Brain connectivity dynamics in cisgender and transmen people with gender incongruence before gender affirmative hormone treatment

AbstractLarge-scale brain network interactions have been described between trans- and cis-gender binary identities. However, a temporal perspective of the brain's 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 offer a functional explanation from the neurodevelopmental cortical hypothesis of a gendered-self.

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Brain Connectivity Dynamics in Untreated Transmen and Cisgender Individuals

10.21203/rs.3.rs-376858/v1 ◽

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.

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Salience Network Disruption in US Army Soldiers with PTSD

10.1101/496505 ◽

2018 ◽

Author(s):

Chadi Abdallah ◽

Christopher Averill ◽

Amy Ramage ◽

Lynnette Averill ◽

Selin Goktas ◽

...

Keyword(s):

Resting State ◽

Right Hemisphere ◽

Brain Connectivity ◽

Brain Network ◽

Data Driven ◽

Salience Network ◽

Symptom Provocation ◽

Us Army ◽

Data Driven Approach ◽

Army Soldiers

BACKGROUND: Better understanding of the neurobiology of posttraumatic stress disorder (PTSD) may be critical to developing novel, effective therapeutics. Here, we conducted a data-driven investigation using a well-established, graph- based topological measure of nodal strength to determine the extent of functional dysconnectivity in a cohort of active duty US Army soldiers with PTSD compared to controls. METHODS: 102 participants with (n=50) or without PTSD (n=52) completed functional magnetic resonance imaging (fMRI) at rest and during symptom provocation using subject-specific script imagery. Vertex/voxel global brain connectivity with global signal regression (GBCr), a measure of nodal strength, was calculated as the average of its functional connectivity with all other vertices/voxels in the brain gray matter. RESULTS: In contrast to during resting-state, where there were no group differences, we found a significantly higher GBCr, in PTSD participants compared to controls, in areas within the right hemisphere, including anterior insula, caudal- ventrolateral prefrontal, and rostral-ventrolateral parietal cortices. Overall, these clusters overlapped with the ventral and dorsal salience networks. Post hoc analysis showed increased GBCr in these salience clusters during symptom provocation compared to resting-state. In addition, resting-state GBCr in the salience clusters predicted GBCr during symptom provocation in PTSD participants but not in controls. CONCLUSION: In PTSD, increased connectivity within the salience network has been previously hypothesized, based primarily on seed-based connectivity findings. The current results strongly support this hypothesis using whole-brain network measure in a fully data-driven approach. It remains to be seen in future studies whether these identified salience disturbances would normalize following treatment.

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Childhood trauma history is linked to abnormal brain connectivity in major depression

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1900801116 ◽

2019 ◽

Vol 116 (17) ◽

pp. 8582-8590 ◽

Cited By ~ 29

Author(s):

Meichen Yu ◽

Kristin A. Linn ◽

Russell T. Shinohara ◽

Desmond J. Oathes ◽

Philip A. Cook ◽

...

Keyword(s):

Childhood Trauma ◽

Network Architecture ◽

Brain Connectivity ◽

Network Connectivity ◽

Brain Network ◽

Childhood Experiences ◽

Attention Network ◽

Sensorimotor Network ◽

Frontoparietal Network ◽

Subcortical Regions

Patients with major depressive disorder (MDD) present with heterogeneous symptom profiles, while neurobiological mechanisms are still largely unknown. Brain network studies consistently report disruptions of resting-state networks (RSNs) in patients with MDD, including hypoconnectivity in the frontoparietal network (FPN), hyperconnectivity in the default mode network (DMN), and increased connection between the DMN and FPN. Using a large, multisite fMRI dataset (n= 189 patients with MDD,n= 39 controls), we investigated network connectivity differences within and between RSNs in patients with MDD and healthy controls. We found that MDD could be characterized by a network model with the following abnormalities relative to controls: (i) lower within-network connectivity in three task-positive RSNs [FPN, dorsal attention network (DAN), and cingulo-opercular network (CON)], (ii) higher within-network connectivity in two intrinsic networks [DMN and salience network (SAN)], and (iii) higher within-network connectivity in two sensory networks [sensorimotor network (SMN) and visual network (VIS)]. Furthermore, we found significant alterations in connectivity between a number of these networks. Among patients with MDD, a history of childhood trauma and current symptoms quantified by clinical assessments were associated with a multivariate pattern of seven different within- and between-network connectivities involving the DAN, FPN, CON, subcortical regions, ventral attention network (VAN), auditory network (AUD), VIS, and SMN. Overall, our study showed that traumatic childhood experiences and dimensional symptoms are linked to abnormal network architecture in MDD. Our results suggest that RSN connectivity may explain underlying neurobiological mechanisms of MDD symptoms and has the potential to serve as an effective diagnostic biomarker.

