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Rapid eye movement (REM) sleep is an elusive neural state that is associated with a variety of functions from physiological regulatory mechanisms to complex cognitive processing. REM periods consist of the alternation of phasic and tonic REM microstates that differ in spontaneous and evoked neural activity. Although previous studies indicate, that cortical and thalamocortical activity differs across phasic and tonic microstates, the characterization of neural activity, particularly in subcortical structures that are critical in the initiation and maintenance of REM sleep is still limited in humans. Here, we examined electric activity patterns of the anterior nuclei of the thalamus as well as their functional connectivity with scalp EEG recordings during REM microstates and wakefulness in a group of epilepsy patients (N = 12, 7 females). Anterothalamic local field potentials (LFPs) showed increased high-α and β frequency power in tonic compared with phasic REM, emerging as an intermediate state between phasic REM and wakefulness. Moreover, we observed increased thalamocortical synchronization in phasic compared with tonic REM sleep, especially in the slow and fast frequency ranges. Wake-like activity in tonic REM sleep may index the regulation of arousal and vigilance facilitating environmental alertness. On the other hand, increased thalamocortical synchronization may reflect the intrinsic activity of frontolimbic networks supporting emotional and memory processes during phasic REM sleep. In sum, our findings highlight that the heterogeneity of phasic and tonic REM sleep is not limited to cortical activity, but is also manifested by anterothalamic LFPs and thalamocortical synchronization. SIGNIFICANCE STATEMENT REM sleep is a heterogeneous sleep state that features the alternation of two microstates, phasic and tonic rapid eye movement (REM). These states differ in sensory processing, awakening thresholds, and cortical activity. Nevertheless, the characterization of these microstates, particularly in subcortical structures is still limited in humans. We had the unique opportunity to examine electric activity patterns of the anterior nuclei of the thalamus (ANTs) as well as their functional connectivity with scalp EEG recordings during REM microstates and wakefulness. Our findings show that the heterogeneity of phasic and tonic REM sleep is not limited to cortical activity, but is also manifested in the level of the thalamus and thalamocortical networks.

Sleep EEG reflects instantaneous voltage differences relative to a reference, while its spectrum reflects the degree to which it is comprised of oscillations at various frequencies. In contrast, the envelope of the sleep EEG reflects the instantaneous amplitude of oscillations at specific frequencies, and its spectrum reflects the rhythmicity of the occurrence of these oscillations. The ordinary sleep EEG and its spectrum have been extensively studied and its individual stability and relationship to various demographic characteristics, psychological traits and pathologies is well known. In contrast, the envelope spectrum has not been extensively studied before. In two studies, we explored the generating mechanisms and utility of studying the envelope of the sleep EEG. First, we used human invasive data from cortex-penetrating microelectrodes and subdural grids to demonstrate that the sleep EEG envelope spectrum reflects local neuronal firing. Second, we used a large database of healthy volunteers to demonstrate that the scalp EEG envelope spectrum is highly stable within individuals, especially in NREM sleep, and that it is affected by age and sex. Multivariate models based on a learning algorithm could predict both age (r=0.6) and sex (r=0.5) with considerable accuracy from the EEG envelope spectrum. With age, oscillations characteristically shifted from a 4-5 second rhythm to higher rhythms. The envelope spectrum was not associated with general cognitive ability (IQ). Our results demonstrate that the sleep envelope spectrum is a promising, neuronal firing-based biomarker of various demographic and disease-related phenotypes.

We report on a peculiar way of chronic cognitive impairment associated with interictal epileptic activity during NREM sleep. We review three major groups of epilepsy: mesiotemporal epilepsy (MTLE) involving the epileptic derailment of the hippocampal declarative memory system; childhood developmental epileptic encephalopathies; and the spectrum disorders of the perisylvian communication network with the centrotemporal spike phenomenon, overarching child- and adulthood epilepsies, totaling up the majority of epilepsies in childhood. We outline high impact research-lines on the cognitive harm of epilepsy; causing specific or global cognitive decline through its interference with sleep plastic functions. We highlight the key role of interictal activity in the development of cognitive impairment and the fact that we are unarmed against this harm, antiepileptic pharmaco-therapy being ineffective against the interictal process marked by spikes and high frequency oscillations.

