0010 Functional Brain Connectivity Alterations in Restless Legs Syndrome are Modulated by Dopaminergic Medication

Abstract Introduction Functional brain connectivity studies revealed alterations within thalamic, salience, and default mode networks in patients with restless legs syndrome. The objective of this study was to characterize functional connectivity and network topology in a large cohort of patients with restless legs syndrome compared to healthy controls, and to investigate the modulatory effect of dopaminergic treatment upon connectivity. Methods 82 patients with restless legs syndrome (untreated, n=30; on dopaminergic medication, n=42; on alpha-2-delta ligands as mono- or polytherapy combined with dopaminergic medication, n=10) and 82 individually age and gender matched healthy controls were studied with resting state functional MRI. Connectivity of twelve resting-state networks was compared with independent component analysis, and among 410 brain regions with graph theoretical modeling. Results Patients with restless legs syndrome showed significantly higher connectivity within salience (P=0.029), executive (P=0.001), somatomotor (P=0.050), and cerebellar (P=0.041) networks, as well as significantly (P<0.05) lower cerebello-frontal communication compared to healthy controls. Untreated patients had significantly (P<0.05) lower cerebello-parietal communication compared to healthy controls and connectivity between the thalamus and frontal regions were significantly increased in patients on dopaminergic medication compared to untreated patients and healthy controls (P<0.05). Conclusion Networks with higher intra-network connectivity (i.e. salience, executive, somatomotor, cerebellar) and lower between regions connectivity (i.e. cerebello-frontal, cerebello-parietal) in restless legs syndrome correspond to regions associated with attention, response inhibitory control, and processing of sensory information. Dopaminergic medication normalizes the altered cerebello-parietal communication and increases thalamic connectivity to the prefrontal cortex suggesting that these regions are associated with the emergence of symptoms in restless legs syndrome. Support The study was funded by a Grant from Translational Research Fund of the government of Tyrol, Austria, and in-kind resources of the Medical University of Innsbruck.

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Sex Classification by Resting State Brain Connectivity

Cerebral Cortex ◽

10.1093/cercor/bhz129 ◽

2019 ◽

Vol 30 (2) ◽

pp. 824-835 ◽

Cited By ~ 12

Author(s):

Susanne Weis ◽

Kaustubh R Patil ◽

Felix Hoffstaedter ◽

Alessandra Nostro ◽

B T Thomas Yeo ◽

...

Keyword(s):

Resting State ◽

Brain Connectivity ◽

Brain Regions ◽

Brain Organization ◽

Functional Brain ◽

Clear Cut ◽

Human Connectome Project ◽

Machine Learning Approach ◽

Imaging Research ◽

Functional Brain Organization

Abstract A large amount of brain imaging research has focused on group studies delineating differences between males and females with respect to both cognitive performance as well as structural and functional brain organization. To supplement existing findings, the present study employed a machine learning approach to assess how accurately participants’ sex can be classified based on spatially specific resting state (RS) brain connectivity, using 2 samples from the Human Connectome Project (n1 = 434, n2 = 310) and 1 fully independent sample from the 1000BRAINS study (n = 941). The classifier, which was trained on 1 sample and tested on the other 2, was able to reliably classify sex, both within sample and across independent samples, differing both with respect to imaging parameters and sample characteristics. Brain regions displaying highest sex classification accuracies were mainly located along the cingulate cortex, medial and lateral frontal cortex, temporoparietal regions, insula, and precuneus. These areas were stable across samples and match well with previously described sex differences in functional brain organization. While our data show a clear link between sex and regionally specific brain connectivity, they do not support a clear-cut dimorphism in functional brain organization that is driven by sex alone.

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The Influence of Heart Rate Variability Biofeedback on Cardiac Regulation and Functional Brain Connectivity

Frontiers in Neuroscience ◽

10.3389/fnins.2021.691988 ◽

2021 ◽

Vol 15 ◽

Author(s):