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Individual Variation in Brain Network Topology Predicts Emotional Intelligence

10.1101/275768 ◽

2018 ◽

Author(s):

Ling George ◽

Lee Ivy ◽

Guimond Synthia ◽

Lutz Olivia ◽

Tandon Neeraj ◽

...

Keyword(s):

Emotional Intelligence ◽

Social Cognition ◽

Network Topology ◽

Resting State ◽

Large Scale ◽

Psychotic Disorders ◽

Brain Connectivity ◽

Distance Matrix ◽

Resting State Fmri ◽

Brain Network

AbstractBackgroundSocial cognitive ability is a significant determinant of functional outcome and deficits in social cognition are a disabling symptom of psychotic disorders. The neurobiological underpinnings of social cognition are not well understood, hampering our ability to ameliorate these deficits.ObjectiveUsing ‘resting-state’ fMRI (functional magnetic resonance imaging) and a trans-diagnostic, data-driven analytic strategy, we sought to identify the brain network basis of emotional intelligence, a key domain of social cognition.MethodsStudy participants included 60 participants with a diagnosis of schizophrenia or schizoaffective disorder and 46 healthy comparison participants. All participants underwent a resting-state fMRI scan. Emotional Intelligence was measured using the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT). A connectome-wide analysis of brain connectivity examined how each individual brain voxel’s connectivity correlated with emotional intelligence using multivariate distance matrix regression (MDMR).ResultsWe identified a region in the left superior parietal lobule (SPL) where individual network topology predicted emotional intelligence. Specifically, the association of this region with the Default Mode Network predicted higher emotional intelligence and association with the Dorsal Attention Network predicted lower emotional intelligence. This correlation was observed in both schizophrenia and healthy comparison participants.ConclusionPrevious studies have demonstrated individual variance in brain network topology but the cognitive or behavioral relevance of these differences was undetermined. We observe that the left SPL, a region of high individual variance at the cytoarchitectonic level, also demonstrates individual variance in its association with large scale brain networks and that network topology predicts emotional intelligence.

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Generative models of rich clubs in Hebbian neuronal networks and large-scale human brain networks

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2013.0531 ◽

2014 ◽

Vol 369 (1653) ◽

pp. 20130531 ◽

Cited By ~ 25

Author(s):

Petra E. Vértes ◽

Aaron Alexander-Bloch ◽

Edward T. Bullmore

Keyword(s):

Neural Networks ◽

Human Brain ◽

Large Scale ◽

Hebbian Learning ◽

Brain Connectivity ◽

Brain Networks ◽

Brain Network ◽

Generative Models ◽

Adaptive Behaviour ◽

Topological Term

Rich clubs arise when nodes that are ‘rich’ in connections also form an elite, densely connected ‘club’. In brain networks, rich clubs incur high physical connection costs but also appear to be especially valuable to brain function. However, little is known about the selection pressures that drive their formation. Here, we take two complementary approaches to this question: firstly we show, using generative modelling, that the emergence of rich clubs in large-scale human brain networks can be driven by an economic trade-off between connection costs and a second, competing topological term. Secondly we show, using simulated neural networks, that Hebbian learning rules also drive the emergence of rich clubs at the microscopic level, and that the prominence of these features increases with learning time. These results suggest that Hebbian learning may provide a neuronal mechanism for the selection of complex features such as rich clubs. The neural networks that we investigate are explicitly Hebbian, and we argue that the topological term in our model of large-scale brain connectivity may represent an analogous connection rule. This putative link between learning and rich clubs is also consistent with predictions that integrative aspects of brain network organization are especially important for adaptive behaviour.

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Aberrant striatal dopamine links topographically with cortico-thalamic dysconnectivity in schizophrenia

Brain ◽

10.1093/brain/awaa296 ◽

2020 ◽

Vol 143 (11) ◽

pp. 3495-3505 ◽

Cited By ~ 1

Author(s):

Mihai Avram ◽

Felix Brandl ◽

Franziska Knolle ◽

Jorge Cabello ◽

Claudia Leucht ◽

...

