Biology subjects

Szatkowska, I.

Publications and source records attributed to Szatkowska, I..

6 recordsLinked to original sources

bioRxiv2025

Circadian rhythm distinctness predicts academic performance based on large-scale learning management system data

The subjective amplitude of circadian oscillations (distinctness) is an understudied dimension of circadian rhythmicity, which describes how strongly mood and cognition fluctuate during the day. Emerging evidence suggests that distinctness may be as important as chronotype in regulating the temporal organization of key physiological processes. Previous studies have relied on questionnaires and lacked an objective measure of distinctness. Here, we propose the first objective behavioral measure of distinctness based on circular statistics. We applied this approach to 3.4 million login events from 13,894 unique university students and found a non-linear association between distinctness and academic performance: students with moderate daily rhythmicity achieved the highest performance. This relationship varied by chronotype: larks benefited from stronger rhythms, finches from moderate rhythms, and owls from weaker, more flexible rhythms. Circadian distinctness was also closely linked to social jetlag, which increased with more rigid rhythmicity across chronotypes. These findings suggest that the academic disadvantage often attributed to specific chronotypes does not stem from time preference itself, but from the overall interplay of chronotype, distinctness, and schedules that are incompatible with individual biological timings. Considering rhythm flexibility alongside chronotype may therefore improve educational design and equity.

animal behavior and cognition↗

bioRxiv2025

Divergent disruption of brain networks following total and chronic sleep loss: a longitudinal fMRI study

Study objectivesSleep loss significantly disrupts cognitive and emotional functioning, yet the neural consequences of different types of sleep deprivation remain unclear. MethodsIn a within-subject resting-state fMRI study, we examined how acute total sleep deprivation (TSD) and chronic sleep restriction (CSR) alter intrinsic functional brain organization in 28 healthy adults scanned under three conditions: rested wakefulness (RW), after one night of TSD, and after five nights of CSR. To quantify network-level disruption, we applied graph-theoretical analyses, including a novel within-subject adaptation of the Hub Disruption Index and Covariate-Constrained Manifold Learning (CCML), an unsupervised embedding technique sensitive to subject-level covariates. Moreover, we assessed subjective sleep quality, sleepiness, and circadian traits. ResultsBoth TSD and CSR were associated with a consistent reorganization of graph topology relative to RW. Furthermore, direct comparisons revealed that TSD and CSR affect different brain hubs. Regional changes in degree, closeness, and clustering coefficients were most prominent in subsystems of the default mode network, frontoparietal network, and cerebellum. These differences were also captured in CCML embeddings, supporting the hypothesis that acute and chronic sleep deprivation exert divergent effects on brain connectivity. Findings were robust across graph thresholds, brain atlases, and nodal metrics. Moreover, these results were further supported by the subjective measures - sleepiness was associated with reduced network integration in RW, and circadian phenotype emerged as a key determinant of individual sensitivity to sleep loss. ConclusionsOur results show that TSD and CSR induce distinct alterations in brain functional organization, offering new insights into their neural impact. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=157 HEIGHT=200 SRC="FIGDIR/small/681651v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@1f24790org.highwire.dtl.DTLVardef@1387233org.highwire.dtl.DTLVardef@d18e97org.highwire.dtl.DTLVardef@1e88a15_HPS_FORMAT_FIGEXP M_FIG C_FIG Statement of significanceSleep deprivation is a growing public health concern, yet it remains unclear whether total and chronic sleep loss affect the brain in the same way. In this study, participants underwent one sleepless night and five consecutive days of reduced sleep (as in working week). We found that these two forms of sleep loss disrupt brain networks in fundamentally different ways. This distinction closes a critical gap in understanding how the brain responds to the total and chronic sleep loss. Recognizing that not all sleep deprivation is alike has important implications for managing fatigue in occupational, educational, and clinical contexts. Our findings highlight the need for personalized strategies to protect brain health and performance under conditions of sleep disruption.

neuroscience↗

bioRxiv2025

Circadian rhythmicity and reinforcement processing: a dataset of MRI, fMRI, and behavioral measurements

Circadian rhythmicity is a complex phenomenon that influences human behavior, emotionality and brain activity. A detailed description of individual differences in circadian rhythmicity could inform the design of educational systems, shift-worker schedules, and daily routines. Here we present a comprehensive dataset for studying diurnal rhythms and their relationship with human behavior. Thirty seven male participants (aged 20-30) filled in validated psychometric questionnaires assessing characteristics of the circadian rhythm, sleep quality, emotionality, personality traits, reward-punishment processing and attention deficits. Moreover, we acquired high-resolution anatomical T1-weighted images using magnetic resonance imaging (MRI), B0 fieldmaps for distortion corrections, and functional MRI (fMRI) during the Monetary Incentive Delay (MID) task, which is a common paradigm to assess human neural reinforcement processing. All files are organized in Brain Imaging Data Structure (BIDS) and openly available on OpenNeuro.org. The validation of all data confirmed high-quality of described dataset. The various psychological measures combined with neuroimaging data provide strong foundation for exploring emotionality, affective processing, and attention in the context of brain activity and circadian influences.

neuroscience↗

bioRxiv2024

High distinctness of circadian rhythm is related to negative emotionality and enhanced neural processing of punishment-related information in men

