Biology subjects

Gombos, F.

Publications and source records attributed to Gombos, F..

17 recordsLinked to original sources

bioRxiv2026

Pubertal timing is a critical dimension of adolescent brain vulnerability

Adolescence is a period of rapid brain development, during which biological maturational timing varies substantially between individuals. This variability may drive specific developmental vulnerabilities to adverse experiences with long-term consequences, warranting early identification of at-risk individuals. We utilized ultrasonic bone age measurements to track pubertal maturity, classifying participants by adolescent biological maturity relative to chronological age (accelerated, average, decelerated). Brain hierarchy was quantified as the irreversibility of brain signals in resting state electroencephalography, providing a brain-based method to detect vulnerability patterns. The COVID-19 pandemic presented a unique opportunity to also assess alterations in brain hierarchy following external disruption. We mapped maturity-defined trajectories and rates of hierarchical organization, and their post-pandemic deviation from expected development, capturing two distinct vulnerability forms. First, early maturing adolescents showed persistent reduction in brain hierarchy. Second, those undergoing their fastest phase of development - specifically, decelerated adolescents - showed the strongest disruption in brain hierarchy following the pandemic. These findings suggest that pubertal timing is a critical dimension of individual variation in adolescent brain development and vulnerability. They also emphasize the need for objective maturity measurements to tailor support to individual pubertal timelines, particularly given the secular trend toward earlier puberty and ongoing global ecological crises.

neuroscience↗

bioRxiv2025

A broken power-law model of heart rate variability spectra in sleep

AimsThe aim of the study was to introduce a parametric description of RR-interval spectra using a broken power-law model, in addition to the parametrization of oscillatory peaks. Furthermore, to use this model to evaluate effects of age, sex and sleep architecture on overnight heart rate variability (HRV) in healthy subjects. Methods & ResultsFrom a polysomnography database, 215 whole-night, high quality electrocardiograms (ECGs) were extracted. The fractal and oscillatory power-spectral densities (PSDs) were calculated from evenly resampled RR-interval time-series, then a broken power-law model was fitted using piecewise linear regression to the double-logarithmic PSD, determining a custom breaking point in the fractal component, and allowing for two independent spectral slopes in the lower and higher frequency domains. The two-slope model provided a more optimal description compared to linear regression in all cases, even when penalizing increased model complexity. Peak detection was applied to the oscillatory component in the LF (0.04-0.15 Hz) and HF (0.15-0.4 Hz) bands, extracting the frequency and prominence of the dominant peak from each. The high frequency domain intercept, the breaking point frequency and the LF peak frequency decreased significantly with age. Both slopes were flatter in females, while the high domain intercept and the HF peak prominence was significantly increased. Waking after sleep onset and lightest sleep (N1) were associated with lower intercept values, while REM sleep had an opposite effect. ConclusionsThe broken power-law model proved to be more appropriate for the description of RR-interval spectra than the single-slope model, and also captured effects of age, sex and sleep structure that were corroborated by the literature. We would like to highlight that while HRV changes are often assumed to be of oscillatory origin, the fractal component has a major contribution to the total PSD, and thus to all measures derived from it.

physiology↗

bioRxiv2025

Spectral features of heart rate variability in Williams syndrome during sleep

AimsThe study aims to reveal the spectral alterations of heart rate variability (HRV) in Williams syndrome (WS) during sleep, using a two-slope, broken power-law model, taking into account the multi-fractal properties of the RR-interval spectra, including effects of aging and associations with sleep structure indicators. Methods & ResultsExtracting ECG recordings from a polysomnography database of 20 subjects with WS and 20 age and sex matched typically developing (TD) controls, RR-interval time series were constructed, then the fractal and oscillatory power-spectral densities computed using the Irregular-Resampling Auto-Spectral Analysis (IRASA) method. The fractal component was parametrized with a piecewise-linear function, that allowed for a custom breaking point in the power spectral density (PSD), and separate slope and intercept values in the lower and higher frequency domains. The frequency and prominence of the dominant peak was extracted from the LF (0.04-0.15 Hz) and HF (0.15-0.4 Hz) bands. Strong WS vs TD group differences were found in the frequency of the breaking point, high domain slope, intercept and HF peak prominence. Analysis of the LF peak frequency revealed age-dependent decrease in the TD, but not in the WS group, while generally decreased values in WS independent of age, potentially reflected accelerated aging, characteristic of the syndrome. As fractal parameters were correlated, a main component was identified using principal component analysis that described the typical alterations in the fractal spectrum in WS, and was correlated with sleep structure indices as well. ConclusionsThe broken power-law model proved to be successful in characterizing the fractal component of HRV spectra, furthermore it captured alterations in cardiac regulation in WS. A main spectral feature of WS was identified in the fractal component, being associated with sleep quality indicators, a possible biomarker of the degree of general autonomic deregulation inherent to the syndrome.