Keyword(s):

Basal Ganglia ◽

Large Scale ◽

Theoretical Models ◽

Striatal Dopamine ◽

Psychotic Symptoms ◽

Dopamine Synthesis ◽

Salience Network ◽

Thalamic Nuclei ◽

Cortical Networks ◽

Sensorimotor Network

Abstract Aberrant dopamine function in the dorsal striatum and aberrant intrinsic functional connectivity (iFC) between distinct cortical networks and thalamic nuclei are among the most consistent large-scale brain imaging findings in schizophrenia. A pathophysiological link between these two alterations is suggested by theoretical models based on striatal dopamine’s topographic modulation of cortico-thalamic connectivity within cortico-basal-ganglia-thalamic circuits. We hypothesized that aberrant striatal dopamine links topographically with aberrant cortico-thalamic iFC, i.e. aberrant associative striatum dopamine is associated with aberrant iFC between the salience network and thalamus, and aberrant sensorimotor striatum dopamine with aberrant iFC between the auditory-sensorimotor network and thalamus. Nineteen patients with schizophrenia during remission of psychotic symptoms and 19 age- and sex-comparable control subjects underwent simultaneous fluorodihydroxyphenyl-l-alanine PET (18F-DOPA-PET) and resting state functional MRI (rs-fMRI). The influx constant kicer based on 18F-DOPA-PET was used to measure striatal dopamine synthesis capacity; correlation coefficients between rs-fMRI time series of cortical networks and thalamic regions of interest were used to measure iFC. In the salience network-centred system, patients had reduced associative striatum dopamine synthesis capacity, which correlated positively with decreased salience network-mediodorsal-thalamus iFC. This correlation was present in both patients and healthy controls. In the auditory-sensorimotor network-centred system, patients had reduced sensorimotor striatum dopamine synthesis capacity, which correlated positively with increased auditory-sensorimotor network-ventrolateral-thalamus iFC. This correlation was present in patients only. Results demonstrate that reduced striatal dopamine synthesis capacity links topographically with cortico-thalamic intrinsic dysconnectivity in schizophrenia. Data suggest that aberrant striatal dopamine and cortico-thalamic dysconnectivity are pathophysiologically related within dopamine-modulated cortico-basal ganglia-thalamic circuits in schizophrenia.

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Measuring inter-individual differences in stress sensitivity during MR-guided prostate biopsy

Scientific Reports ◽

10.1038/s41598-021-82199-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Nils Kohn ◽

Jan Heidkamp ◽

Guillén Fernández ◽

Jurgen Fütterer ◽

Indira Tendolkar

Keyword(s):

Positive Affect ◽

Prostate Biopsy ◽

Large Scale ◽

Acute Stress ◽

Brain Connectivity ◽

Real Life ◽

Brain Network ◽

Stress Sensitivity ◽

Mri Guided ◽

The Impact

AbstractPeople often experience high level of distress during invasive interventions, which may exceed their coping abilities. This may be in particular evident when confronted with the suspicion of cancer. Taking the example of prostate biopsy sampling, we aimed at investigating the impact of an MRI guided prostate biopsy on the acute stress response and its mechanistic basis. We recruited 20 men with a clinical suspicion of prostate cancer. Immediately before an MRI guided biopsy procedure, we conducted fMRI in the same scanner to assess resting-state brain connectivity. Physiological and hormonal stress measures were taken during the procedure and associated with questionnaires, hair cortisol levels and brain measures to elucidate mechanistic factors for elevated stress. As expected, patients reported a stress-related change in affect. Decreased positive affect was associated with higher hair but not saliva cortisol concentration. Stronger use of maladaptive emotion regulation techniques, elevated depression scores and higher within-salience-network connectivity was associated with stronger increase in negative affect and/or decrease of positive affect during the procedure. While being limited in its generalization due to age, sample size and gender, our proof of concept study demonstrates the utility of real-life stressors and large-scale brain network measures in stress regulation research with potential impact in clinical practice.