Sleep spindles are major oscillatory components of Non-Rapid Eye Movement (NREM) sleep, reflecting hyperpolarization-rebound sequences of thalamocortical neurons, the inhibition of which is caused by the NREM-dependent activation of GABAergic neurons in the reticular thalamic nucleus. Reports suggest a link between sleep spindles and several forms of interictal epileptic discharges (IEDs) which are considered as expressions of pathological off-line neural plasticity in the central nervous system. Here we investigated the relationship between thalamic sleep spindles, IEDs and ripples in the anterior and mediodorsal nuclei (ANT and MD) of epilepsy patients. Whole-night LFP from the ANT and MD were co-registered with scalp EEG/polysomnography by using externalized leads in 15 epilepsy patients undergoing Deep Brain Stimulation protocol. Slow (∼12 Hz) and fast (∼14 Hz) sleep spindles were present in the human ANT and MD. Roughly, one third of thalamic sleep spindles were associated with IEDs or ripples. Both IED- and ripple-associated spindles were longer than pure spindles. IED-associated thalamic sleep spindles were characterized by broadband increase in thalamic and cortical activity, both below and above the spindle frequency range, whereas ripple-associated thalamic spindles exceeded pure spindles in terms of 80–200 Hz thalamic, but not cortical activity as indicated by time-frequency analysis. These result show that thalamic spindles coupled with IEDs are reflected at the scalp slow and beta-gamma oscillation as well. IED density during sleep spindles in the MD, but not in the ANT was identified as correlates of years spent with epilepsy, whereas no signs of pathological processes were correlated with measures of ripple and spindle association. Furthermore, the density of ripple-associated sleep spindles in the ANT showed a positive correlation with general intelligence. Our findings indicate the complex and multifaceted role of the human thalamus in sleep spindle-related physiological and pathological neural plasticity.

Features of sleep were shown to reflect aging, typical sex differences and cognitive abilities of humans. However, these measures are characterized by redundancy and arbitrariness. Our present approach relies on the assumptions that the spontaneous human brain activity as reflected by the scalp-derived electroencephalogram (EEG) during non-rapid eye movement (NREM) sleep is characterized by arrhythmic, scale-free properties and is based on the power law scaling of the Fourier spectra with the additional consideration of the rhythmic, oscillatory waves at specific frequencies, including sleep spindles. Measures derived are the spectral intercept and slope, as well as the maximal spectral peak amplitude and frequency in the sleep spindle range, effectively reducing 191 spectral measures to 4, which were efficient in characterizing known age-effects, sex-differences and cognitive correlates of sleep EEG. Future clinical and basic studies are supposed to be significantly empowered by the efficient data reduction provided by our approach.

The aim of this review is to summarize and discuss the strong bond between NREM sleep and epilepsy underlain by the shared link and effect on brain plasticity. Beyond the seizure occurrence rate, sleep relatedness may manifest in the enhancement of interictal epileptic discharges (spikes and pathological ripples). The number of the discharges as well as their propagation increase during NREM sleep, unmasking the epileptic network that is hidden during wakefulness. The interictal epileptic discharges associate with different sleep constituents (sleep slow waves, spindling and high frequency oscillations); known to play essential role in memory and learning. We highlight three major groups of epilepsies, in which sleep-related plastic functions suffer an epileptic derailment. In absence epilepsy mainly involving the thalamo-cortical system, sleep spindles transform to generalized spike-wave activity. In mesio-temporal epilepsy affecting the hippocampal declarative memory system, the sharp wave ripples derail to dysfunctional epileptic oscillations (spikes and pathological ripples). Idiopathic childhood epilepsies affecting the perisylvian network may progress to catastrophic status electricus during NREM sleep. In these major epilepsies, NREM sleep has a pivotal role in the development and course of the disorder. Epilepsy is born in-, and exhibits its pathological properties during NREM sleep. Interictal discharges are important causative agents in this process.

