Biology subjects

Kozhemiako, N.

Publications and source records attributed to Kozhemiako, N..

12 recordsLinked to original sources

bioRxiv2026

Disrupted Sleep-Dependent Neural Oscillations and Transcriptomic Changes in the Cacna1g Loss-of-Function Mouse Model Implicated in Schizophrenia

Sleep is an essential biological process for maintaining brain function, and impaired sleep microarchitecture is a well-established feature of schizophrenia (SCZ). Rare loss-of-function variants in CACNA1G, encoding the T-type calcium channel CaV3.1, confer substantial risk for SCZ, implicating sleep-regulatory circuits in disease pathophysiology. Here, we first show that among individuals with SCZ, carriers of rare CACNA1G missense variants exhibit more pronounced alterations in sleep neurophysiology than non-carriers, identifying a human phenotype suggestive of altered channel function. Motivated by this observation, we examined the consequences of Cacna1g loss of function in mice. Cacna1g deficiency produced profound disruptions in sleep microarchitecture, including reduced sleep spindles, altered slow oscillations, impaired spindle-slow oscillation coupling, and reduced cortical synchrony--closely recapitulating neurophysiological signatures observed in individuals with schizophrenia. Beyond sleep structure, Cacna1g loss disrupted the normal coordination of brain rhythms across the 24-hour cycle, most notably abolishing diurnal modulation of theta oscillations. At the molecular level, Cacna1g loss uncoupled sleep-wake state from gene and protein regulation, producing widespread, sleep-phase-biased transcriptional and synaptic alterations across brain regions and cell types, particularly in cortical excitatory neurons. These network and molecular disruptions were accompanied by behavioral hyperactivity during the active phase. Together, these findings establish CACNA1G/CaV3.1 as a key regulator linking sleep-dependent brain dynamics to molecular homeostasis and behavior, and provide a mechanistic framework through which genetic risk for SCZ may drive disease-relevant sleep and circuit dysfunction. One Sentence SummaryLoss of CACNA1G disrupts sleep rhythms and gene regulation, creating a mismatch between brain state and behavior linked to schizophrenia.

neuroscience↗

bioRxiv2025

The effect of sex on sleep EEG in typical and altered neurodevelopment

Sleep electroencephalography (EEG) patterns exhibit complex variations influenced by multiple factors, including sex. While sex effects in sleep neurophysiology are relatively well described in adults, evidence in pediatric populations is more limited, particularly in the context of neurodevelopmental disorders (NDDs). Here, we analyzed a large pediatric clinical dataset to examine sex differences in whole-night sleep EEG among children without NDDs (N=1523, 2.5-17.5 years) and those with autism spectrum disorder (ASD, N=196), attention deficit hyperactivity disorder (ADHD, N=523), and intellectual disabilities (IntDis, N=167). Medical record analysis revealed limited sex differences in the prevalence of sleep disorders. Using the open-source package Luna, we extracted a broad range of sleep EEG features (435 in total) and found that 25% of all tested metrics showed significant sex differences in the non-NDD sample with the majority replicated in an independent population-based pediatric cohort. Non-NDD boys exhibited more fragmented sleep compared to girls, but this pattern was not observed among children with NDDs. In contrast, fast spindle density was lower in boys regardless of NDD diagnosis, which may contribute to males increased susceptibility to developing NDDs. No sex differences were observed in EEG-based brain age predictions. Several sleep EEG metrics showed nominal group-by-sex interactions with ASD and ADHD girls displaying more pronounced alterations, pointing to a varying degree of sleep disturbance. Overall, our findings demonstrate that many sleep EEG features exhibit significant sex differences during childhood, but these differences may be distinct in NDD populations. The sex-specific sleep alterations in NDDs underscore the importance of including both sexes in future research.

