Sex Differences in Magnetoencephalography-Identified Functional Connectivity in the Human Connectome Project Connectomics of Brain Aging and Dementia Cohort

Psychosis proneness has been linked to heightened Openness to Experience and to cognitive deficits. Openness and psychotic disorders are associated with the default and frontoparietal networks, and the latter network is also robustly associated with intelligence. We tested the hypothesis that functional connectivity of the default and frontoparietal networks is a neural correlate of the openness-psychoticism dimension. Participants in the Human Connectome Project (N = 1003) completed measures of psychoticism, openness, and intelligence. Resting state functional magnetic resonance imaging was used to identify intrinsic connectivity networks. Structural equation modeling revealed relations among personality, intelligence, and network coherence. Psychoticism, openness, and especially their shared variance, were related positively to default network coherence and negatively to frontoparietal coherence. These associations remained after controlling for intelligence. Intelligence was positively related to frontoparietal coherence. Research suggests psychoticism and openness are linked in part through their association with connectivity in networks involving experiential simulation and cognitive control. We propose a model of psychosis risk that highlights roles of the default and frontoparietal networks. Findings echo research on functional connectivity in psychosis patients, suggesting shared mechanisms across the personality-psychopathology continuum.

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Role of glial cells in the generation of sex differences in neurodegenerative diseases and brain aging

Mechanisms of Ageing and Development ◽

10.1016/j.mad.2021.111473 ◽

2021 ◽

pp. 111473

Author(s):

Julie A. Chowen ◽

Luis M. Garcia-Segura

Keyword(s):

Sex Differences ◽

Neurodegenerative Diseases ◽

Glial Cells ◽

Brain Aging

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Heritability and interindividual variability of regional structure-function coupling

Nature Communications ◽

10.1038/s41467-021-25184-4 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Zijin Gu ◽

Keith Wakefield Jamison ◽

Mert Rory Sabuncu ◽

Amy Kuceyeski

Keyword(s):

Functional Connectivity ◽

Structure Function ◽

Regional Differences ◽

Regional Scale ◽

Brain Regions ◽

Diffusion Weighted Mri ◽

Regional Structure ◽

Human Connectome Project ◽

Structural Connections ◽

The Relationship

AbstractWhite matter structural connections are likely to support flow of functional activation or functional connectivity. While the relationship between structural and functional connectivity profiles, here called SC-FC coupling, has been studied on a whole-brain, global level, few studies have investigated this relationship at a regional scale. Here we quantify regional SC-FC coupling in healthy young adults using diffusion-weighted MRI and resting-state functional MRI data from the Human Connectome Project and study how SC-FC coupling may be heritable and varies between individuals. We show that regional SC-FC coupling strength varies widely across brain regions, but was strongest in highly structurally connected visual and subcortical areas. We also show interindividual regional differences based on age, sex and composite cognitive scores, and that SC-FC coupling was highly heritable within certain networks. These results suggest regional structure-function coupling is an idiosyncratic feature of brain organisation that may be influenced by genetic factors.

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Association Between Brain Activation and Functional Connectivity

Cerebral Cortex ◽

10.1093/cercor/bhy077 ◽

2018 ◽

Vol 29 (5) ◽

pp. 1984-1996 ◽

Cited By ~ 13

Author(s):

Dardo Tomasi ◽

Nora D Volkow

Keyword(s):

Functional Connectivity ◽

Brain Activity ◽

Low Frequency ◽

Brain Activation ◽

Blood Oxygen Level Dependent ◽

Common Source ◽

Functional Connectivity Density ◽

Density Mapping ◽

Human Connectome Project ◽

Bold Responses

Abstract The origin of the “resting-state” brain activity recorded with functional magnetic resonance imaging (fMRI) is still uncertain. Here we provide evidence for the neurovascular origins of the amplitude of the low-frequency fluctuations (ALFF) and the local functional connectivity density (lFCD) by comparing them with task-induced blood-oxygen level dependent (BOLD) responses, which are considered a proxy for neuronal activation. Using fMRI data for 2 different tasks (Relational and Social) collected by the Human Connectome Project in 426 healthy adults, we show that ALFF and lFCD have linear associations with the BOLD response. This association was significantly attenuated by a novel task signal regression (TSR) procedure, indicating that task performance enhances lFCD and ALFF in activated regions. We also show that lFCD predicts BOLD activation patterns, as was recently shown for other functional connectivity metrics, which corroborates that resting functional connectivity architecture impacts brain activation responses. Thus, our findings indicate a common source for BOLD responses, ALFF and lFCD, which is consistent with the neurovascular origin of local hemodynamic synchrony presumably reflecting coordinated fluctuations in neuronal activity. This study also supports the development of task-evoked functional connectivity density mapping.