physiology↗

bioRxiv2024

Visual training induced occipital fast sleep spindle clustering in humans revealed by full-night HD-EEG recordings

This study investigates the impact of extensive visual procedural training on the temporal organisation of sleep spindles in healthy young adults. We selected 39 participants aged 16-20 and employed high-density electroencephalography to assess spindle characteristics during two full nights of sleep, with daytime practising in a contour integration task in between the two nights. We utilised linear mixed models to comprehensively analyse the effects of age and training on basic, clustering- and rhythmicity-related spindle parameters. Our findings indicate no significant age effects in this age-range, and no significant change between the two nights with respect to slow spindles. Fast spindles demonstrated a significant increase in density after training, and we observed significant changes in spindle clustering and rhythmicity parameters as well. Local spindle density, train density, and the ratio of clustered spindles have increased, and inter-train interval decreased by the second night. These results contribute to the growing literature on sleep-dependent memory consolidation by demonstrating that spindle reorganisation occurs not only in motor tasks but also in visual learning contexts. The absence of age-related differences further highlights the robustness of these mechanisms across developmental stages. Our study emphasises the importance of spindle dynamics in procedural learning and suggests promising possibilities for future research into the neurophysiological basis of memory consolidation. By revealing the relationship between training and sleep spindle characteristics, our findings provide valuable insights into how sleep supports learning and memory processes in young adults, potentially informing interventions aimed at enhancing memory performance through sleep-related strategies.

neuroscience↗

bioRxiv2024

The contributions of biological maturity and experience to fine motor development in adolescence

Fine motor function develops into adulthood, but little is known about the differential effects of biological maturation and experience on speed and complex sequential performance of the hand. To determine maturity levels, ultrasonic bone age (BA) was assessed in 225 adolescents (123 females; BA range: 9.9 to 17.9 years). The role of experience was evaluated based on chronological age (CA, range: 11.1 to 16.5 years), musical instrumental experience, and handedness. Multiple linear regression modeling showed that BA is the strongest predictor of sequential motor performance, while CA influenced motor speed when no musical instrumental experience was present. When present, the amount of highly specific musical instrumental experience becomes the main predictor of sequential performance.

neuroscience↗

bioRxiv2024

Aperiodic neural activity distinguishes between phasic and tonic REM sleep

IntroductionTraditionally categorized as a uniform sleep phase, rapid eye movement (REM) sleep exhibits substantial heterogeneity with its phasic and tonic constituents showing marked differences regarding neuronal network activity, environmental alertness and information processing. Here, we investigate how tonic and phasic states differ with respect to aperiodic neural activity, a marker of arousal levels, sleep stages, depth of sleep and sleep intensity. We also attempt to challenge the binary categorisation of REM sleep states by introducing graduality into their definition. Specifically, we quantify the intensity of phasic oculomotor events and investigate their temporal relationships with aperiodic activity. MethodWe analyzed 57 polysomnographic recordings from three open-access datasets of healthy young volunteers aged 21.7{+/-}1.4 years. REM sleep heterogeneity was assessed using either binary phasic-tonic categorization or quantification of eye movement (EM) amplitudes detected by electrooculography with the YASA algorithm. Slopes of the aperiodic power component measured by electroencephalography in the low (2-30Hz) and high (30-48Hz) frequency bands were calculated using the Irregularly Resampled Auto-Spectral Analysis. For statistical analyses, we used ANOVA, Spearman correlations and cross-correlations. ResultsThe binary approach revealed that the phasic state is characterized by steeper low-band aperiodic slopes compared to the tonic state with the strongest effect observed over the frontal area. The phasic state also showed flatter high-band slopes with the strongest effect over central and parietal areas. The gradual approach confirmed this result further showing that higher EM amplitudes are linked to steeper low-band and flatter high-band aperiodic slopes. The temporal analysis within REM episodes revealed that aperiodic activity preceding or following EM events did not cross-correlate with EM amplitudes. ConclusionThis study demonstrates that aperiodic slopes can serve as a reliable objective marker able to differentiate between phasic and tonic constituents of REM sleep and reflect the intensity of phasic oculomotor events for instantaneous measurements. However, EM events could not be predicted by preceding aperiodic activity and vice versa, at least not with scalp electroencephalography.

neuroscience↗

bioRxiv2023

Navigating Pubertal Goldilocks: The Optimal Pace for Hierarchical Brain Organization