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bioRxiv2023

A spectrum of altered non-rapid eye movement sleep in schizophrenia

BackgroundMultiple facets of sleep neurophysiology, including electroencephalography (EEG) metrics such as non-rapid eye movement (NREM) spindles and slow oscillations (SO), are altered in individuals with schizophrenia (SCZ). However, beyond group-level analyses which treat all patients as a unitary set, the extent to which NREM deficits vary among patients is unclear, as are their relationships to other sources of heterogeneity including clinical factors, illness duration and ageing, cognitive profiles and medication regimens. Using newly collected high density sleep EEG data on 103 individuals with SCZ and 68 controls, we first sought to replicate our previously reported (Kozhemiako et. al, 2022) group-level mean differences between patients and controls (original N=130). Then in the combined sample (N=301 including 175 patients), we characterized patient-to-patient variability in NREM neurophysiology. ResultsWe replicated all group-level mean differences and confirmed the high accuracy of our predictive model (Area Under the ROC Curve, AUC = 0.93 for diagnosis). Compared to controls, patients showed significantly increased between-individual variability across many (26%) sleep metrics, with patterns only partially recapitulating those for group-level mean differences. Although multiple clinical and cognitive factors were associated with NREM metrics including spindle density, collectively they did not account for much of the general increase in patient-to-patient variability. Medication regimen was a greater (albeit still partial) contributor to variability, although original group mean differences persisted after controlling for medications. Some sleep metrics including fast spindle density showed exaggerated age-related effects in SCZ, and patients exhibited older predicted biological ages based on an independent model of ageing and the sleep EEG. ConclusionWe demonstrated robust and replicable alterations in sleep neurophysiology in individuals with SCZ and highlighted distinct patterns of effects contrasting between-group means versus within-group variances. We further documented and controlled for a major effect of medication use, and pointed to greater age-related change in NREM sleep in patients. That increased NREM heterogeneity was not explained by standard clinical or cognitive patient assessments suggests the sleep EEG provides novel, nonredundant information to support the goals of personalized medicine. Collectively, our results point to a spectrum of NREM sleep deficits among SCZ patients that can be measured objectively and at scale, and that may offer a unique window on the etiological and genetic diversity that underlies SCZ risk, treatment response and prognosis.

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bioRxiv2023

Spindle Chirp and other Sleep Oscillatory Features in Young Children with Autism

ObjectivesTo determine whether spindle chirp and other sleep oscillatory features differ in young children with and without autism. MethodsAutomated processing software was used to re-assess an extant set of polysomnograms representing 121 children (91 with autism [ASD], 30 typically-developing [TD]), with an age range of 1.35-8.23 years. Spindle metrics, including chirp, and slow oscillation (SO) characteristics were compared between groups. SO and fast and slow spindle (FS, SS) interactions were also investigated. Secondary analyses were performed assessing behavioural data associations, as well as exploratory cohort comparisons to children with non-autism developmental delay (DD). ResultsPosterior FS and SS chirp was significantly more negative in ASD than TD. Both groups had comparable intra-spindle frequency range and variance. Frontal and central SO amplitude were decreased in ASD. In contrast to previous manual findings, no differences were detected in other spindle or SO metrics. The ASD group displayed a higher parietal coupling angle. No differences were observed in phase-frequency coupling. The DD group demonstrated lower FS chirp and higher coupling angle than TD. Parietal SS chirp was positively associated with full developmental quotient. ConclusionsFor the first time spindle chirp was investigated in autism and was found to be significantly more negative than in TD in this large cohort of young children. This finding strengthens previous reports of spindle and SO abnormalities in ASD. Further investigation of spindle chirp in healthy and clinical populations across development will help elucidate the significance of this difference and better understand this novel metric.

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bioRxiv2022

Mapping Typical and Altered Neurodevelopment with Sleep Macro- and Micro-Architecture