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Functional connectivity of fMRI using differential covariance predicts structural connectivity and behavioral reaction times

10.1101/2021.09.01.458609 ◽

2021 ◽

Author(s):

Yusi Chen ◽

Qasim Bukhari ◽

Tiger Wutu Lin ◽

Terrence J Sejnowski

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Functional Connectivity ◽

Resting State ◽

Structural Connectivity ◽

Reaction Times ◽

Resonance Imaging ◽

Brain Areas ◽

Human Connectome Project ◽

Wide Range

Recordings from resting state functional magnetic resonance imaging (rs-fMRI) reflect the influence of pathways between brain areas. A wide range of methods have been proposed to measure this functional connectivity (FC), but the lack of ''ground truth'' has made it difficult to systematically validate them. Most measures of FC produce connectivity estimates that are symmetrical between brain areas. Differential covariance (dCov) is an algorithm for analyzing FC with directed graph edges. Applied to synthetic datasets, dCov-FC was more effective than covariance and partial correlation in reducing false positive connections and more accurately matching the underlying structural connectivity. When we applied dCov-FC to resting state fMRI recordings from the human connectome project (HCP) and anesthetized mice, dCov-FC accurately identified strong cortical connections from diffusion Magnetic Resonance Imaging (dMRI) in individual humans and viral tract tracing in mice. In addition, those HCP subjects whose rs-fMRI were more integrated, as assessed by a graph-theoretic measure, tended to have shorter reaction times in several behavioral tests. Thus, dCov-FC was able to identify anatomically verified connectivity that yielded measures of brain integration causally related to behavior.

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Impact of prenatal maternal cytokine exposure on sex differences in brain circuitry regulating stress in offspring 45 years later

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2014464118 ◽

2021 ◽

Vol 118 (15) ◽

pp. e2014464118

Author(s):

Jill M. Goldstein ◽

Justine E. Cohen ◽

Klara Mareckova ◽

Laura Holsen ◽

Susan Whitfield-Gabrieli ◽

...

Keyword(s):

Sex Differences ◽

Functional Connectivity ◽

Proinflammatory Cytokines ◽

Brain Activity ◽

In Utero ◽

Anterior Cingulate ◽

Hippocampal Activity ◽

Brain Circuitry ◽

Anti Inflammatory ◽

In Utero Development

Stress is associated with numerous chronic diseases, beginning in fetal development with in utero exposures (prenatal stress) impacting offspring’s risk for disorders later in life. In previous studies, we demonstrated adverse maternal in utero immune activity on sex differences in offspring neurodevelopment at age seven and adult risk for major depression and psychoses. Here, we hypothesized that in utero exposure to maternal proinflammatory cytokines has sex-dependent effects on specific brain circuitry regulating stress and immune function in the offspring that are retained across the lifespan. Using a unique prenatal cohort, we tested this hypothesis in 80 adult offspring, equally divided by sex, followed from in utero development to midlife. Functional MRI results showed that exposure to proinflammatory cytokines in utero was significantly associated with sex differences in brain activity and connectivity during response to negative stressful stimuli 45 y later. Lower maternal TNF-α levels were significantly associated with higher hypothalamic activity in both sexes and higher functional connectivity between hypothalamus and anterior cingulate only in men. Higher prenatal levels of IL-6 were significantly associated with higher hippocampal activity in women alone. When examined in relation to the anti-inflammatory effects of IL-10, the ratio TNF-α:IL-10 was associated with sex-dependent effects on hippocampal activity and functional connectivity with the hypothalamus. Collectively, results suggested that adverse levels of maternal in utero proinflammatory cytokines and the balance of pro- to anti-inflammatory cytokines impact brain development of offspring in a sexually dimorphic manner that persists across the lifespan.

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Are sex differences in human brain structure associated with sex differences in behaviour?

10.31234/osf.io/8fcve ◽

2021 ◽

Author(s):

Liza van Eijk ◽

Dajiang Zhu ◽

Baptiste Couvy-Duchesne ◽

Lachlan T Strike ◽

Anthony J Lee ◽

...