Adolescence is a timed process with an onset, tempo, and duration. Nevertheless, the temporal dimension, especially the pace of maturation, remains an insufficiently studied aspect of developmental progression. This study focuses on the modifications due to the different timings of developmental shifts during adolescence and addresses the impact of adolescent maturation on brain development. To reveal potential relationships between pubertal pace and the advancement of brain organisation, we analyse the connection between skeletal age-based maturation stages and hierarchical organisation in the temporal dynamics of resting-state EEG recordings (alpha frequency range). By adopting skeletal maturity as a proxy for pubertal progress and employing entropy production to measure hierarchical brain organisation, our findings indicate that an average maturational trajectory optimally aligns with cerebral hierarchical order. Adaptive developmental plasticity may not fully compensate for accelerated or decelerated timelines, potentially increasing the risk of behavioural problems and psychiatric disorders consequent to such alterations.

neuroscience↗

bioRxiv2022

Scale-free and oscillatory spectral measures of sleep stages in humans

Power spectra of sleep electroencephalograms (EEG) comprise two main components: a decaying power-law corresponding to the aperiodic neural background activity, and spectral peaks present due to neural oscillations.Traditional band-based spectral methods ignore this fundamental structure of the EEG spectra and thus are susceptible to misrepresenting the underlying phenomena. A fitting method that attempts to separate and parameterize the aperiodic and periodic spectral components called fitting oscillations & one over f (FOOOF) was applied to a set of annotated whole-night sleep EEG recordings of 251 subjects from a wide age range (4-69 years). Most of the extracted parameters exhibited sleep stage sensitivity; significant main effects and interactions of sleep stage, age, sex, and brain region were found. The spectral slope (describing the steepness of the aperiodic component) showed especially large and consistent variability between sleep stages (and low variability between subjects), making it a candidate indicator of sleep states. The limitations and arisen problems of the FOOOF method are also discussed, possible solutions for some of them are suggested.

bioinformatics↗

bioRxiv2021

The adolescent pattern of sleep spindle development revealed by HD-EEG polisomnography

Sleep spindles are developmentally relevant cortical oscillatory patterns; however, they have mostly been studied by considering the entire spindle frequency range (11 to 15 Hz) without a distinction between the functionally and topographically different slow and fast spindles, using relatively few electrodes and analysing wide age-ranges. Here, we employ HD-EEG polysomnography in three age-groups between 12 to 20 years of age, with an equal distribution between the two genders, and analyse the adolescent developmental pattern of the four major parameters of slow and fast sleep spindles. Most of our findings corroborate those very few previous studies that also make a distinction between slow and fast spindles in their developmental analysis. We find spindle frequency increasing with age, although spindle density change is not obvious in our study. We confirm the declining tendencies for amplitude and duration, although within narrower, more specific age-windows than previously. Spindle frequency seems to be higher in females in the oldest age-group. Based on the pattern of our findings, we suggest that HD-EEG, specifically targeting slow and fast spindle ranges and relatively narrow age-ranges would advance the understanding of both adolescent development and the functional relevance of sleep spindles in general.

neuroscience↗

bioRxiv2021

Visual imagery vividness declines across the lifespan

The capacity to elicit vivid visual mental images varies within an extensive range across individuals between hyper- and aphantasia. It is not clear, however, whether imagery vividness is constant across the lifespan or changes during development and later in life. Without enforcing the constraints of strict experimental procedures and representativity across the entire population, our purpose was to take a first look at the self-reported level of imagery vividness and determine the relative proportion of aphantasic/hyperphantasic participants in different age-groups. Relying on the frequently used Vividness of Visual Mental Imagery questionnaire, we collected data on a random sample of 2252 participants between the ages of 12 to 60 years. We found a novel developmental pattern describing a declining ability to elicit vivid visual mental images in the group averages of different age-groups from adolescence to middle age. This effect involves both a decreasing proportion of individuals with very vivid imagery and an increasing proportion of individuals with weak imagery as maturation (assessed by boneage estimations in adolescents) and aging progresses. This finding may help to shed light on yet unknown developmental mechanisms of our internal, stimulus-independent processes, and might also help to determine genetic, maturational, and age-dependent factors in the extreme cases of hyper- and aphantasia.

neuroscience↗

bioRxiv2021

Dissociating experience-dependent and maturational changes in fine motor function during adolescence