For years, research on the human biological clock has focused primarily on chronotype (phase of the circadian rhythm). However, a second dimension - distinctness (subjective amplitude) of the rhythm, has so far been overlooked. This study aimed to explore the intricate interplay between psychometric traits and reward-punishment processing, considering both chronotype and distinctness. Circadian rhythmicity characteristics of 37 healthy men (aged 20-30) were measured using the Morningness-Eveningness-Stability-Scale improved (MESSi) questionnaire. We also employed a battery of psychometric questionnaires and used functional magnetic resonance (fMRI) during the Monetary Incentive Delay task, which is a common method of assessing reward-punishment processing. We found a positive association between distinctness and the activity in the bilateral Superior Frontal Gyrus (SFG), Supplementary Motor Area (SMA) and Ventral Tegmental Area (VTA) during processing of punishment cues. These results are consistent with psychometric findings - a significant positive association between distinctness and sensitivity to punishment, neuroticism, behavioral inhibition system (BIS), attention deficits, and negative emotionality. As regards eveningness, we found its negative association only with sensitivity to punishment and BIS. These results highlight the crucial role of distinctness in human functioning, especially in terms of punishment processing and negative emotionality.

neuroscience↗

bioRxiv2023

The subjective amplitude of the diurnal rhythm matters - chronobiological insights for neuroimaging studies

Multiple aspects of human physiology, including mood and cognition, are subjected to diurnal rhythms. While the previous neuroimaging studies have focused solely on the morningness-eveningness (ME) preference dichotomy, i.e. the circadian phase, the second key dimension of the diurnal rhythms, i.e. the strength of these preferences (amplitude; AM), has been completely overlooked. Uncovering the neural correlates of AM is especially important considering its link with negative emotionality. Structural T1-weighted neuroimaging data from 79 early (EC) and 74 late (LC) chronotypes were analysed to compare grey matter (GM) volume and cortical thickness. The study aimed to elucidate whether the subjective AM and its interaction with ME was a significant predictor of individual brain structure. Both GM volume and cortical thickness of the left primary visual cortex was negatively correlated with AM scores across the entire sample. Furthermore, EC and LC differed in their association between AM scores and the GM volume in the right middle temporal gyrus, with the positive and negative correlations reported respectively in the two groups. The current study underlines the importance of the visual system in circadian rhythmicity and provides possible neural correlates for AM-related differences in negative affect processing. Furthermore, the presence of the opposite correlations between brain anatomy and AM in the two groups suggests that the behavioural and neuronal chronotype differences might become more pronounced in individuals with extreme diurnal differences in mood and cognition, highlighting the necessity to additionally account for AM in neuroimaging studies. HighlightsO_LIStructure of primary visual cortex is linked to subjective diurnal rhythms amplitude C_LIO_LIMiddle temporal gyrus is sensitive to interaction of rhythm phase and distinctness C_LIO_LIDistinctness of the diurnal rhythms may modulate results of the neuroimaging studies C_LI

neuroscience↗

bioRxiv2020

Parcellation of the human amygdala using recurrence quantification analysis

Several previous attempts have been made to divide the human amygdala into smaller subregions based on the unique functional properties of the subregions. Although these attempts have provided valuable insight into the functional heterogeneity in this structure, the possibility that spatial patterns of functional characteristics can quickly change over time has been neglected in previous studies. In the present study, we explicitly account for the dynamic nature of amygdala activity. Our goal was not only to develop another parcellation method but also to augment existing methods with novel information about amygdala subdivisions. We performed state-specific amygdala parcellation using resting-state fMRI (rsfMRI) data and recurrence quantification analysis (RQA). RsfMRI data from 102 subjects were acquired with a 3T Trio Siemens scanner. We analyzed values of several RQA measures across all voxels in the amygdala and found two amygdala subdivisions, the ventrolateral (VL) and dorsomedial (DM) subdivisions, that differ with respect to one of the RQA measures, Shannons entropy of diagonal lines. Compared to the DM subdivision, the VL subdivision can be characterized by a higher value of entropy. The results suggest that VL activity is determined and influenced by more brain structures than is DM activity. To assess the biological validity of the obtained subdivisions, we compared them with histological atlases and currently available parcellations based on structural connectivity patterns (Anatomy Probability Maps) and cytoarchitectonic features (SPM Anatomy toolbox). Moreover, we examined their cortical and subcortical functional connectivity. The obtained results are similar to those previously reported on parcellation performed on the basis of structural connectivity patterns. Functional connectivity analysis revealed that the VL subdivision has strong connections to several cortical areas, whereas the DM subdivision is mainly connected to subcortical regions. This finding suggests that the VL subdivision corresponds to the basolateral subdivision of the amygdala (BLA), while the DM subdivision has some characteristics typical of the centromedial amygdala (CMA). The similarity in functional connectivity patterns between the VL subdivision and BLA, as well as between the DM subdivision and CMA, confirm the utility of our parcellation method. Overall, the study shows that parcellation based on BOLD signal dynamics is a powerful tool for identifying distinct functional systems within the amygdala. This tool might be useful for future research on functional brain organization. HighlightsO_LIA new method for parcellation of the human amygdala was developed C_LIO_LIThe ventrolateral and dorsomedial subdivisions of the amygdala were revealed C_LIO_LIThe two subdivisions correspond to the anatomically defined regions of the amygdala C_LIO_LIThe two subdivisions differ with respect to values of entropy C_LIO_LIA new parcellation method provides novel information about amygdala subdivisions C_LI

neuroscience↗