Biology subjects

Krugliakova, E.

Publications and source records attributed to Krugliakova, E..

9 recordsLinked to original sources

bioRxiv2026

REM Sleep Iota Oscillations Across the Lifespan

Iota oscillations are a newly discovered marker of wakefulness and rapid eye movement (REM) sleep. So far, iota in REM sleep has only been reported in the surface electroencephalography (EEG) of a small sample of young adults and in intracranial recordings of epileptic patients. Here, we investigated the presence of these oscillations in a large dataset (N=937) of high-density sleep EEG recordings from individuals 7 to 70 years old. We found that iota spectral peaks during REM sleep were between 25 and 40 Hz, slightly faster than in wake (25-35 Hz). Iota power was significantly associated with REM sleep architecture, increasing with both REM duration and across progressive sleep cycles. Iota peaks were observed in individuals of all ages, although the prevalence decreased gradually with age, from 88% in children to 44% in older adults. Most iota spectral peak properties (frequency, amplitude, timing, topography) likewise shifted with age. The most striking effect, however, was in bandwidth, such that children had narrow iota peaks, older adults had broad iota peaks, and 20-30 year olds could have either. It remains unclear whether narrowband and broadband iota are functionally equivalent. On shorter time scales (< 1 year), iota properties remained stable across measurements. Analyses of a separate dataset of monozygotic and dizygotic twins revealed high heritability of all iota peak properties except bandwidth. Overall, these results establish iota as a genetically determined trait-like marker of REM sleep with unique age-related changes. Iota oscillations open new avenues to investigate the interaction between sleep, genetics, development, and aging.

neuroscience↗

bioRxiv2025

Local modulation of sleep slow waves depends on timing between auditory stimuli

Conflicting evidence exists regarding the role of the targeted slow-wave phase in determining the direction and spatial specificity of slow-wave activity (SWA) modulation via phase-targeted auditory stimulation (PTAS) during sleep. To reconcile these discrepancies, we re-analyzed high-density electroencephalography (hd-EEG) data from previous studies, focusing on SWA responses to auditory stimuli presented with varying inter-stimulus intervals (ISIs). Our analysis reveals that ISI is a primary determinant of PTAS-induced SWA modulation, exceeding the influence of targeted phase alone. Specifically, auditory stimulation with longer ISIs evoked a global increase in SWA, consistent with a stereotypical auditory-evoked K-complex (KC), independent of targeted phase. Conversely, longer stimulus trains with rapid successive stimulus presentation resulted in spatially localized, phase-dependent SWA modulation, with up-PTAS enhancing and down-PTAS reducing SWA locally around the targeted area. This distinction resolves inconsistencies in prior PTAS studies by demonstrating that phase alone in insufficient in predicting slow-wave responses. Rather, it was the ISI which determined whether PTAS resulted in a global, KC-mediated response or a local, phase-specific modulation of SWA. Consequently, our findings refine the mechanistic understanding of PTAS, suggesting that ISI regulates the engagement of distinct neural circuits and thereby potentially enables the targeted manipulation of specific slow-wave subtypes and their associated functions.

neuroscience↗

bioRxiv2024

The Infraslow Fluctuation of Sigma Power During Sleep: Links to Markers of Arousal and Memory Reactivation Across Development

Sleep is both a state of disconnection from the environment and a critical period for restoration. But how does sleep balance responsiveness with the protection of key functions? The infraslow fluctuation of sigma power (ISFS)--the clustering of sleep spindles over 10-100 seconds--is thought to regulate this trade-off in rodents. However, the organization of arousal and memory reactivation markers within the human ISFS and its conservation in younger ages remain unclear. This study characterizes the ISFS from childhood to young adulthood (N = 154; ages 8-26), examining its relationship with functional markers. Results indicate that the ISFS is present across all ages, with frequency, variability, and strength increasing from early to late adolescence. Notably, markers of arousal and memory reactivation are organized within the spindle-rich ISFS peak. The consistent presence and organization of the ISFS suggest it is intrinsic to sleep, with adolescence marking a dynamic window. These insights may guide interventions to promote healthier sleep across development.

