The associations between spindle characteristics and cognitive ability in a large adolescent birth cohort

Season is related to the slow wave and sigma activity of infants and toddlers

OBJECTIVE/BACKGROUND

Slow wave activity (SWA) and sigma frequency activity (SFA) are hallmarks of NREM sleep EEG and important indicators of neural plasticity, development of the central nervous system, and cognition. However, little is known about the factors that modulate these sleep EEG activities, especially in small children.

PATIENTS/METHODS

We analyzed the power spectral densities of SWA (1-4 Hz) and SFA range (10-15 Hz) from six EEG derivations of 56 infants (8 months) and 60 toddlers (24 months) during their all-night sleep and during the first and the last half of night sleep. The spectral values were compared between the four seasons.

RESULTS

In the spring group of infants, compared with the darker seasons, SFA was lower in the centro-occipital EEG derivations during both halves of the night. The SWA findings of the infants were restricted to the last half of the night (SWA2) and frontally, where SWA2 was higher during winter than spring. The toddlers presented less frontal SWA2 during winter compared with autumn. Both age groups showed a reduction in both SWA and SFA towards the last half of the night.

CONCLUSIONS

The sleep EEG spectral power densities are more often associated with seasons in infants' SFA range. The results might stem from seasonally changing light exposure, but the exact mechanism warrants further study. Moreover, contrary to the adult-like increment of SFA, the SFA at both ages was lower at the last part of the night sleep. This suggests different regulation of spindle activity in infants and toddlers.

Optimal spindle detection parameters for predicting cognitive performance

STUDY OBJECTIVES

Alterations in sleep spindles have been linked to cognitive impairment. This finding has contributed to a growing interest in identifying sleep-based biomarkers of cognition and neurodegeneration, including sleep spindles. However, flexibility surrounding spindle definitions and algorithm parameter settings present a methodological challenge. The aim of this study was to characterize how spindle detection parameter settings influence the association between spindle features and cognition and to identify parameters with the strongest association with cognition.

METHODS

Adult patients (n = 167, 49 ± 18 years) completed the NIH Toolbox Cognition Battery after undergoing overnight diagnostic polysomnography recordings for suspected sleep disorders. We explored 1000 combinations across seven parameters in Luna, an open-source spindle detector, and used four features of detected spindles (amplitude, density, duration, and peak frequency) to fit linear multiple regression models to predict cognitive scores.

RESULTS

Spindle features (amplitude, density, duration, and mean frequency) were associated with the ability to predict raw fluid cognition scores (r = 0.503) and age-adjusted fluid cognition scores (r = 0.315) with the best spindle parameters. Fast spindle features generally showed better performance relative to slow spindle features. Spindle features weakly predicted total cognition and poorly predicted crystallized cognition regardless of parameter settings.

CONCLUSIONS

Our exploration of spindle detection parameters identified optimal parameters for studies of fluid cognition and revealed the role of parameter interactions for both slow and fast spindles. Our findings support sleep spindles as a sleep-based biomarker of fluid cognition.

The relationship between cognitive ability and BOLD activation across sleep-wake states

The sleep spindle, a waxing and waning oscillation in the sigma frequency range, has been shown to correlate with fluid intelligence; i.e. the ability to use logic, learn novel rules/patterns, and solve problems. Using simultaneous EEG and fMRI, we previously identified the neural correlates of this relationship, including activation of the thalamus, bilateral putamen, medial frontal gyrus, middle cingulate cortex, and precuneus. However, research to date has focussed primarily on non-rapid eye movement (NREM) sleep, and spindles per se, thus overlooking the possibility that brain activity that occurs in other sleep-wake states might also be related to cognitive abilities. In our current study, we sought to investigate whether brain activity across sleep/wake states is also related to human intelligence in N = 29 participants. During NREM sleep, positive correlations were observed between fluid intelligence and blood oxygen level dependent (BOLD) activations in the bilateral putamen and the paracentral lobule/precuneus, as well as between short-term memory (STM) abilities and activity in the medial frontal cortex and inferior frontal gyrus. During wake, activity in bilateral postcentral gyri and occipital lobe was positively correlated with short-term memory abilities. In participants who experienced REM sleep in the scanner, fluid intelligence was positively associated with midbrain activation, and verbal intelligence was associated with right postcentral gyrus activation. These findings provide evidence that the relationship between sleep and intellectual abilities exists beyond sleep spindles.