Slow waves recorded with EEG in NREM sleep are indicative of the strength and spatial extent of synchronized firing in neuronal assemblies of the cerebral cortex. Slow waves often appear in the A1 part of the cyclic alternating patterns (CAP), which correlate with a number of behavioral and biological parameters, but their physiological significance is not adequately known. We automatically detected slow waves from the scalp recordings of 37 healthy patients, visually identified CAP A1 events and compared slow waves during CAP A1 with those during NCAP. For each slow wave, we computed the amplitude, slopes, frequency, synchronization (synchronization likelihood) between specific cortical areas, as well as the location of origin and scalp propagation of individual waves. CAP A1 slow waves were characterized by greater spatial extent and amplitude, steeper slopes and greater cortical synchronization, but a similar prominence in frontal areas and similar propagation patterns to other areas on the scalp. Our results indicate that CAP A1 represents a period of highly synchronous neuronal firing over large areas of the cortical mantle. This feature may contribute to the role CAP A1 plays in both normal synaptic homeostasis and in the generation of epileptiform phenomena in epileptic patients.

Females and males differ in several features of their spindle oscillations, as well as in the hemispheric lateralization of their neurocognitive processes. In addition, the hemispheric lateralization of cognitive functions was shown to vary in an age-dependent manner. In spite of the above knowledge, data on the hemispheric lateralization of these oscillatory phenomena are scarce and no sex differences or age effects in the hemispheric lateralization of sleep spindles were reported. Here, we aim to fill this gap by the description of the hemispheric lateralization of sleep spindles in healthy human subjects. Data sets from three research groups were unified (N = 251, age range: 4−69 years, 122 females) in this retrospective multicenter study. The amplitude, density, and duration of slow (frontally dominant) and fast (centroparietally dominant) spindles were analyzed using the individual adjustment method. Hemispheric lateralization was quantified by the (L − R)/mean (L, R) index. Orbitofronto-temporo-occi...

Sleep spindles are generated in thalamocortical, corticothalamic and possibly cortico-cortical circuits. Previous hypotheses suggested that slow and fast spindles or spindles with various spatial extent may be generated in different circuits with various cortical laminar innervation patterns. We used NREM sleep EEG data recorded from four human epileptic patients undergoing presurgical electrophysiological monitoring with subdural electrocorticographic grids (ECoG) and implanted laminar microelectrodes penetrating the cortex (IME). The position of IME electrodes within cortical layers was confirmed using postsurgical histological reconstructions. Many micro-domain spindles detected on the IME occurred only in one layer and were absent from the ECoG, but with increasing amplitude simultaneous detection in other layers and on the ECoG became more likely. Macro-domain spindles sufficiently large to be detected on the ECoG were in contrast usually accompanied by IME spindles. Neither micro-domain nor macro-domain spindle cortical profiles were strongly associated with sleep spindle frequency or globality. Multiple-unit and single-unit activity during spindles, however, was heterogeneous across spindle types, but also across layers and subjects. Our results indicate that extremely local spindles may occur in any cortical layer, but co-occurrence at other locations becomes likelier with increasing amplitude and the relatively large spindles detected on ECoG channels have a stereotypical laminar profile. We found no compelling evidence that different spindle types are associated with different laminar profiles, suggesting that they are generated in cortical and thalamic circuits with similar cortical innervation patterns. Local neuronal activity is a stronger candidate mechanism for driving functional differences between spindles subtypes.

Slow wave sleep (SWS) is characterized by the predominance of delta waves and slow oscillations, reflecting the synchronized activity of large cortical neuronal populations. Amongst other functions, SWS plays a crucial role in the restorative capacity of sleep. Rhythmic acoustic stimulation (RAS) during SWS has been shown a cost-effective method to enhance slow wave activity. Slow wave activity can be expressed in a region-specific manner as a function of previous waking activity. However, it is unclear whether slow waves can be enhanced in a region-specific manner using RAS. We investigated the effects of unilaterally presented rhythmic acoustic sound patterns on sleep electroencephalographic (EEG) oscillations. Thirty-five participants received during SWS 12-second long rhythmic bursts of pink noise (at a rate of 1 Hz) that alternated with non-stimulated, silent periods, unilaterally delivered into one of the ears of the participants. As expected, RAS enhanced delta power, especially in its low-frequency components between 0.75 and 2.25 Hz. However, increased slow oscillatory activity was apparent in both hemispheres regardless of the side of the stimulation. The most robust increases in slow oscillatory activity appeared during the first 3-4 seconds of the stimulation period. Furthermore, a short-lasting increase in theta and sigma power was evidenced immediately after the first pulse of the stimulation sequences. Our findings indicate that lateralized RAS has a strong potential to globally enhance slow waves during daytime naps. The lack of localized effects suggests that slow waves are triggered by the ascending reticular system and not directly by specific auditory pathways.

