity at 9–16 Hz during NREM sleep, have been thought to be global and relatively uniform throughout the cortex. Recent work, however, has brought this concept into question but it remains unclear to what degree spindles are global or local and if their properties are uniform or location-dependent. We addressed this question by recording sleep in eight patients undergoing evaluation for epilepsy with intracranial electrocorticography, which combines high spatial resolution with extensive cortical coverage. We find that spindle characteristics are not uniform but are strongly influenced by the underlying cortical regions, particularly for spindle density and fundamental frequency. We observe both highly isolated and spatially distributed spindles, but in highly skewed proportions: while most spindles are restricted to one or very few recording channels at any given time, there are spindles that occur over widespread areas, often involving lateral prefrontal cortices and superior temporal gyri. Their co-occurrence is affected by a subtle but significant propagation of spindles from the superior prefrontal regions and the temporal cortices towards the orbitofrontal cortex. This work provides a brain-wide characterization of sleep spindles as mostly local graphoelements with heterogeneous characteristics that depend on the underlying cortical area. We propose that the combination of local characteristics and global organization reflects the dual properties of the thalamo-cortical generators and provides a flexible framework to support the many functions ascribed to sleep in general and spindles specifically