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Aberrant posterior superior temporal sulcus functional connectivity and executive dysfunction in adolescents with internet gaming disorder

Journal of Behavioral Addictions ◽

10.1556/2006.2020.00060 ◽

2020 ◽

Vol 9 (3) ◽

pp. 589-597

Author(s):

Junghan Lee ◽

Deokjong Lee ◽

Kee Namkoong ◽

Young-Chul Jung

Keyword(s):

Functional Connectivity ◽

Default Mode Network ◽

Large Scale ◽

Internet Gaming Disorder ◽

Executive Dysfunction ◽

Brain Network ◽

Salience Network ◽

Gaming Disorder ◽

Default Mode ◽

Internet Gaming

AbstractBackground and aimsThe clinical significance of Internet gaming disorder (IGD) is spreading worldwide, but its underlying neural mechanism still remains unclear. Moreover, the prevalence of IGD seems to be the highest in adolescents whose brains are in development. This study investigated the functional connectivity between large-scale intrinsic networks including default mode network, executive control network, and salience network. We hypothesized that adolescents with IGD would demonstrate different functional connectivity patterns among large-scale intrinsic networks, implying neurodevelopmental alterations, which might be associated with executive dysfunction.MethodsThis study included 17 male adolescents with Internet gaming disorder, and 18 age-matched male adolescents as healthy controls. Functional connectivity was examined using seed-to-voxel analysis and seed-to-seed analysis, with the nodes of large-scale intrinsic networks used as region of interests. Group independent component analysis was performed to investigate spatially independent network.ResultsWe identified aberrant functional connectivity of salience network and default mode network with the left posterior superior temporal sulcus (pSTS) in adolescents with IGD. Furthermore, functional connectivity between salience network and pSTS correlated with proneness to Internet addiction and self-reported cognitive problems. Independent component analysis revealed that pSTS was involved in social brain network.Discussion and conclusionsThe results imply that aberrant functional connectivity of social brain network with default mode network and salience network was identified in IGD that may be associated with executive dysfunction. Our results suggest that inordinate social stimuli during excessive online gaming leads to altered connections among large-scale networks during neurodevelopment of adolescents.

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BRAPH: A Graph Theory Software for the Analysis of Brain Connectivity

10.1101/106625 ◽

2017 ◽

Author(s):

Mite Mijalkov ◽

Ehsan Kakaei ◽

Joana B. Pereira ◽

Eric Westman ◽

Giovanni Volpe ◽

...

Keyword(s):

Graph Theory ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Large Scale ◽

Brain Connectivity ◽

Resting State Fmri ◽

Brain Network ◽

Local Network ◽

Healthy Controls ◽

The Brain

AbstractThe brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH – BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer’s disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson’s patients with mild cognitive impairment.

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Networks Are Associated With Depression in Patients With Parkinson’s Disease: A Resting-State Imaging Study

Frontiers in Neuroscience ◽

10.3389/fnins.2020.573538 ◽

2021 ◽

Vol 14 ◽

Author(s):

Haiyan Liao ◽

Sainan Cai ◽

Qin Shen ◽

Jie Fan ◽

Tianyu Wang ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Resting State ◽

Large Scale ◽

Brain Connectivity ◽

Imaging Study ◽

Sensorimotor Network ◽

Depression Level ◽

Large Scale Networks ◽

The Right

BackgroundDisturbance of networks was recently proposed to be associated with the occurrence of depression in Parkinson’s disease (PD). However, the neurobiological mechanism of depression underlying PD remains unclear.ObjectiveThis study was conducted to investigate whether intra-network and inter-network brain connectivity is differently changed in PD patients with and without depression (PDD and PDND patients, respectively).MethodsForty-one PDD patients, 64 PDND patients, and 55 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (fMRI). The default mode network (DMN), executive control network (ECN), salience network (SN), precuneus network (PCUN), and sensorimotor network (SMN) were extracted using independent component analysis (ICA), and then the functional connectivity (FC) values within and between these networks were measured.ResultsPDD patients exhibited abnormal FC values within the DMN, ECN, SN, PCUN, and SMN. In addition, PDD patients demonstrated decreased connectivity between anterior SN (aSN) and bilateral ECN, between posterior SN (pSN) and dorsal DMN (dDMN), and between PCUN and dDMN/SMN/bilateral ECN. Connectivity within the left hippocampus of dDMN and the right medial superior frontal gyrus of aSN was a significant predictor of depression level in PD patients.ConclusionsAberrant intra- and inter-network FC is involved in several important hubs in the large-scale networks, which can be a biomarker for distinguishing PDD from PDND.

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