Slow-wave activity is a hallmark of deep non-rapid eye movement sleep. Scalp slow wave morphology is stereotypical and it is highly correlated with the synchronized onset and cessation of cortical neuronal firing measured from the surface or depth of the cortex. It is also strongly affected by aging, and these changes are causally associated with age-related cognitive decline. We investigated how normal aging affects the individual morphology of the slow wave and whether these changes are captured by the summary slow wave parameters generally used in the literature. We recorded full-night polysomnography in 176 participants (age 17–69 years) and automatically detected slow waves. We established individual slow morphologies using average amplitude at 501 data points for each participant and also calculated the individual average slow-wave amplitude, average ascending and descending slope steepness, halfwave duration, and the total number of slow waves (gross parameters). Using least absolute shrinkage and selection operator penalized regression, we found that SW gross parameters explain up to 60% of age variance but using fine morphology up to 80% of age variance can be accounted for. This predictive power was greatest when data from multiple channels were averaged, in midline derivations and in the first quarter of the night. Young participants had faster slow-wave polarity reversals, suggesting a more efficient initiation and termination of slow-wave downstate and upstate. Our results demonstrate the superiority of the high-resolution slow wave morphology as a biomarker of aging and highlight downstate-upstate transitions as promising targets of restorative stimulation-based interventions.

Epileptiform activity in various but not all epilepsy and recording types and cerebral areas is more frequent in NREM sleep, and especially during sleep periods with high-amplitude EEG slow waves. Slow waves synchronize high-frequency oscillations: physiological activity from the theta through the gamma band usually appears during scalp-positive upstates while epileptiform activity occurs at transitory phases and the scalp-negative downstate. It has been proposed that interictal discharges (IIDs) are facilitated by the high degree of neuronal firing synchrony during slow wave transitory and downstates. This would suggest that their occurrence increases as a function of slow wave synchronization, indicated by greater amplitude, steeper slopes and higher EEG signal synchronization. We investigated the occurrence of IIDs during NREM sleep slow waves in epileptic patients undergoing presurgical electrophysiological monitoring. Intracranially registered IIDs preferentially occurred during the scalp-negative downstates of frontal scalp slow waves in all subjects. IID occurrence was more frequent during larger slow waves in the pooled sample and a subset of subjects. However, slow wave slope steepness and EEG signal synchronization between two frontal scalp channels was not significantly associated with IID occurrence. Our results indicate that IIDs indeed do not occur at the same slow wave phase as physiological rhythms, but contrary to previous hypotheses their occurrence is not strongly affected by EEG synchronization.

Non-rapid eye movement (NREM) sleep is characterized by recurring transient events (Cyclic Alternating Patterns, CAP), some of which consist of increased slow wave activity (A1 subtype). Such transient slow-wave events may play an important role in NREM sleep regulation and are known to facilitate epileptiform activity. In our study we investigated the relationship between interictal spike activity and Cyclic Alternating Patterns in three epileptic patients, using simultaneous scalp electroencephalogram (EEG) recording and intracranial electrocorticography. A significant increase of interictal activity was found during CAP A1 subtypes. A positive correlation between scalp EEG delta power and spike activity was found only in CAP A1 subtypes, but not during other events. These results show that transient (but not subcontinuous) delta activity has a facilitating effect on epileptoform activity, also suggesting a functional dissociation between morphologically similar delta activities.

Sleep spindles are frequently studied for their relationship with state and trait cognitive variables, and they are thought to play an important role in sleep-related memory consolidation. Due to their frequent occurrence in NREM sleep, the detection of sleep spindles is only feasible using automatic algorithms, of which a large number is available. We compared subject averages of the spindle parameters computed by a fixed frequency (FixF) (11-13 Hz for slow spindles, 13-15 Hz for fast spindles) automatic detection algorithm and the individual adjustment method (IAM), which uses individual frequency bands for sleep spindle detection. Fast spindle duration and amplitude are strongly correlated in the two algorithms, but there is little overlap in fast spindle density and slow spindle parameters in general. The agreement between fixed and manually determined sleep spindle frequencies is limited, especially in case of slow spindles. This is the most likely reason for the poor agreement between the two detection methods in case of slow spindle parameters. Our results suggest that while various algorithms may reliably detect fast spindles, a more sophisticated algorithm primed to individual spindle frequencies is necessary for the detection of slow spindles as well as individual variations in the number of spindles in general.