Profiles of sleep duration and timing and corresponding electroencephalographic activity reflect brain changes that support cognitive and behavioral maturation and may provide practical markers for tracking typical and atypical neurodevelopment. To build and evaluate a sleep-based, quantitative metric of brain maturation, we used whole-night polysomnography data, initially from two large National Sleep Research Resource samples, spanning childhood and adolescence (total N = 4,013, aged 2.5 to 17.5 years): the Childhood Adenotonsillectomy Trial (CHAT), a research study of children with snoring without neurodevelopmental delay, and NCH, a pediatric sleep clinic cohort. Among children without developmental disorders, sleep metrics derived from the electroencephalogram (EEG) displayed robust age-related changes consistently across datasets. Prominent stage-, band- and channel-specific developmental trajectories in spectral power were found. During non-rapid eye movement (NR) sleep, spindles and slow oscillations further exhibited characteristic developmental patterns, with respect to their rate of occurrence, temporal coupling and morphology. Based on these metrics in NCH, we constructed a model to predict an individuals chronological age. The model performed with high accuracy (r = 0.95 in the held-out NCH testing sample and r = 0.88 in a second independent replication sample (PATS) with a broadly comparable age range). EEG-based age predictions reflected clinically meaningful neurodevelopmental differences; for example, compared to typically developing children, those with neurodevelopmental diagnoses (NDD) showed greater variability in predicted age, and children with Down syndrome or intellectual disability had significantly younger brain age predictions (respectively, 2.2 and 0.59 years less than their chronological age) compared to age-matched non-NDD children. Overall, our results indicate that sleep architecture offers a sensitive window for characterizing brain maturation, suggesting the potential for scalable, objective sleep-based biomarkers to measure typical and atypical neurodevelopment.

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bioRxiv2022

Bias in group-level EEG microstate analysis

Microstate analysis is a promising technique for analyzing high-density electroencephalographic data, but there are multiple questions about methodological best practices. Between and within individuals, microstates can differ both in terms of characteristic topographies and temporal dynamics, which leads to analytic challenges as the measurement of microstate dynamics is dependent on assumptions about their topographies. Here we focus on the analysis of group differences, using simulations seeded on real data from healthy control subjects to compare approaches that derive separate sets of maps within subgroups versus a single set of maps applied uniformly to the entire dataset. In the absence of true group differences in either microstate maps or temporal metrics, we found that using separate subgroup maps resulted in substantially inflated type I error rates. On the other hand, when groups truly differed in their microstate maps, analyses based on a single set of maps confounded topographic effects with differences in other derived metrics. We propose an approach to alleviate both classes of bias, based on a paired analysis of all subgroup maps. We illustrate the qualitative and quantitative impact of these issues in real data by comparing waking versus non-rapid eye movement sleep microstates. Overall, our results suggest that even subtle chance differences in microstate topography can have profound effects on derived microstate metrics and that future studies using microstate analysis should take steps to mitigate this large source of error.

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bioRxiv2021

Non-rapid eye movement sleep and wake neurophysiology in schizophrenia

Motivated by the potential of objective neurophysiological markers to index thalamocortical function in patients with severe psychiatric illnesses, we comprehensively characterized key NREM sleep parameters across multiple domains, their interdependencies, and their relationship to waking event-related potentials and symptom severity. In 130 schizophrenia (SCZ) patients and controls, we confirmed a marked reduction in sleep spindle density in SCZ and extended these findings to show that only slow spindles predicted symptom severity, and that fast and slow spindle properties were largely uncorrelated. We also describe a novel measure of slow oscillation and spindle interaction that was attenuated in SCZ. The main sleep findings were replicated in a demographically distinct sample, and a joint model, based on multiple NREM components, predicted disease status in the replication cohort. Although also altered in patients, auditory event-related potentials elicited during wake were unrelated to NREM metrics. Consistent with a growing literature implicating thalamocortical dysfunction in SCZ, our characterization identifies independent NREM and wake EEG biomarkers that may index distinct aspects of SCZ pathophysiology and point to multiple neural mechanisms underlying disease heterogeneity. This study lays the groundwork for evaluating these neurophysiological markers, individually or in combination, to guide efforts at treatment and prevention as well as identifying individuals most likely to benefit from specific interventions.

