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 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 Effects of dopamine agonist treatment on resting-state network connectivity in Parkinson’s disease

2020 ◽  
Author(s):  
David M. Cole ◽  
Bahram Mohammadi ◽  
Maria Milenkova ◽  
Katja Kollewe ◽  
Christoph Schrader ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Decision Making ◽  
Parkinson's Disease ◽  
Basal Ganglia ◽  
Dopamine Agonist ◽  
Resting State ◽  
Large Scale ◽  
Network Connectivity ◽  
Resting State Network ◽  
Large Scale Networks

ABSTRACTDopamine agonist (DA) medications commonly used to treat, or ‘normalise’, motor symptoms of Parkinson’s disease (PD) may lead to cognitive-neuropsychiatric side effects, such as increased impulsivity in decision-making. Subject-dependent variation in the neural response to dopamine modulation within cortico-basal ganglia circuitry is thought to play a key role in these latter, non-motor DA effects. This neuroimaging study combined resting-state functional magnetic resonance imaging (fMRI) with DA modification in patients with idiopathic PD, investigating whether brain ‘resting-state network’ (RSN) functional connectivity metrics identify disease-relevant effects of dopamine on systems-level neural processing. By comparing patients both ‘On’ and ‘Off’ their DA medications with age-matched, un-medicated healthy control subjects (HCs), we identified multiple non-normalising DA effects on frontal and basal ganglia RSN cortico-subcortical connectivity patterns in PD. Only a single isolated, potentially ‘normalising’, DA effect on RSN connectivity in sensori-motor systems was observed, within cerebro-cerebellar neurocircuitry. Impulsivity in reward-based decision-making was positively correlated with ventral striatal connectivity within basal ganglia circuitry in HCs, but not in PD patients. Overall, we provide brain systems-level evidence for anomalous DA effects in PD on large-scale networks supporting cognition and motivated behaviour. Moreover, findings suggest that dysfunctional striatal and basal ganglia signalling patterns in PD are compensated for by increased recruitment of other cortico-subcortical and cerebro-cerebellar systems.

scholarly journals Brain Connectivity Dynamics in Untreated Transmen and Cisgender Individuals

2021 ◽  
Author(s):  
Carme Uribe ◽  
Carme Junque ◽  
Esther Gómez-Gil ◽  
María Díez-Cirarda ◽  
Antonio Guillamon
Keyword(s):  
Large Scale ◽  
Brain Connectivity ◽  
Positive Association ◽  
Brain Network ◽  
Functional Explanation ◽  
Salience Network ◽  
Temporal Perspective ◽  
Attention Regulation ◽  
Sensorimotor Network ◽  
Control Networks

Abstract Large-scale brain network interactions have been described between trans- and cis-gender identities. However, a temporal perspective of the brain spontaneous fluctuations is missing. We investigated the functional connectivity dynamics in transmen with gender incongruence and its relationship with interoceptive awareness. We describe four states in native and meta-state spaces: i) one state highly prevalent with sparse overall connections; ii) a second with strong couplings mainly involving components of the salience, default and executive control networks. Two states with global sparse connectivity but positive couplings iii) within the sensorimotor network, and iv) between salience network regions. Transmen had more dynamical fluidity than cismen, while cismen presented less meta-state fluidity and range dynamism than transmen and ciswomen. A positive association between attention regulation and fluidity, and meta-state range dynamism was found in transmen. There exist gender differences in the temporal brain dynamism, characterized by distinct interrelations of the salience network as catalyst interacting with other networks. We provide a functional explanation to the neurodevelopmental hypothesis proposing different brain phenotypes in the construction of the gendered-self.

scholarly journals Attention Networks and the Intrinsic Network Structure of the Human Brain

2021 ◽  
Author(s):  
Sebastian Markett ◽  
David Nothdurfter ◽  
Antonia Focsa ◽  
Martin Reuter ◽  
Philippe Jawinski
Keyword(s):  
Network Structure ◽  
Network Theory ◽  
Large Scale ◽  
Brain Connectivity ◽  
Resting State Fmri ◽  
Relevant Information ◽  
Attention Network ◽  
Attention Networks ◽  
Large Scale Networks ◽  
The Brain

Attention network theory states that attention is not a unified construct but consists of three independent systems that are supported by separable distributed networks: an alerting network to deploy attentional resources in anticipation of upcoming events, an orienting network to direct attention to a cued location, and a control network to select relevant information at the expense of concurrently available information. Ample behavioral and neuroimaging evidence supports the dissociation of the three attention domains. The strong assumption that each attentional system is realized through a separable network, however, raises the question how these networks relate to the intrinsic network structure of the brain. Our understanding of brain networks has advanced majorly in the past years due to the increasing focus on brain connectivity. It is well established that the brain is intrinsically organized into several large-scale networks whose modular structure persists across task states. Existing proposals on how the presumed attention networks relate to intrinsic networks rely mostly on anecdotal and partly contradictory arguments. We addressed this issue by mapping different attention networks with highest spatial precision at the level of cifti-grayordinates. Resulting group maps were compared to the group-level topology of 23 intrinsic networks which we reconstructed from the same participants' resting state fMRI data. We found that all attention domains recruited multiple and partly overlapping intrinsic networks and converged in the dorsal fronto-parietal and midcingulo-insular network. While we observed a preference of each attentional domain for its own set of intrinsic networks, implicated networks did not match well to those proposed in the literature. Our results indicate a necessary refinement of the attention network theory.