Sleep spindles are generated in thalamocortical circuits. Thalamocortical projections can be classified as one of two main types: a “core” network consisting of spatially concentrated projections terminating in cortical layer IV, and a “matrix” network with more diffuse projections, terminating in the superficial cortical layers. It has been hypothesized that sleep spindles can be generated in both systems, but localized spindles are preferentially generated in the “core” system and global spindles in the “matrix system”. Our analysis of laminar microelectrode recordings during ECoG spindles indeed reveals that current source density (CSD) is maximal in layer I-II and IV, consistent with the anatomy of the hypothesized “core” and “matrix” networks. However, CSD is prominent at both depths in both local and global spindles, and CSD magnitude is strongly correlated between superficial layers and layer IV (although less so in local spindles). Fast spindles slow relatively greater CSD in layer IV and slow spindles in superficial layers. Sleep spindles are associated with several neurobehavioral markers, such as memory consolidation, cognitive ability and disease phenotypes. These associations, however, were mainly found with fast spindles. Centroparietal fast spindles also appear more prominently in EEG recordings and leave more prominent spectral peaks. While neither slow nor fast spindles rely exclusively on both “core” and “matrix” thalamocortical projections, it is likely that spatially focused “core” projections to layer IV are especially significant for sleep spindle function due to their role in fast spindle generation.

NREM sleep slow waves reflect both the temporal dynamics of the synchronized onset and cessation of cortical neuron firing and the spatial extent of this synchronized firing pattern. This synchronization is crucially dependent on synaptic strength, and the renormalization of synaptic changes occurring in wakefulness is thought to be one of the main functions of NREM sleep. In line with this hypothesis, slow waves are more frequent, larger and steeper in cases when the synaptic load is high and the need for homeostatic synaptic renormalization is strong: early in the night, in younger subjects with greater neural plasticity and after prolonged or more intensive wakefulness. Slow waves exhibit substantial heterogeneity and may contribute to these processes to a differing degree. In NREM sleep, series of large-amplitude slow waves (Cyclic Alternating Pattern [CAP] A1) sometimes appear, either spontaneously with predictably cyclicity or after sensory stimulation. Slow waves in CAP A1 resemble slow waves normally recorded under high homeostatic sleep pressure: they are characterized by a greater spatial extent, larger amplitude, steeper slopes (even when correcting for amplitude) and higher EEG synchronization, even though their topography and propagation patterns are similar to ordinary (non-CAP) slow waves. These results indicate that CAP A1 represents a period of highly synchronous neuronal firing over large areas of the cortical mantle. This feature may contribute to the role CAP A1 plays in both normal synaptic homeostasis and – through greater synchronization – in the generation of epileptiform phenomena in epileptic patients.

Introduction Sleep spindles are generated in thalamo-cortical networks. Thalamo-cortical projections include core projections to middle and matrix projections to superficial cortical layers. It has been proposed that sleep spindles can be generated in either of these networks. Materials and methods We used electrophysiological data recorded with subdural grid and intracortical multielectrodes in five therapy-resistant epileptic patients undergoing invasive monitoring. Spindles were detected automatically in electrocorticography channels and detection-triggered laminar microelectrode recordings were analyzed. The second spatial derivative of spindle-band filtered (band pass 10–16 Hz, 96 dB) local field potential data allowed to approximate the laminar distribution of the transmembrane generators (current source density, CSD) of spindles. The information regarding the concurrent population cellular activity was obtained by applying a high frequency band filter (500–5000 Hz, 48 dB) on epoched data. Based on the histological reconstructions of laminar electrode tracks, we could identify the precise laminar localization of current sources and sinks. Results Results indicate highly heterogeneous intracortical local field potentials during sleep spindles, and maximum CSD in layer I, II and IV. Multi-unit activity was increased in spindle troughs as it was identified based on the spindle band filtered local field potentials. The single unit analyis revealed preferential firing of most neurons during the positive-negative phase transition of spindles. Conclusions The results confirm that both core and matrix thalamocortical projections contribute to spindle generation, but most spindles appear to be generated by a combination of the two and only a small minority by only one or the other. Neuronal firing tracks the phase of spindles in corticographic channels. Supported by KTIA_NAP_13-1-2013-0001.