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bioRxiv2021

Sources of variation in the spectral slope of the sleep EEG

Building on previous work linking changes in the electroencephalogram (EEG) spectral slope to arousal level, Lendner et al. (2021) reported that wake, non rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep exhibit progressively steeper 30-45 Hz slopes, interpreted in terms of increasing cortical inhibition. Here we sought to replicate Lendner et al.s scalp EEG findings (based on 20 individuals) in a larger sample of 11,630 individuals from multiple cohorts in the National Sleep Research Resource (NSRR). In a final analytic sample of N = 10,255 distinct recordings, there was unambiguous statistical support for the hypothesis that, within individuals, the mean spectral slope grows steeper going from wake to NREM to REM sleep. We found that the choice of mastoid referencing scheme modulated the extent to which electromyogenic or electrocardiographic artifacts were likely to bias 30-45 Hz slope estimates, as well as other sources of technical, device-specific bias. Nonetheless, within individuals, slope estimates were relatively stable over time. Both cross-sectionally and longitudinal, slopes tended to become shallower with increasing age, particularly for REM sleep; males tended to show flatter slopes than females across all states. Although conceptually distinct, spectral slope did not predict sleep state substantially better than other summaries of the high frequency EEG power spectrum (>20 Hz, in this context) including beta band power, however. Finally, to more fully describe sources of variation in the spectral slope and its relationship to other sleep parameters, we quantified state-dependent differences in the variances (both within and between individuals) of spectral slope, power and interhemispheric coherence, as well as their covariances. In contrast to the common conception of the REM EEG as relatively wake-like (i.e. paradoxical sleep), REM and wake were the most divergent states for multiple metrics, with NREM exhibiting intermediate profiles. Under a simplified modelling framework, changes in spectral slope could not, by themselves, fully account for the observed differences between states, if assuming a strict power law model. Although the spectral slope is an appealing, theoretically inspired parameterization of the sleep EEG, here we underscore some practical considerations that should be borne in mind when applying it in diverse datasets. Future work will be needed to fully characterize state-dependent changes in the aperiodic portions of the EEG power spectra, which appear to be consistent with, albeit not fully explained by, changes in the spectral slope.

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bioRxiv2019

Atypical neuromagnetic resting activity associated with thalamic volume and cognitive outcome in very preterm children

Children born very preterm, even in the absence of overt brain injury or major impairment, are at risk of cognitive difficulties. This risk is associated with disruption of ongoing critical periods involving development of the thalamocortical system while in the neonatal intensive care unit. The thalamus is an important structure that not only relays sensory information but acts as a hub integrating cortical activity, and through this integration, it regulates cortical power at different frequency bands. In this study, we investigate the association between atypical power at rest in children born very preterm at school age, neurocognitive function and structural alterations related to the thalamus. Our results indicate that children born extremely preterm have higher power at low frequencies and lower power at high frequencies, compared to controls born full-term. A similar pattern of spectral power was found to be associated with poorer neurocognitive outcomes. This pattern of spectral power was also associated with normalized T1 intensity and the volume of the thalamus. Overall, this study provides evidence of the relation between structural alterations related to very preterm birth, atypical oscillatory power at rest and neurocognitive difficulties at school-age children born very preterm.

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bioRxiv2019

Neuromagnetic activation dynamics of stimulus-locked processing during a naturalistic viewing