Adolescence is a sensitive period in motor development but little is known about how long-term learning dependent processes shape hand function in tasks of different complexity. We mapped two fundamental aspects of hand function: simple repetitive and complex sequential finger movements, as a function of the length of musical instrumental training. We controlled maturational factors such as chronological and biological age of adolescent female participants (11 to 15 years of age, n=114). We demonstrated that experience improves performance as a function of task complexity, the more complex task being more susceptible for experience driven performance changes. Overall, these results suggest that fine motor skills involving cognitive control and relying on long-range functional brain networks are substantially shaped by experience. On the other hand, performance in a simple repetitive task that explains fine motor speed is primarily shaped by white matter development driven by maturational factors.

neuroscience↗

bioRxiv2021

Circadian modulation of human sleep spindle frequency

Homeostatic and circadian processes play a pivotal role in determining sleep structure, timing and quality. In sharp contrast with the wide accessibility of the EEG index of sleep homeostasis, an electrophysological measure of the circadian modulation of sleep is still non-available. Evidence suggests that sleep spindle frequencies decelerate during biological night. In order to test the feasibility of measuring this marker in common polysomnographic protocols, the Budapest-Munich database of sleep records (N = 251 healthy subjects, 122 females, age range: 4-69 years), as well as an afternoon nap sleep record database (N = 112 healthy subjects, 30 females, age range: 18-30 years) were analysed by the Individual Adjustment Method of sleep spindle analysis. Slow and fast sleep spindle frequencies were characterized by U-shaped overnight dynamics, with highest values in the first and the fourth-to-fifth sleep cycle and the lowest values in the middle of the sleeping period (cycles 2-3). Age-related attenuation of sleep spindle deceleration was evident. Estimated phases of the nadirs in sleep spindle frequencies were advanced in children as compared to other age groups. Additionally, nap sleep spindles were faster than night sleep spindles (0.57 and 0.39 Hz difference for slow and fast types, respectively). The fine frequency resolution analysis of sleep spindles is a feasible method of measuring the assumed circadian modulation of sleep. Moreover, age-related attenuation of circadian sleep modulation might be measurable by assessing the overnight dynamics in sleep spindle frequency. Phase of the minimal sleep spindle frequency is a putative biomarker of chronotype.

neuroscience↗

bioRxiv2021

Topographical relocation of adolescent sleep spindles reveals a new maturational pattern of the human brain

Current theories of human neural development emphasize the posterior-to-anterior pattern of brain maturation. However, this scenario leaves out significant brain areas not directly involved with sensory input and behavioral control. Suggesting the relevance of cortical activity unrelated to sensory stimulation, such as sleep, we investigated adolescent transformations in the topography of sleep spindles. Sleep spindles are known to be involved in neural plasticity and in adults have a bimodal topography: slow spindles are frontally dominant, while fast spindles have a parietal/precuneal origin. The late functional segregation of the precuneus from the frontoparietal network during adolescence suggests that spindle topography might approach the adult state relatively late in development, and it may not be a result of the posterior-to-anterior maturational pattern. We analyzed the topographical distribution of spindle parameters in HD-EEG polysomnographic sleep recordings of adolescents and found that slow spindle duration maxima traveled from central to anterior brain regions, while fast spindle density, amplitude and frequency peaks traveled from central to more posterior brain regions. These results provide evidence for the gradual posteriorization of the anatomical localization of fast sleep spindles during adolescence and indicate the existence of an anterior-to posterior pattern of human brain maturation.

neuroscience↗

bioRxiv2021

Selective effects of biological and chronological age on the development of cognitive abilities in adolescence

Adolescent human development is not only shaped by the mere passing of time and accumulating experience, but it also depends on pubertal timing and the cascade of maturational processes orchestrated by gonadal hormones. Although individual variability in puberty onset confounds adolescent studies, it has not been efficiently controlled for. Here we introduce ultrasonic bone age assessment to estimate biological maturity and disentangle the independent effects of chronological and biological age on adolescent cognitive abilities. Comparing cognitive performance of participants with different skeletal maturity we uncover the striking impact of biological age on both IQ and specific abilities. We find that biological age has a selective effect on abilities: more mature individuals within the same age group have higher working memory capacity and processing speed, while those with higher chronological age have better verbal abilities, independently of their maturity. Bone age appears to be a surprisingly strong predictor of cognitive abilities, and it seems that a teens IQ is determined by biological age.

neuroscience↗

bioRxiv2020

A new set of composite, non-redundant electroencephalogram measures of non-rapid eye movement sleep based on the power law scaling of the Fourier spectrum

