scholarly journals Sex differences in brain correlates of STEM anxiety

2019 ◽  
Author(s):  
Ariel A. Gonzalez ◽  
Katherine L. Bottenhorn ◽  
Jessica E. Bartley ◽  
Timothy Hayes ◽  
Michael C. Riedel ◽  
...  
Keyword(s):  
Sex Differences ◽  
Academic Performance ◽  
Large Scale ◽  
Math Anxiety ◽  
Brain Connectivity ◽  
Learning Experience ◽  
Network Connectivity ◽  
Male Students ◽  
Stem Learning ◽  
Default Mode

ABSTRACTAnxiety is known to dysregulate the salience, default mode, and central executive networks of the human brain, yet this phenomenon has not been fully explored across the STEM learning experience, where anxiety can impact negatively academic performance. Here, we evaluated anxiety and large-scale brain connectivity in 101 undergraduate physics students. We found sex differences in STEM-related but not clinical anxiety, with longitudinal increases in science anxiety observed for both female and male students. Sex-specific impacts of STEM anxiety on brain connectivity emerged, with male students exhibiting distinct inter-network connectivity for STEM and clinical anxiety and female students demonstrating no significant within-sex correlations. Anxiety was negatively correlated with academic performance in sex-specific ways at both pre-and post-instruction. Moreover, math anxiety in male students mediated the relation between default mode-salience connectivity and course grade. Together, these results reveal complex sex differences in the neural mechanisms driving how anxiety impacts STEM learning.

scholarly journals Sex differences in brain correlates of STEM anxiety

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Ariel A. Gonzalez ◽  
Katherine L. Bottenhorn ◽  
Jessica E. Bartley ◽  
Timothy Hayes ◽  
Michael C. Riedel ◽  
...  
Keyword(s):  
Sex Differences ◽  
Academic Performance ◽  
Large Scale ◽  
Math Anxiety ◽  
Brain Connectivity ◽  
Learning Experience ◽  
Network Connectivity ◽  
Male Students ◽  
Stem Learning ◽  
Default Mode

Abstract Anxiety is known to dysregulate the salience, default mode, and central executive networks of the human brain, yet this phenomenon has not been fully explored across the STEM learning experience, where anxiety can impact negatively academic performance. Here, we evaluated anxiety and large-scale brain connectivity in 101 undergraduate physics students. We found sex differences in STEM-related and clinical anxiety, with longitudinal increases in science anxiety observed for both female and male students. Sex-specific relationships between STEM anxiety and brain connectivity emerged, with male students exhibiting distinct inter-network connectivity for STEM and clinical anxiety, and female students demonstrating no significant within-sex correlations. Anxiety was negatively correlated with academic performance in sex-specific ways at both pre- and post-instruction. Moreover, math anxiety in male students mediated the relation between default mode-salience connectivity and course grade. Together, these results reveal complex sex differences in the neural mechanisms driving how anxiety is related to STEM learning.

scholarly journals Widespread attenuating changes in brain connectivity associated with the general factor of psychopathology in 9- and 10-year olds

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chandra Sripada ◽  
Mike Angstadt ◽  
Aman Taxali ◽  
Daniel Kessler ◽  
Tristan Greathouse ◽  
...  
Keyword(s):  
Large Scale ◽  
Brain Connectivity ◽  
Network Connectivity ◽  
Quadrant Analysis ◽  
Default Network ◽  
General Factor ◽  
Multiple Control ◽  
Control Networks ◽  
Large Scale Networks ◽  
P Factor

AbstractConvergent research identifies a general factor (“P factor”) that confers transdiagnostic risk for psychopathology. Large-scale networks are key organizational units of the human brain. However, studies of altered network connectivity patterns associated with the P factor are limited, especially in early adolescence when most mental disorders are first emerging. We studied 11,875 9- and 10-year olds from the Adolescent Brain and Cognitive Development (ABCD) study, of whom 6593 had high-quality resting-state scans. Network contingency analysis was used to identify altered interconnections associated with the P factor among 16 large-scale networks. These connectivity changes were then further characterized with quadrant analysis that quantified the directionality of P factor effects in relation to neurotypical patterns of positive versus negative connectivity across connections. The results showed that the P factor was associated with altered connectivity across 28 network cells (i.e., sets of connections linking pairs of networks); pPERMUTATION values < 0.05 FDR-corrected for multiple comparisons. Higher P factor scores were associated with hypoconnectivity within default network and hyperconnectivity between default network and multiple control networks. Among connections within these 28 significant cells, the P factor was predominantly associated with “attenuating” effects (67%; pPERMUTATION < 0.0002), i.e., reduced connectivity at neurotypically positive connections and increased connectivity at neurotypically negative connections. These results demonstrate that the general factor of psychopathology produces attenuating changes across multiple networks including default network, involved in spontaneous responses, and control networks involved in cognitive control. Moreover, they clarify mechanisms of transdiagnostic risk for psychopathology and invite further research into developmental causes of distributed attenuated connectivity.