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 Identifying and quantifying potential super-spreaders in social networks

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Dayong Zhang ◽  
Yang Wang ◽  
Zhaoxin Zhang
Keyword(s):  
Social Networks ◽  
Information Flow ◽  
Time Complexity ◽  
Large Scale ◽  
Network Connectivity ◽  
Sir Model ◽  
The Other ◽  
Nearest Neighbours ◽  
Large Scale Networks ◽  
Accuracy And Stability

Abstract Quantifying the nodal spreading abilities and identifying the potential influential spreaders has been one of the most engaging topics recently, which is essential and beneficial to facilitate information flow and ensure the stabilization operations of social networks. However, most of the existing algorithms just consider a fundamental quantification through combining a certain attribute of the nodes to measure the nodes’ importance. Moreover, reaching a balance between the accuracy and the simplicity of these algorithms is difficult. In order to accurately identify the potential super-spreaders, the CumulativeRank algorithm is proposed in the present study. This algorithm combines the local and global performances of nodes for measuring the nodal spreading abilities. In local performances, the proposed algorithm considers both the direct influence from the node’s neighbourhoods and the indirect influence from the nearest and the next nearest neighbours. On the other hand, in the global performances, the concept of the tenacity is introduced to assess the node’s prominent position in maintaining the network connectivity. Extensive experiments carried out with the Susceptible-Infected-Recovered (SIR) model on real-world social networks demonstrate the accuracy and stability of the proposed algorithm. Furthermore, the comparison of the proposed algorithm with the existing well-known algorithms shows that the proposed algorithm has lower time complexity and can be applicable to large-scale networks.

scholarly journals Connectomic Alterations Linked to Transdiagnostic Risk for Psychopathology at the Transition to Adolescence

2020 ◽  
Author(s):  
Chandra Sripada ◽  
Mike Angstadt ◽  
Saige Rutherford ◽  
Aman Taxali ◽  
Tristan Greathouse ◽  
...  
Keyword(s):  
Default Mode Network ◽  
Cross Validation ◽  
The United States ◽  
Basis Set ◽  
General Factor ◽  
Default Mode ◽  
Control Networks ◽  
Functional Connections ◽  
Transition To Adolescence ◽  
P Factor

AbstractBACKGROUNDConvergent research identifies a general factor (“P factor”) that confers transdiagnostic risk for psychopathology. However, brain functional connectivity patterns that underpin the P factor remain poorly understood, especially at the transition to adolescence when many serious mental disorders have their onset.OBJECTIVEIdentify a distributed connectome-wide neurosignature of the P factor and assess the generalizability of this neurosignature in held out samples.DESIGN, SETTING, AND PARTICIPANTSThis study used data from the full baseline wave of the Adolescent Brain and Cognitive Development (ABCD) national consortium study, a prospective, population-based study of 11,875 9- and 10-year olds. Data for this study were collected from September 1, 2016 to November 15, 2018 at 21 research sites across the United States.MAIN OUTCOMES AND MEASURESWe produced whole brain functional connectomes for 5,880 youth with high quality resting state scans. We then constructed a low rank basis set of 250 components that captures interindividual connectomic differences. Multi-level regression modeling was used to link these components to the P factor, and leave-one-site-out cross-validation was used to assess generalizability of P factor neurosignatures to held out subjects across 19 ABCD sites.RESULTSThe set of 250 connectomic components was highly statistically significantly related to the P factor, over and above nuisance covariates alone (ANOVA nested model comparison, incremental R-squared 6.05%, χ2(250) =412.1, p<4.6×10−10). In addition, two individual connectomic components were statistically significantly related to the P factor after Bonferroni correction for multiple comparisons (t(5511)= 4.8, p<1.4×10−06; t(5121)= 3.9, p<9.7×10−05). Functional connections linking control networks and default mode network were prominent in the P factor neurosignature. In leave-one-site-out cross-validation, the P factor neurosignature generalized to held out subjects (average correlation between actual and predicted P factor scores across 19 held out sites=0.13; pPERMUTATION<0.0001). Additionally, results remained significant after a number of robustness checks.CONCLUSIONS AND RELEVANCEThe general factor of psychopathology is associated with connectomic alterations involving control networks and default mode network. Brain imaging combined with network neuroscience can identify distributed and generalizable signatures of transdiagnostic risk for psychopathology during emerging adolescence.

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 Targeted cortical reorganization using optogenetics in non-human primates

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Azadeh Yazdan-Shahmorad ◽  
Daniel B Silversmith ◽  
Viktor Kharazia ◽  
Philip N Sabes
Keyword(s):  
Large Scale ◽  
Network Connectivity ◽  
Cortical Reorganization ◽  
Strongly Correlated ◽  
Hebbian Plasticity ◽  
Two Measures ◽  
Evoked Activity ◽  
Large Scale Networks ◽  
Induced Changes ◽  
Stimulation Of

Brain stimulation modulates the excitability of neural circuits and drives neuroplasticity. While the local effects of stimulation have been an active area of investigation, the effects on large-scale networks remain largely unexplored. We studied stimulation-induced changes in network dynamics in two macaques. A large-scale optogenetic interface enabled simultaneous stimulation of excitatory neurons and electrocorticographic recording across primary somatosensory (S1) and motor (M1) cortex (Yazdan-Shahmorad et al., 2016). We tracked two measures of network connectivity, the network response to focal stimulation and the baseline coherence between pairs of electrodes; these were strongly correlated before stimulation. Within minutes, stimulation in S1 or M1 significantly strengthened the gross functional connectivity between these areas. At a finer scale, stimulation led to heterogeneous connectivity changes across the network. These changes reflected the correlations introduced by stimulation-evoked activity, consistent with Hebbian plasticity models. This work extends Hebbian plasticity models to large-scale circuits, with significant implications for stimulation-based neurorehabilitation.

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