Gender-based functional connectivity differences in brain networks in childhood

İçer, Semra; Acer, İrem; Baş, Abdullah

doi:10.1016/j.cmpb.2020.105444

Cited by 13 publications

(9 citation statements)

References 60 publications

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“…Additionally, the thresholded analysis showed significant positive correlations between D-RT in the Easy and Medium states for both H(2) and H 15 networks, warranting further investigation in future studies (Supplementary Figure 2). While a growing number of publications investigates the FC-related differences between the two sexes (Zhang et al, 2018;Ýçer et al, 2020), we found no significant sex-related differences in network architecture. Since the studies mentioned above had higher spatial resolution (higher density EEG or fMRI recordings), we believe that future experiments with higher number of EEG channels might be able to reveal such differences.…”

Section: Discussioncontrasting

confidence: 74%

Multifractal Functional Connectivity Analysis of Electroencephalogram Reveals Reorganization of Brain Networks in a Visual Pattern Recognition Paradigm

Stylianou

Racz

Kim

et al. 2021

Front. Hum. Neurosci.

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The human brain consists of anatomically distant neuronal assemblies that are interconnected via a myriad of synapses. This anatomical network provides the neurophysiological wiring framework for functional connectivity (FC), which is essential for higher-order brain functions. While several studies have explored the scale-specific FC, the scale-free (i.e., multifractal) aspect of brain connectivity remains largely neglected. Here we examined the brain reorganization during a visual pattern recognition paradigm, using bivariate focus-based multifractal (BFMF) analysis. For this study, 58 young, healthy volunteers were recruited. Before the task, 3-3 min of resting EEG was recorded in eyes-closed (EC) and eyes-open (EO) states, respectively. The subsequent part of the measurement protocol consisted of 30 visual pattern recognition trials of 3 difficulty levels graded as Easy, Medium, and Hard. Multifractal FC was estimated with BFMF analysis of preprocessed EEG signals yielding two generalized Hurst exponent-based multifractal connectivity endpoint parameters, H(2) and ΔH15; with the former indicating the long-term cross-correlation between two brain regions, while the latter captures the degree of multifractality of their functional coupling. Accordingly, H(2) and ΔH15 networks were constructed for every participant and state, and they were characterized by their weighted local and global node degrees. Then, we investigated the between- and within-state variability of multifractal FC, as well as the relationship between global node degree and task performance captured in average success rate and reaction time. Multifractal FC increased when visual pattern recognition was administered with no differences regarding difficulty level. The observed regional heterogeneity was greater for ΔH15 networks compared to H(2) networks. These results show that reorganization of scale-free coupled dynamics takes place during visual pattern recognition independent of difficulty level. Additionally, the observed regional variability illustrates that multifractal FC is region-specific both during rest and task. Our findings indicate that investigating multifractal FC under various conditions – such as mental workload in healthy and potentially in diseased populations – is a promising direction for future research.

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Section: Discussioncontrasting

confidence: 74%

Multifractal Functional Connectivity Analysis of Electroencephalogram Reveals Reorganization of Brain Networks in a Visual Pattern Recognition Paradigm

Stylianou

Racz

Kim

et al. 2021

Front. Hum. Neurosci.

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“…While not a main question of the current study, the main effect of sex was also investigated given the report of sex differences in FC using resting-state functional MRI data in typically developing children. [57] In a sample of 7-18-year-old children, females showed more broadly distributed stronger connections in comparison to males, particularly in the left hemisphere, [58] which is also what our data showed (Figure 3A). However, we also reported larger FC in males than females.…”

Section: Discussionsupporting

confidence: 89%

Assessing the relationship between maternal risk for attention deficit hyperactivity disorder and functional connectivity in their biological toddlers

et al. 2022

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BackgroundAttention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder associated with increased risk for poor educational attainment and compromised social integration. Currently, clinical diagnosis rarely occurs before school-age, despite behavioral signs of ADHD in very early childhood. There is no known brain biomarker for ADHD risk in children ages 2-3 years-old. MethodsThe current study aimed to investigate the functional connectivity (FC) associated with ADHD risk in 70 children aged 2.5 and 3.5 years via functional Near-Infrared Spectroscopy (fNIRS) in bilateral frontal and parietal cortices; regions involved in attentional and goal-directed cognition.Children were instructed to passively watch videos for approximately 5 minutes. Risk for ADHD in each child was assessed via maternal symptoms of ADHD, and brain data was evaluated for FC. ResultsHigher risk for Maternal ADHD was associated with lower FC in a left-sided parieto-frontal network. Further, the interaction between sex and risk for ADHD was significant, where FC reduction in a widespread bilateral parieto-frontal network was associated with higher risk in male, but not female, participants. ConclusionsThese findings suggest functional organization differences in the parietal-frontal network in toddlers at risk for ADHD; potentially advancing the understanding of the neural mechanisms underlying the development of ADHD.

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“…Some studies report differences in the networks that exhibit high functional connectivity in women and men 34 , and men have higher functional connectivity between cognitive and sensorimotor regions than women 34 . In contrast, others have reported reduced functional connectivity across various networks in males versus females 35 , or no differences 36 , with more recent investigations documenting sex differences. In one uniquely robust study, several resting state data sets were used to determine brain region classifiers for sex differences and these included regions such as the cingulate cortex and other limbic and prefrontal cortical regions 37 .…”

Section: Discussionmentioning

confidence: 86%

Robustness of sex-differences in functional connectivity over time in middle-aged marmosets

Nephew

Febo

Cali

et al. 2020

Sci Rep

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Nonhuman primates (NHPs) are an essential research model for gaining a comprehensive understanding of the neural mechanisms of neurocognitive aging in our own species. In the present study, we used resting state functional connectivity (rsFC) to investigate the relationship between prefrontal cortical and striatal neural interactions, and cognitive flexibility, in unanaesthetized common marmosets (Callithrix jacchus) at two time points during late middle age (8 months apart, similar to a span of 5–6 years in humans). Based on our previous findings, we also determine the reproducibility of connectivity measures over the course of 8 months, particularly previously observed sex differences in rsFC. Male marmosets exhibited remarkably similar patterns of stronger functional connectivity relative to females and greater cognitive flexibility between the two imaging time points. Network analysis revealed that the consistent sex differences in connectivity and related cognitive associations were characterized by greater node strength and/or degree values in several prefrontal, premotor and temporal regions, as well as stronger intra PFC connectivity, in males compared to females. The current study supports the existence of robust sex differences in prefrontal and striatal resting state networks that may contribute to differences in cognitive function and offers insight on the neural systems that may be compromised in cognitive aging and age-related conditions such as mild cognitive impairment and Alzheimer’s disease.

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Gender-based functional connectivity differences in brain networks in childhood

Cited by 13 publications

References 60 publications

Multifractal Functional Connectivity Analysis of Electroencephalogram Reveals Reorganization of Brain Networks in a Visual Pattern Recognition Paradigm

Multifractal Functional Connectivity Analysis of Electroencephalogram Reveals Reorganization of Brain Networks in a Visual Pattern Recognition Paradigm

Assessing the relationship between maternal risk for attention deficit hyperactivity disorder and functional connectivity in their biological toddlers

Robustness of sex-differences in functional connectivity over time in middle-aged marmosets

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