Introduction Deep brain stimulation of anterior nucleus of the thalamus (ANT-DBS) is an approved therapeutic approach for drug resistant epilepsy. Little is known about the participation of ANT in epileptic and sleep EEG processes. The appearance of the sleep spindles (SS) is related to interictal discharges (IID), and thalamus is considered as the generator of SSs, however, according to animal data, ANT do not participate in the genesis of sleep spindles. Methods In this present study we included 10 ANT-DBS bitemporal epilepsy patients with externalised leads and surface electrodes undergoing 2 days video-EEG monitoring (VEM). We investigated IIDs, ictal events (IE) and SSs in ANT and also in surface EEG recordings. IIDs and IEs were analysed by visual inspection, SSs were detected according to the patient own special spindle frequency, separately on the scalp (Fp1-2, F3-4, F7-8) and thalamus both sides. SS spectral peak frequency and synchronization between scalp and ANT was measured. Results IIDs appeared in the thalamus and on the scalp both dependent and independent manner. Three patients had seizures during VEM. Seizures did not start but start spread to the ANT electrodes. The slow, frontal type of SSs were prevailing in the ANT. Conclusion ANT participates in both sleep and epileptogenic processes. It seems that IIDs and IE spread to the ANT. Frontal, slow frequency SSs has local sources int he ANT indication its participation in sleep processes. Further evaluation for seizure outcome of ANT-DBS therapy and correlation with ANT recordings are underway.

Evidence supports the intricate relationship between sleep electroencephalogram (EEG) spindling and cognitive abilities in children and adults. Although sleep EEG changes during adolescence index fundamental brain reorganization, a detailed analysis of sleep spindling and the spindle-intelligence relationship was not yet provided for adolescents. Therefore, adolescent development of sleep spindle oscillations were studied in a home polysomnographic study focusing on the effects of chronological age and developmentally acquired overall mental efficiency (fluid IQ) with sex as a potential modulating factor. Subjects were 24 healthy adolescents (12 males) with an age range of 15-22 years (mean: 18 years) and fluid IQ of 91-126 (mean: 104.12, Raven Progressive Matrices Test). Slow spindles (SSs) and fast spindles (FSs) were analyzed in 21 EEG derivations by using the individual adjustment method (IAM). A significant age-dependent increase in average FS density (r = 0.57; p = 0.005) was found. Moreover, fluid IQ correlated with FS density (r = 0.43; p = 0.04) and amplitude (r = 0.41; p = 0.049). The latter effects were entirely driven by particularly reliable FS-IQ correlations in females [r = 0.80 (p = 0.002) and r = 0.67 (p = 0.012), for density and amplitude, respectively]. Region-specific analyses revealed that these correlations peak in the fronto-central regions. The control of the age-dependence of FS measures and IQ scores did not considerably reduce the spindle-IQ correlations with respect to FS density. The only positive spindle-index of fluid IQ in males turned out to be the frequency of FSs (r = 0.60, p = 0.04). Increases in FS density during adolescence may index reshaped structural connectivity related to white matter maturation in the late developing human brain. The continued development over this age range of cognitive functions is indexed by specific measures of sleep spindling unraveling gender differences in adolescent brain maturation and perhaps cognitive strategy.

Contains fulltext : 136083.pdf (Publisher’s version ) (Open Access) Sleep spindles are thalamocortical oscillations in nonrapid eye movement sleep, which play an important role in sleep-related neuroplasticity and offline information processing. Sleep spindle features are stable within and vary between individuals, with, for example, females having a higher number of spindles and higher spindle density than males. Sleep spindles have been associated with learning potential and intelligence; however, the details of this relationship have not been fully clarified yet. In a sample of 160 adult human subjects with a broad IQ range, we investigated the relationship between sleep spindle parameters and intelligence. In females, we found a positive age-corrected association between intelligence and fast sleep spindle amplitude in central and frontal derivations and a positive association between intelligence and slow sleep spindle duration in all except one derivation. In males, a negative association between intelligence and fast spindle density in posterior regions was found. Effects were continuous over the entire IQ range. Our results demonstrate that, although there is an association between sleep spindle parameters and intellectual performance, these effects are more modest than previously reported and mainly present in females. This supports the view that intelligence does not rely on a single neural framework, and stronger neural connectivity manifesting in increased thalamocortical oscillations in sleep is one particular mechanism typical for females but not males. 11 p.