neuroscience↗

bioRxiv2024

Wake EEG oscillation dynamics reflect both sleep need and brain maturation across childhood and adolescence

1An objective measure of brain maturation is highly insightful for monitoring both typical and atypical development. Slow wave activity, recorded in the sleep electroencephalogram (EEG), reliably indexes age-related changes in sleep pressure as well as deficits related to developmental disorders such as attention-deficit hyperactivity disorder (ADHD). We aimed to determine whether wake EEG measured before and after sleep could index the same developmental changes in sleep pressure, using data collected from 163 participants 3-25 years old. We analyzed ageand sleep-dependent changes in two measures of oscillatory activity, amplitudes and density, as well as two measures of aperiodic activity, offsets and exponents. We then compared these wake measures to sleep slow wave amplitudes and slopes. Finally, we compared wake EEG in children with ADHD (N=58) to neurotypical controls. Of the four wake measures, only oscillation amplitudes consistently exhibited the same changes as sleep slow waves. Wake amplitudes decreased with age, decreased after sleep, and this overnight decrease decreased with age. Furthermore, wake amplitudes were significantly related to both sleep slow wave amplitudes and slopes. Wake oscillation densities decreased overnight in children but increased overnight in adolescents and adults. Aperiodic offsets decreased linearly with age, decreased after sleep, and were significantly related to sleep slow wave amplitudes. Aperiodic exponents also decreased with age, but increased after sleep. No wake measure showed significant effects of ADHD. Overall, our results indicate that wake oscillation amplitudes, and to some extent aperiodic offsets, behave like sleep slow waves across sleep and development. At the same time, overnight changes in oscillation densities independently reflect some yet-unknown shift in neural activity around puberty.

neuroscience↗

bioRxiv2023

Acoustically evoked K-complexes are sufficient to boost verbal memory consolidation during sleep

Over the past decade, phase-targeted auditory stimulation (PTAS), a neuromodulation approach which presents auditory stimuli locked to the ongoing phase of slow waves during sleep, has shown potential to enhance specific aspects of sleep functions. However, the complexity of PTAS responses complicates the establishment of causality between specific electroencephalographic events and observed benefits. Here, we used down-PTAS during sleep to specifically evoke the early, K-complex (KC)-like response following PTAS without leading to a sustained increase in slow-wave activity throughout the stimulation window. Over the course of two nights, one with down-PTAS, the other without, high-density electroencephalography (hd-EEG) was recorded from 14 young healthy adults. The early response exhibited striking similarities to evoked KCs and was associated with improved verbal memory consolidation via stimulus-evoked spindle events nested into the up-phase of ongoing 1 Hz waves in a central region. These findings suggest that the early, KC-like response is sufficient to boost memory, potentially by orchestrating aspects of the hippocampal-neocortical dialogue.

neuroscience↗

bioRxiv2022

The theta paradox: 4-8 Hz EEG oscillations reflect both local sleep and cognitive control

Human brain activity generates electroencephalographic (EEG) oscillations that characterize specific behavioral and vigilance states. The frequency of these oscillations is typically sufficient to distinguish a given state, however theta oscillations (4-8 Hz) have instead been found in near-opposite conditions of drowsiness during sleep deprivation and alert cognitive control. While the latter has been extensively studied and is often referred to as "frontal midline theta", the former has been investigated far less but is considered to be a marker for local sleep during wake. In this study we investigated to what extent theta oscillations differed during cognitive tasks and sleep deprivation. We measured high-density EEG in 18 young healthy adults performing 6 tasks under 3 levels of sleep deprivation. We found both cognitive load and sleep deprivation increased theta power in medial prefrontal cortical areas, however sleep deprivation caused additional increases in theta in many other, predominantly frontal, areas. The sources of sleep deprivation theta were task-dependent, with a visual-spatial task and short-term memory task showing the most widespread effects. Notably, theta was highest in supplementary motor areas during passive music listening, and highest in the inferior temporal cortex during a spatial game. This suggests that theta caused by sleep deprivation may preferentially occur in cortical areas not involved in ongoing behavior. While our results find differences in topography from frontal midline theta, they raise the possibility that a common mechanism may underly both theta oscillations during cognition and during sleep deprivation.