A novel method for deriving composite, non-redundant measures of non-rapid eye movement (NREM) sleep electroencephalogram (EEG) is developed on the basis of the power law scaling of the Fourier spectra. Measures derived are the spectral intercept, the slope (spectral exponent), as well as the maximal whitened spectral peak amplitude and frequency in the sleep spindle range. As a proof of concept, we apply these measures on a large sleep EEG dataset (N = 175; 81 females; age range: 17-60 years) with previously demonstrated effects of age, sex and intelligence. As predicted, aging is associated with decreased overall spectral slopes (increased exponents) and whitened spectral peak amplitudes in the spindle frequency range. In addition, age associates with decreased sleep spindle spectral peak frequencies in the frontal region. Women were characterized by higher spectral intercepts and higher spectral peak frequencies in the sleep spindle range. No sex differences in whitened spectral peak amplitudes of the sleep spindle range were found. Intelligence correlated positively with whitened spectral peak amplitudes of the spindle frequency range in women, but not in men. Last, age-related increases in spectral exponents did not differ in subjects with average and high intelligence. Our findings replicate and complete previous reports in the literature, indicating that the number of variables describing NREM sleep EEG can be effectively reduced in order to overcome redundancy and Type I statistical errors in future electrophysiological studies of sleep. Author summaryGiven the tight reciprocal relationship between sleep and wakefulness, the objective description of the complex neural activity patterns characterizing human sleep is of utmost importance in understanding the several facets of brain function, like sex differences, aging and cognitive abilities. Current approaches are either exclusively based on visual impressions expressed in graded levels of sleep depth (W, N1, N2, N3, REM), whereas computerized quantitative methods provide an almost infinite number of potential metrics, suffering from significant redundancy and arbitrariness. Our current approach relies on the assumptions that the spontaneous human brain activity as reflected by the scalp-derived electroencephalogram (EEG) are characterized by coloured noise-like properties. That is, the contribution of different frequencies to the power spectrum of the signal are best described by power law functions with negative exponents. In addition, we assume, that stages N2-N3 are further characterized by additional non-random (non-noise like, sinusoidal) activity patterns, which are emerging at specific frequencies, called sleep spindles (9-18 Hz). By relying on these assumptions we were able to effectively reduce 191 spectral measures to 4: (1) the spectral intercept reflecting the overall amplitude of the signal, (2) the spectral slope reflecting the constant ratio of low over high frequency power, (3) the frequency of the maximal sleep spindle activity and (4) the amplitude of the sleep spindle spectral peak. These 4 measures 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.

neuroscience↗

bioRxiv2019

The laminar profile of sleep spindles in humans

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.

neuroscience↗

bioRxiv2018

The paradox of Rapid Eye Movement sleep in the light of oscillatory activity and functional synchronization during phasic and tonic microstates

Rapid Eye Movement (REM) sleep is a peculiar neural state showing a combination of muscle atonia and intense cortical activity. REM sleep is usually considered as a unitary state in neuroscientific research; however, it is composed of two different microstates: phasic and tonic REM. These differ in awakening thresholds, sensory processing, and cortical oscillations. Nevertheless, studies examining cortical oscillations during REM microstates are scarce, and used low spatial sampling. Here, we analyzed the data of 18 healthy individuals assessed by high-density sleep EEG recordings. We systematically contrasted phasic and tonic REM periods in terms of topographical distribution, source localization, as well as local, global and long-range synchronization of frequency-specific cortical activity. Tonic periods showed relatively increased high alpha and beta power over frontocentral derivations. In addition, higher frequency components of beta power exhibited increased global synchronization during tonic compared to phasic states. In contrast, in phasic periods we found increased power and synchronization of low frequency oscillations coexisting with increased and synchronized gamma activity. Source localization revealed several multimodal, higher-order associative, as well as sensorimotor areas as potential sources of increased high alpha/beta power during tonic compared to phasic REM. Increased gamma power in phasic REM was attributed to medial prefrontal and right lateralized temporal areas associated with emotional processing. Our findings emphasize the heterogeneous nature of REM sleep, expressed in two microstates with remarkably different neural activity. Considering the microarchitecture of REM sleep may provide new insights into the mechanisms of REM sleep in health and disease.\n\nSignificance StatementRapid Eye movement (REM) is composed of the alternation of two markedly different microstates: phasic and tonic REM. Here we present the first high-resolution topographical study that systematically contrasted spectral power, neural synchronization and brain topography of spontaneous cortical oscillations across phasic and tonic microstates. Phasic REM was characterized by the combination of synchronized low frequency oscillations resembling deeper sleep stages and high frequency oscillations reflecting intense cortical activity. In contrast, tonic REM sleep showed increased oscillatory activity in the alpha and beta ranges that may reflect a shift towards increased environmental alertness resembling resting wakefulness. Exploring the neurophysiological aspects of REM microstates may shed new light on the mechanisms of REM sleep in healthy and pathological conditions.

neuroscience↗