Sleep Spindle Features and Neurobehavioral Performance in Healthy School-Aged Children

PURPOSE

In adults, central fast-frequency sleep spindles are involved in learning and memory functions. The density of local spindles is higher than global spindles, emphasizing the importance of local plastic neural processes. In children, findings on the association of spindles with cognition are more variable. Hence, we aim to study whether the local spindles are also important for neurobehavioral performance in children.

METHODS

We studied the correlations between local (occurring in only one channel: Fp1, Fp2, C3, or C4), bilateral, and diffuse (occurring in all four channels) spindles and neurobehavioral performance in 17 healthy children (median age 9.6 years).

RESULTS

Local spindles were not as frequent as bilateral spindles (P-values < 0.05). Central spindle types had significant correlations with sensorimotor and language functions (e.g., the density of bilateral central spindles correlated positively with the Object Assembly in NEPSY, r = 0.490). Interestingly, frontopolar spindles correlated with behavior (e.g., the more bilateral the frontopolar spindles, the less hyperactive the children, r = -0.618).

CONCLUSIONS

In children, the local spindles, but also more widespread central spindles, seem to be involved in the cognitive processes. Based on our findings, it is important that ageadjusted frequency limits are used in studies evaluating the frequencies of spindles in children.

The protective effect of daytime sleep on planning and risk-related decision-making in emerging adults

We assessed the effect of a daytime sleep opportunity on planning and risk-related decision-making in emerging adults using multiple neurobehavioral assessments. A total of 136 healthy emerging adults (20.0 ± 1.5 years), 65% female, performed the Risky-Gains Task and the Tower of London test twice. Between these assessments, they were randomized to either have a sleep opportunity monitored by polysomnography (Sleep group, n = 101) or to stay awake (Wake group, n = 35). During Test 2, in comparison to the Sleep group, the Wake group showed increased sleepiness, worse planning ability and more decrease in reaction times when selecting risky choices. Changes in Tower of London test steps used and Risky-Gains Task response time correlated with the number of central and frontal fast sleep spindles, respectively. These results indicate that among emerging adults who commonly have poor sleep patterns, a daytime sleep opportunity was related to better planning ability, better psychomotor vigilance and stable response speeds in risk-related decision-making. Changes in planning and risk-related decision-making correlated with the number of sleep spindles during the nap, supporting a specific role for sleep in modulating planning and potentially other higher-order cognitive functions.

The association between sleep-wake ratio and overnight picture recognition is moderated by BDNF genotype

A wealth of studies supports the role of sleep in memory performance. Experimentally controlled studies indicate that prolonged wake after memory encoding is detrimental for memory outcome whereas sleep protects from wake-time interference and promotes memory consolidation. We examined how the natural distribution of wake and sleep between encoding and retrieval associated with overnight picture recognition accuracy among 161 adolescents following their typical sleep schedule with an in-home polysomnography. The memorized pictures varied in their level of arousal (calm to exciting) and valence (negative to positive). Suspecting genotypic influence on the sensitivity for sleep/wake dynamics, we also assessed if these associations were affected by known gene polymorphisms involved in neural plasticity and sleep homeostasis: brain-derived neurotrophic factor (BDNF) Val66Met and Catechol-O-methyltransferase (COMT) Val158Met. In the whole sample, overnight recognition accuracy was associated with the levels of arousal and valence of the pictures, but not with sleep percentage (i.e. the percentage of time spent asleep between memory encoding and retrieval). While the allelic status of BDNF or COMT did not have any main effect on recognition accuracy, a significant moderation by BDNF Val66Met was found (p = .004): the subgroup homozygous for valine allele showed positive association between sleep percentage and recognition accuracy. This was underlain by detrimental influence of wake, rather than by any memory benefit of sleep. Our results complement the mounting evidence that the relation between sleep and memory performance is moderated by BDNF Val66Met. Further studies are needed to clarify the specific mechanisms.