scholarly journals Large-Scale Functional Networks, Cognition and Brain Structures Supporting Social Cognition and Theory of Mind Performance in Prodromal to Mild Alzheimer’s Disease

2021 ◽  
Vol 13 ◽  
Author(s):  
Jose Manuel Valera-Bermejo ◽  
Matteo De Marco ◽  
Micaela Mitolo ◽  
Chiara Cerami ◽  
Alessandra Dodich ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Social Cognition ◽  
Theory Of Mind ◽  
Large Scale ◽  
Grey Matter ◽  
Network Connectivity ◽  
Functional Networks ◽  
Default Mode ◽  
The Right

Impairment of social cognition (SC) skills such as recognition and attribution of intentions and affective states of others (Theory of Mind, ToM) has been evidenced in Alzheimer’s Disease (AD). This study investigated the neuropsychological, neuroanatomical and brain-functional underpinnings of SC processing to obtain an understanding of the social neurophenotype in early probable AD. Forty-six patients with mild cognitive impairment and mild probable AD underwent SC assessment including emotion recognition (Ekman-60-faces task) and cognitive and affective ToM (Reading-the-Mind-in-the-Eyes test and Story-based Empathy task). Linear models tested the association between SC scores and neuropsychological measures, grey matter maps and large-scale functional networks activity. The executive domain had the most predominant association with SC scores in the cognitive profile. Grey matter volume of the anterior cingulate, orbitofrontal, temporoparietal junction (TPJ), superior temporal, and cerebellar cortices were associated with ToM. Social cognition scores were associated with lower connectivity of the default-mode network with the prefrontal cortex. The right fronto-parietal network displayed higher inter-network connectivity in the right TPJ and insula while the salience network showed lower inter-network connectivity with the left TPJ and insula. Connectivity coupling alterations of executive-attentional networks may support default mode social-cognitive-associated decline through the recruitment of frontal executive mechanisms.

scholarly journals Altered functional connectivity of cortical networks in semantic variant Primary Progressive Aphasia

2020 ◽  
Author(s):  
Haroon Popal ◽  
Megan Quimby ◽  
Daisy Hochberg ◽  
Bradford C. Dickerson ◽  
Jessica A. Collins
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Large Scale ◽  
Network Connectivity ◽  
Primary Progressive Aphasia ◽  
Cognitive Networks ◽  
Default Mode ◽  
Progressive Aphasia ◽  
Primary Progressive ◽  
Semantic Variant

AbstractAs their illness progresses, patients with the semantic variant of Primary Progressive Aphasia (svPPA) frequently exhibit peculiar behaviors indicative of altered visual attention or an increased interest in artistic endeavors. In the present study, we examined changes within and between large-scale functional brain networks that may explain this altered visual behavior. We first examined the connectivity of the visual association network, the dorsal attention network, and the default mode network in healthy young adults (n=89) to understand the typical architecture of these networks in the healthy brain. We then compared the large-scale functional connectivity of these networks in a group of svPPA patients (n=12) to a group of age-matched cognitively normal controls (n=30). Our results showed that the between-network connectivity of the dorsal attention and visual association networks was elevated in svPPA patients relative to controls. We further showed that this heightened between-network connectivity was associated with a decrease in the within-network connectivity of the default mode network, possibly due to progressive degeneration of the anterior temporal lobes in svPPA. These results suggest that focal neurodegeneration can lead to the reorganization of large-scale cognitive networks beyond the primarily affected network(s), possibly contributing to cognitive or behavioral changes that are commonly present as part of the clinical phenotype of svPPA.

scholarly journals Predicting Empathy from Resting Brain Connectivity

2019 ◽  
Author(s):  
Leonardo Christov-Moore ◽  
Nicco Reggente ◽  
Pamela K. Douglas ◽  
Jamie D. Feusner ◽  
Marco Iacoboni
Keyword(s):  
Sex Differences ◽  
Visual System ◽  
Brain Connectivity ◽  
Network Connectivity ◽  
Task Demands ◽  
Empathic Concern ◽  
Control Networks ◽  
Biological Sex ◽  
Network Properties ◽  
And Control