neuroscience↗

bioRxiv2019

Changes in cross-frequency coupling following closed-loop auditory stimulation in non-rapid eye movement sleep

The activity of different brain networks in non-rapid eye movement (NREM) sleep is regulated locally in an experience-dependent manner, reflecting the extent of the network load during wakefulness. In particular, improved task performance after sleep correlates with the local post-learning power increase of neocortical slow waves and faster oscillations such as sleep spindles and their temporal coupling. Recently, it was demonstrated that by targeting slow waves in a particular region at a particular phase with closed-loop auditory stimulation it is possible to locally manipulate slow-wave activity and interact with training-induced neuroplastic changes. Based on this finding, we tested whether closed-loop auditory stimulation targeting the up-phase of slow-waves over the right sensorimotor area might affect power in delta, theta and sigma bands and coupling between these oscillations within the circumscribed region. We demonstrate that while closed-loop auditory stimulation globally enhances power in delta, theta and sigma bands, changes in cross-frequency coupling of these oscillations were more spatially restricted. In particular, stimulation induced a significant decrease of delta-theta coupling in frontal channels, within the area of the strongest baseline coupling between these frequency bands. In contrast, a significant increase in delta-sigma coupling was observed over the right parietal area, located directly posterior to the target electrode. These findings suggest that closed-loop auditory stimulation locally modulates coupling between delta phase and sigma power in a targeted region, which could be used to manipulate sleep-dependent memory formation within the brain network of interest.

neuroscience↗

bioRxiv2016

Localizing hidden regularities with known temporal structure in the EEG evoked response data

In this paper we describe a novel data driven spatial filtering technique that can be applied to the ERP analysis in order to find statistically significant hidden differential activations in the EEG data. The technique is based on the known morphological characteristics of the response. Underlying optimization problem is formulated as a generalized Rayleigh quotient maximization problem. We supply our tech-nique with a relevant randomization-based statistical test to assess the significance of the discovered phenomenon. Furthermore, we describe an application of the proposed method to the EEG data acquired in the study devoted to the analysis of the auditory neuroplasticity. We show how the mismatch negativity component, a tiny and short-lasting negative response that hallmarks the novel stimuli activating primary error-detection mechanisms, can be detected after filtration.

animal behavior and cognition↗

bioRxiv2016

RL mechanisms of short-term plasticity of auditory cortex

The decision-making process is exposed to modulatory factors, and, according to the expected value (EV) concept the two most influential factors are magnitude of prospective behavioural outcome and probability of receiving this outcome. The discrepancy between received and predicted outcomes is reflected by the reward prediction error (RPE), which is believed to play a crucial role in learning in dynamic environment. Feedback related negativity (FRN), a frontocentral negative component registered in EEG during feedback presentation, has been suggested as a neural signature of RPE. In modern neurobiological models of decision-making the primary sensory input is assumed to be constant over the time and independent of the evaluation of the option associated to it. In this study we investigated whether the electrophysiological changes in auditory cues perception is modulated by the strengths of reinforcement signal, represented in the EEG as FRN.\n\nWe quantified the changes in sensory processing through a classical passive oddball paradigm before and after performance a neuroeconomic monetary incentive delay (MID) task. Outcome magnitude and probability were encoded in the physical characteristics of auditory incentive cues. We evaluated the association between individual biomarkers of reinforcement signal (FRN) and the degree of perceptual learning, reflected by changes in auditory ERP components (mismatch negativity and P3a). We observed a significant correlation of MMN and valence - dFRN, reflecting differential processing of gains and omission of gains. Changes in P3a were correlated to probability - dFRN, including information on salience of the outcome, in addition to its valence.\n\nMID task performance evokes plastic changes associated with more fine-grained discrimination of auditory anticipatory cues and enhanced involuntary attention switch towards these cues. Observed signatures of neuro-plasticity of the auditory cortex may play an important role in learning and decision-making processes through facilitation of perceptual discrimination of valuable external stimuli. Thus, the sensory processing of options and the evaluation of options are not independent as implicitly assumed by the modern neuroeconomics models of decision-making.

neuroscience↗