Slow-wave activity and sigma activities are associated with psychomotor development at 8 months of age

STUDY OBJECTIVES

The electrophysiological properties of non-rapid eye movement sleep (NREM) EEG are homeostatically modulated on global and local use-dependent levels. Furthermore, the local NREM quality reflects age-dependent brain maturation and individual, age-independent, and psychomotor potential. Cortical maturation and its electrophysiological marker, Slow-wave activity (SWA), as well as sleep spindles are known to change in topography and quality during the early years of life, but their associations with psychomotor development in infants are unknown. Therefore, we aimed to evaluate the local properties of SWA and spindles (sigma power) and ascertain whether they correlate with psychomotor development in 8-month-old infants.

METHODS

Ambulatory polysomnographies were recorded in 56 infants at 8 months of age to calculate the local SWA and sigma powers. The associations between the SWA and sigma powers and psychomotor development (Bayley-III) were examined in 36 of these infants.

RESULTS

In both hemispheres, the highest SWA and sigma powers were found occipitally and centrally, respectively, with higher powers in the right hemisphere than in the left. The Bayley-III correlated with local SWA and sigma powers: the occipital SWA and centro-occipital sigma correlated with cognitive scales, and the frontal and occipital SWA and centro-occipital sigma correlated with language and fine motor scales. Most of the correlations were unilateral.

CONCLUSIONS

In 8-month-old infants, the NREM sleep quality shows local differences that are mostly attributable to the topical phase of brain maturation. The local NREM parameters correlate with psychomotor development.

Analyzing human sleep EEG: A methodological primer with code implementation

Recent years have witnessed a surge in human sleep electroencephalography (EEG) studies, employing increasingly sophisticated analysis strategies to relate electrophysiological activity to cognition and disease. However, properly calculating and interpreting metrics used in contemporary sleep EEG requires attention to numerous theoretical and practical signal-processing details that are not always obvious. Moreover, the vast number of outcome measures that can be derived from a single dataset inflates the risk of false positives and threatens replicability. We review several methodological issues related to 1) spectral analysis, 2) montage choice, 3) extraction of phase and amplitude information, 4) surrogate construction, and 5) minimizing false positives, illustrating both the impact of methodological choices on downstream results, and the importance of checking processing steps through visualization and simplified examples. By presenting these issues in non-mathematical form, with sleep-specific examples, and with code implementation, this paper aims to instill a deeper appreciation of methodological considerations in novice and non-technical audiences, and thereby help improve the quality of future sleep EEG studies.

Multimodal assessment shows misalignment of structural and functional thalamocortical connectivity in children and adolescents born very preterm

Thalamocortical connections are altered following very preterm birth but it is unknown whether structural and functional alterations are linked and how they contribute to neurodevelopmental deficits. We used a multimodal approach in 27 very preterm and 35 term-born children and adolescents aged 10-16 years: Structural thalamocortical connectivity was quantified with two measures derived from probabilistic tractography of diffusion tensor data, namely the volume of thalamic segments with cortical connections and mean fractional anisotropy (FA) within the respective segments. High-density sleep EEG was recorded and sleep spindles were identified at each electrode. Sleep spindle density and integrated spindle activity (ISA) were calculated to quantify functional thalamocortical connectivity. In term-born participants, the volume of the global thalamic segment with cortical connections was strongly related to sleep spindles across the entire head (mean r ​= ​.53 ​± .10; range ​= ​0.35 to 0.78). Regionally, the volume of the thalamic segment connecting to frontal brain regions correlated with sleep spindle density in two clusters of electrodes over fronto-temporal brain regions (.42 ​± .06; 0.35 to 0.51 and 0.43 ​± .08; 0.35 to 0.62) and the volume of the thalamic segment connecting to parietal brain regions correlated with sleep spindle density over parietal brain regions (mean r ​= ​.43 ​± .07; 0.35 to 0.61). In very preterm participants, the volume of the thalamic segments was not associated with sleep spindles. In the very preterm group, mean FA within the global thalamic segment was negatively correlated with ISA over a cluster of frontal and temporo-occipital brain regions (mean r ​= ​-.53 ​± .07; -.41 to -.72). No association between mean FA and ISA was found in the term-born group. With this multimodal study protocol, we identified a potential misalignment between structural and functional thalamocortical connectivity in children and adolescents born very preterm. Eventually, this may shed further light on the neuronal mechanisms underlying neurodevelopmental sequelae of preterm birth.