AbstractRecent studies suggest that individual differences in empathic concern may be mediated by continuous interactions between self-other resonance and cognitive control networks. To test this hypothesis, we used machine learning to examine whether resting fMRI connectivity (i.e. the degree of synchronous BOLD activity across multiple cortical areas in the absence of task demands) of resonance and control networks could predict trait empathy (n=58). Indeed, resonance and control networks’ interconnectivity predicted empathic concern. Empathic concern was also predicted by connectivity within the somatomotor network. In light of numerous reported sex differences in empathy, we controlled for biological sex and also studied separately what aspect of these features could predict participants’ sex. Sex was best predicted by the interconnectivity of the visual system with the resonance, somatomotor, and cingulo-opercular network, as well as the somatomotor-control network connectivity. These findings confirm that variation in empathic responses to others reflects characteristic network properties detectable regardless of task demands. Furthermore, network properties of the visual system may be a locus of sex differences previously unaccounted for in empathy research. Finally, these findings suggest that it may be possible to assess empathic predispositions in individuals without needing to perform conventional empathy assessments.

scholarly journals Contributions of sex, depression, and cognition on brain connectivity dynamics in Parkinson’s disease

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Maria Diez-Cirarda ◽  
Iñigo Gabilondo ◽  
Naroa Ibarretxe-Bilbao ◽  
Juan Carlos Gómez-Esteban ◽  
Jinhee Kim ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Sex Differences ◽  
Brain Connectivity ◽  
Network Connectivity ◽  
Motor Symptoms ◽  
Clinical Markers ◽  
Neurodegenerative Process ◽  
Temporal Properties ◽  
Dynamic Connectivity

AbstractAlterations in time-varying functional connectivity (FC) have been found in Parkinson’s disease (PD) patients. To date, very little is known about the influence of sex on brain FC in PD patients and how this could be related to disease severity. The first objective was to evaluate the influence of sex on dynamic FC characteristics in PD patients and healthy controls (HC), while the second aim was to investigate the temporal patterns of dynamic connectivity related to PD motor and non-motor symptoms. Ninety-nine PD patients and sixty-two HC underwent a neuropsychological and clinical assessment. Rs-fMRI and T1-weighted MRI were also acquired. Dynamic FC analyses were performed in the GIFT toolbox. Dynamic FC analyses identified two States: State I, characterized by within-network positive coupling; and State II that showed between-network connectivity, mostly involving somatomotor and visual networks. Sex differences were found in dynamic indexes in HC but these differences were not observed in PD. Hierarchical clustering analysis identified three phenotypically distinct PD subgroups: (1) Subgroup A was characterized by mild motor symptoms; (2) Subgroup B was characterized by depressive and motor symptoms; (3) Subgroup C was characterized by cognitive and motor symptoms. Results revealed that changes in the temporal properties of connectivity were related to the motor/non-motor outcomes of PD severity. Findings suggest that while in HC sex differences may play a certain role in dynamic connectivity patterns, in PD patients, these effects may be overcome by the neurodegenerative process. Changes in the temporal properties of connectivity in PD were mainly related to the clinical markers of PD severity.

scholarly journals From Default Mode Network to the Basal Configuration: Sex Differences in the Resting-State Brain Connectivity as a Function of Age and Their Clinical Correlates

2018 ◽  
Vol 9 ◽  
Author(s):  
Sean D. Conrin ◽  
Liang Zhan ◽  
Zachery D. Morrissey ◽  
Mengqi Xing ◽  
Angus Forbes ◽  
...  
Keyword(s):  
Sex Differences ◽  
Default Mode Network ◽  
Resting State ◽  
Brain Connectivity ◽  
Default Mode ◽  
Clinical Correlates

scholarly journals Oscillatory default mode network coupling in concussion

2017 ◽  
Author(s):  
B.T Dunkley ◽  
K. Urban ◽  
L. Da Costa ◽  
S. Wong ◽  
E.W. Pang ◽  
...  
Keyword(s):  
Large Scale ◽  
Critical Role ◽  
Network Connectivity ◽  
Permutation Testing ◽  
Default Mode ◽  
Spectrum Density ◽  
Intrinsic Connectivity Networks ◽  
Time Courses ◽  
Band Limited ◽  
The Impact