Naturalistic stimuli such as watching a movie while in the scanner provide an ecologically valid paradigm that has the potential of extracting valuable information on how the brain processes complex stimuli in a short period of time. Naturalistic viewing is also easier to conduct with challenging participant groups including patients and children. Given the high temporal resolution of MEG, in the present study, we demonstrate how a short movie clip can be used to map distinguishable activation dynamics underlying the processing of specific classes of visual stimuli such as face and hand manipulations, as well as auditory stimuli with words and non-words.\n\nMEG data were collected from 22 healthy volunteers (6 females, 3 left handed, mean age - 27.7 {+/-} 5.28 years) during the presentation of naturalistic audiovisual stimuli. The MEG data were split into trials with the onset of the stimuli belonging to classes of interest (words, non-words, faces, hand manipulations). Based on the components of the averaged sensor ERFs time-locked to the visual and auditory stimulus onset, four and three time-windows, respectively, were defined to explore brain activation dynamics. Pseudo-Z, defined as the ratio of the source-projected time-locked power to the projected noise power for each vertex, was computed and used as a proxy of time-locked brain activation. Statistical testing using the mean-centered Partial Least Squares analysis indicated periods where a given visual or auditory stimuli had higher activation. Based on peak pseudo-Z differences between the visual conditions, time-frequency resolved analyses were carried to assess beta band desynchronization in motor-related areas, and inter-trial phase synchronization between face processing areas. Our results provide the first evidence that activation dynamics in canonical brain regions associated with the processing of particular classes of visual and auditory stimuli (words, faces, etc.) can be reliably mapped using MEG during presentation of naturalistic stimuli. Given the strength of MEG for brain mapping in temporal and frequency domains, the use of naturalistic stimuli may open new techniques in analyzing brain dynamics during ecologically valid sensation and perception.\n\nHighlightsO_LIA time-locking analysis was employed in naturalistic stimuli paradigm.\nC_LIO_LISpecific visual and auditory stimuli from the movie were mapped in brain space.\nC_LIO_LIMotor {beta}-suppression was evident in periods of watching hand manipulation.\nC_LIO_LIIncreased synchronization between core face-processing areas was found around 200 and 300ms in the face condition.\nC_LIO_LINaturalistic viewing paradigms provide a reliable approach for investigating brain dynamics.\nC_LI

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bioRxiv2019

Atypical developmental features of cortical thickness trajectories in Autism Spectrum Disorder

Neuroimaging studies have reported numerous region-specific atypicalities in the brains of individuals with Autism Spectrum Disorder (ASD), including alterations in cortical thickness (CT). However, there are many inconsistent findings, and this is probably due to atypical CT developmental trajectories in ASD. To this end, we investigated group differences in terms of shapes of developmental trajectories of CT between ASD and typically developing (TD) populations.\n\nUsing the Autism Brain Imaging Data Exchange (ABIDE) repository (releases I and II combined), we investigated atypical shapes of developmental trajectories in ASD using a linear, quadratic and cubic models at various scales of spatial coarseness, and their association with symptomatology using the Autism Diagnostic Observation Schedule (ADOS) scores. These parameters were also used to predict ASD and TD CT development.\n\nWhile no overall group differences in CT was observed across the entire age range, ASD and TD populations were different in terms of age-related changes. Developmental trajectories of CT in ASD were mostly characterized by decreased cortical thinning during early adolescence and increased thinning at later stages, involving mostly frontal and parietal areas. Such changes were associated with ADOS scores. The curvature of the trajectories estimated from the quadratic model was the most accurate and sensitive measure for detecting ASD. Our findings suggest that under the context of longitudinal changes in brain morphology, robust detection of ASD would require three time points to estimate the curvature of age-related changes.

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bioRxiv2019

Multiple constrained minimum variance beamformer (MCMV) performance in connectivity analyses

Functional brain connectivity is increasingly being seen as critical for cognition, perception and motor control.Magnetoencephalography and electroencephalography are modalities that offer noninvasive mapping of electrophysiological interactions among brain regions, yet suffer from signal leakage and signal cancellation when estimating brain activity. This leads to biased connectivity values which complicate interpretation. In this study, we test the hypothesis that a Multiple Constrained Minimum Variance beamformer (MCMV) outperforms the more traditional Linearly Constrained Minimum Variance beamformer (LCMV) for estimation of electrophysiological connectivity. To this end, MCMV and LCMV performance is compared in task related analyses with both simulated data and human MEG recordings of visual steady state signals, and in resting state analyses with simulated data and human MEG data of 89 subjects. In task related scenarios connectivity was estimated using coherence and phase locking values, whereas envelope correlations were used for the resting state data. We also introduce a novel Augmented Pairwise MCMV (APW-MCMV) approach for signal leakage suppression in resting state analyses and assess its performance against LCMV and more conventional MCMV approaches. We demonstrate that with MCMV effects of signal mixing and coherent source cancellation are greatly reduced in both task related and resting state conditions, while in contrast to other approaches 0-and short time lag interactions are preserved. In addition, we demonstrate that in resting state analyses, APW-MCMV strongly reduces spurious connections while better controlling for false negatives compared to more conservative measures such as symmetrical orthogonalization.

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