Keyword(s):

Sex Differences ◽

Brain Structure ◽

Brain Size ◽

Imaging Study ◽

Data Driven ◽

Cultural Norms ◽

Weak Association ◽

Human Connectome Project ◽

Using Data ◽

Behavioural Sex Differences

On average, men and women differ in brain structure and behaviour, raising the possibility of a link between sex differences in brain and behaviour. But women and men are also subject to different societal and cultural norms. We navigated this challenge by investigating variability of sex-differentiated brain structure within each sex. Using data from the Queensland Twin IMaging study (N=1,040) and Human Connectome Project (N=1,113), we obtained data-driven measures of individual differences along a male-female dimension for brain and behaviour based on average sex differences in brain structure and behaviour, respectively. We found a weak association between these brain and behavioural differences, driven by brain size. These brain and behavioural differences were moderately heritable. Our findings suggest that behavioural sex differences are to some extent related to sex differences in brain structure, but that this is mainly driven by differences in brain size, and causality should be interpreted cautiously.

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Body mass variability is represented by distinct functional connectivity patterns

10.31232/osf.io/b9ahw ◽

2018 ◽

Author(s):

Jennifer R Sadler ◽

Grace Elisabeth Shearrer ◽

Kyle Stanley Burger

Keyword(s):

Functional Connectivity ◽

Body Mass ◽

Visual Processing ◽

Weight Status ◽

Design Sensitivity ◽

Human Connectome Project ◽

Connectivity Patterns ◽

Discordant Twins ◽

Project Data ◽

Discordant Twin

Understanding weight-related differences in functional connectivity provides key insight into neurocognitive factors implicated in obesity. Here, we sampled three groups from human connectome project data: 1) 47 pairs of BMI-discordant twins (n=94; average BMI-discordancy 6.7 3.1 kg/m2), 2) 47 pairs of gender and BMI matched BMI-discordant, unrelated individuals, and 3) 47 pairs of BMI-similar twins to test for body mass dependent differences in between network functional connectivity. Across BMI discordant samples, three networks appeared to be highly sensitivity to weight status; specifically, a network compromised of gustatory processing regions, a visual processing network, and the default mode network (DMN). Further, individuals with a lower BMI relative to their twin had stronger connectivity between striatal/thalamic and prefrontal networks (pFWE = 0.04) in the BMI-discordant twin sample. Cortical-striatal-thalamic networks underlie regulation of hedonically motivated behaviors. Stronger connectivity may facilitate increased regulation of decision-making when presented with highly rewarding, energy-dense foods. We also observed that individuals with a higher BMI than their twin had stronger connectivity between cerebellar and insular networks (pFWE = 0.04). Increased cerebellar-insula connectivity is associated with caloric deprivation and, in high BMI individuals, is associated compromised satiation signaling, thereby increasing risk for postprandial food intake. Connectivity patterns observed in the BMI-discordant twin sample were not see in a BMI-similar sample, providing evidence that the results are specific to BMI discordance. Beyond the involvement of gustatory and visual networks and the DMN, little overlap in results were seen between the two BMI-discordant samples. This may be a function of the higher study design sensitivity in the BMI-discordant twin sample, relative to the more generalizable results in the unrelated sample. These findings demonstrate that distinct connectivity patterns can represent weight variability, adding to mounting evidence that implicates atypical brain functioning with the accumulation and/or maintenance of elevated weight.

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Brain network dynamics correlate with personality traits

10.1101/702266 ◽

2019 ◽

Cited By ~ 1

Author(s):

Aya Kabbara ◽

Veronique Paban ◽

Arnaud Weill ◽

Julien Modolo ◽

Mahmoud Hassan

Keyword(s):

Functional Connectivity ◽

Personality Traits ◽

Resting State ◽

Brain Networks ◽

Neural Substrates ◽

Brain Network ◽

Functional Brain ◽

Human Connectome Project ◽

Functional Brain Networks ◽

The Brain

AbstractIntroductionIdentifying the neural substrates underlying the personality traits is a topic of great interest. On the other hand, it is now established that the brain is a dynamic networked system which can be studied using functional connectivity techniques. However, much of the current understanding of personality-related differences in functional connectivity has been obtained through the stationary analysis, which does not capture the complex dynamical properties of brain networks.ObjectiveIn this study, we aimed to evaluate the feasibility of using dynamic network measures to predict personality traits.MethodUsing the EEG/MEG source connectivity method combined with a sliding window approach, dynamic functional brain networks were reconstructed from two datasets: 1) Resting state EEG data acquired from 56 subjects. 2) Resting state MEG data provided from the Human Connectome Project. Then, several dynamic functional connectivity metrics were evaluated.ResultsSimilar observations were obtained by the two modalities (EEG and MEG) according to the neuroticism, which showed a negative correlation with the dynamic variability of resting state brain networks. In particular, a significant relationship between this personality trait and the dynamic variability of the temporal lobe regions was observed. Results also revealed that extraversion and openness are positively correlated with the dynamics of the brain networks.ConclusionThese findings highlight the importance of tracking the dynamics of functional brain networks to improve our understanding about the neural substrates of personality.

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