AbstractBackgroundConcussion is a common form of mild traumatic brain injury (mTBI). Despite the descriptor ‘mild’, a single injury can leave long-lasting and sustained alterations to brain function, including changes to localised activity and large-scale interregional communication. Cognitive complaints are thought to arise from such functional deficits. We investigated the impact of injury on neurophysiological and functionally-specialised resting networks, known as intrinsic connectivity networks (ICNs), using MEG.MethodsWe assessed neurophysiological connectivity in 40 males, 20 with concussion, 20 without, using MEG. Regions-of-interest that comprise nodes of ICNs were defined, and their time courses derived using a beamformer approach. Pairwise fluctuations and covariations in band-limited amplitude envelopes were computed reflecting measures of functional connectivity. Intra-network connectivity was compared between groups using permutation testing, and correlated with symptoms.ResultsWe observed increased resting spectral connectivity in the default mode and motor networks in our concussion group when compared with controls, across alpha through gamma ranges. Moreover, these differences were not explained by power spectrum density (absolute changes in the spectral profiles within the ICNs). Furthermore, this increased coupling was significantly associated with symptoms in the DMN and MOT networks – but once accounting for comorbid symptoms (including, depression, anxiety, and ADHD) only the DMN continued to be associated with symptoms.ConclusionThe DMN network plays a critical role in shifting between cognitive tasks. These data suggest even a single concussion can perturb the intrinsic coupling of functionally-specialised networks in the brain and may explain persistent and wide-ranging symptomatology.

scholarly journals Multivariate associative patterns between the gut microbiota and large-scale brain network connectivity

2020 ◽  
Author(s):  
N. Kohn ◽  
J. Szopinska-Tokov ◽  
A. Llera ◽  
C. Beckmann ◽  
A. Arias Vasquez ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Default Mode Network ◽  
Large Scale ◽  
Network Connectivity ◽  
Brain Network ◽  
Imaging Data ◽  
Microbial Composition ◽  
Attention Networks ◽  
Default Mode ◽  
Brain Network Connectivity

AbstractResearch on the gut-brain axis has accelerated substantially over the course of the last years. Many reviews have outlined the important implications of understanding the relation of the gut microbiota with human brain function and behavior. One substantial drawback in integrating gut microbiome and brain data is the lack of integrative multivariate approaches that enable capturing variance in both modalities simultaneously. To address this issue, we applied a linked independent component analysis (LICA) to microbiota and brain connectivity data.We analyzed data from 58 healthy females (mean age = 21.5 years). Magnetic Resonance Imaging data were acquired using resting state functional imaging data. The assessment of gut microbial composition from feces was based on sequencing of the V4 16S rRNA gene region. We used the LICA model to simultaneously factorize the subjects’ large-scale brain networks and microbiome relative abundance data into 10 independent components of spatial and abundance variation.LICA decomposition resulted in four components with non-marginal contribution of the microbiota data. The default mode network featured strongly in three components, whereas the two-lateralized fronto-parietal attention networks contributed to one component. The executive-control (with the default mode) network was associated to another component. We found the abundance of Prevotella genus was associated to the strength of expression of all networks, whereas Bifidobacterium was associated with the default mode and frontoparietal-attention networks.We provide the first exploratory evidence for multivariate associative patterns between the gut microbiota and brain network connectivity in healthy humans, taking into account the complexity of both systems.

scholarly journals To Cheat or not to Cheat? Sex Differences and Academic Performance as Factors of Cheating Behavior

2019 ◽  
Vol 14 (1) ◽  
pp. 1
Author(s):  
Ibnu Hadjar
Keyword(s):  
Higher Education ◽  
Logistic Regression ◽  
Sex Differences ◽  
Academic Performance ◽  
The Other ◽  
Male Students ◽  
Questionnaire Data ◽  
Stimulant Effect ◽  
Cheating Behavior ◽  
Study Programs

Cheating behavior at higher education is a global phenomenon since it is found at any university in any country. This study is to examine whether sex differences and academic performance reflect the different likelihood of doing cheating among students. Using a questionnaire, data were collected from 436 students selected from different semesters and study programs in all faculties at a State Islamic University. Data were analyzed by using logistic regression, both separately and simultaneously. The results of data analysis revealed that male students tend to be more likely to do cheating categories than that of their female counterparts. It also found that academic performance affects negatively the likelihood of students to cheat in three categories of cheating behavior, but not in the other three. There is no stimulant effect of sex and academic performance on the likelihood of all categories of cheating behaviors. In other words, the effect of sex differences is not depended on academic performance and vice versa.

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