Andy Schumann ◽

Feliberto de la Cruz ◽

Stefanie Köhler ◽

Lisa Brotte ◽

Karl-Jürgen Bär

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Functional Connectivity ◽

Resting State ◽

Brain Connectivity ◽

Cingulate Cortex ◽

Brain Regions ◽

Control Group ◽

Functional Brain ◽

Middle Cingulate Cortex

BackgroundHeart rate variability (HRV) biofeedback has a beneficial impact on perceived stress and emotion regulation. However, its impact on brain function is still unclear. In this study, we aimed to investigate the effect of an 8-week HRV-biofeedback intervention on functional brain connectivity in healthy subjects.MethodsHRV biofeedback was carried out in five sessions per week, including four at home and one in our lab. A control group played jump‘n’run games instead of the training. Functional magnetic resonance imaging was conducted before and after the intervention in both groups. To compute resting state functional connectivity (RSFC), we defined regions of interest in the ventral medial prefrontal cortex (VMPFC) and a total of 260 independent anatomical regions for network-based analysis. Changes of RSFC of the VMPFC to other brain regions were compared between groups. Temporal changes of HRV during the resting state recording were correlated to dynamic functional connectivity of the VMPFC.ResultsFirst, we corroborated the role of the VMPFC in cardiac autonomic regulation. We found that temporal changes of HRV were correlated to dynamic changes of prefrontal connectivity, especially to the middle cingulate cortex, the left insula, supplementary motor area, dorsal and ventral lateral prefrontal regions. The biofeedback group showed a drop in heart rate by 5.2 beats/min and an increased SDNN as a measure of HRV by 8.6 ms (18%) after the intervention. Functional connectivity of the VMPFC increased mainly to the insula, the amygdala, the middle cingulate cortex, and lateral prefrontal regions after biofeedback intervention when compared to changes in the control group. Network-based statistic showed that biofeedback had an influence on a broad functional network of brain regions.ConclusionOur results show that increased heart rate variability induced by HRV-biofeedback is accompanied by changes in functional brain connectivity during resting state.

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The relationship between spatial configuration and functional connectivity of brain regions revisited

10.1101/520502 ◽

2019 ◽

Author(s):

Janine D. Bijsterbosch ◽

Christian F. Beckmann ◽

Mark W. Woolrich ◽

Stephen M. Smith ◽

Samuel J. Harrison

Keyword(s):

Functional Connectivity ◽

Network Structure ◽

Resting State ◽

Spatial Configuration ◽

Brain Connectivity ◽

Brain Regions ◽

Spatial Effects ◽

Functional Brain ◽

Dual Regression ◽

The Relationship

AbstractIn our previous paper (Bijsterbosch et al., 2018), we showed that network-based modelling of brain connectivity interacts strongly with the shape and exact location of brain regions, such that cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Here we show that these spatial effects on connectivity estimates actually occur as a result of spatial overlap between brain networks. This is shown to systematically bias connectivity estimates obtained from group spatial ICA followed by dual regression. We introduce an extended method that addresses the bias and achieves more accurate connectivity estimates.Impact statementWe show that functional connectivity network matrices as estimated from resting state functional MRI are biased by spatially overlapping network structure.

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Sex classification by resting state brain connectivity

10.1101/627711 ◽

2019 ◽

Cited By ~ 4

Author(s):

Susanne Weis ◽

Kaustubh Patil ◽

Felix Hoffstaedter ◽

Alessandra Nostro ◽

B.T. Thomas Yeo ◽

...

Keyword(s):

Resting State ◽

Brain Connectivity ◽

Brain Regions ◽

Brain Organization ◽

Functional Brain ◽

Clear Cut ◽

Human Connectome Project ◽

Two Samples ◽

Imaging Research ◽

Functional Brain Organization

1AbstractA large amount of brain imaging research has focused on group studies delineating differences between males and females with respect to both cognitive performance as well as structural and functional brain organization. To supplement existing findings, the present study employed a machine learning approach to assess how accurately participants’ sex can be classified based on spatially specific resting state (RS) brain-connectivity, using two samples from the Human Connectome Project (n1 = 434, n2 = 310) and one fully independent sample from the 1000BRAINS study (n=941). The classifier, which was trained on one sample and tested on the other two, was able to reliably classify sex, both within sample and across independent samples, differing both with respect to imaging parameters and sample characteristics. Brain regions displaying highest sex classification accuracies were mainly located along the cingulate cortex, medial and lateral frontal cortex, temporo-parietal regions, insula and precuneus. These areas were stable across samples and match well with previously described sex differences in functional brain organization. While our data show a clear link between sex and regionally specific brain connectivity, they do not support a clear-cut dimorphism in functional brain organization that is driven by sex alone.

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The influence of heart rate variability biofeedback on cardiac regulation and functional brain connectivity

10.1101/2020.08.10.243998 ◽

2020 ◽

Author(s):

Andy Schumann ◽

Feliberto de la Cruz ◽

Stefanie Köhler ◽

Lisa Brotte ◽

Karl-Jürgen Bär

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Prefrontal Cortex ◽

Functional Connectivity ◽

Resting State ◽

Brain Connectivity ◽

Brain Regions ◽

Anterior Insula ◽

Control Group ◽

Functional Brain

AbstractBackgroundHeart rate variability (HRV) biofeedback has a beneficial impact on perceived stress and emotion regulation. However, its impact on brain function is still unclear. In this study, we aimed to investigate the effect of an 8-week HRV-biofeedback intervention on functional brain connectivity in healthy subjects.MethodsHRV biofeedback was carried out in five sessions per week, including four at home and one in our lab. A control group played jump‘n’run games instead of the training. Functional magnetic resonance imaging was conducted before and after the intervention in both groups. To compute resting state functional connectivity (RSFC), we defined regions of interest in the ventral medial prefrontal cortex (VMPFC) and a total of 260 independent anatomical regions for network-based analysis. Changes of RSFC of the VMPFC to other brain regions were compared between groups. Temporal changes of HRV during the resting state recording were correlated to dynamic functional connectivity of the VMPFC.ResultsFirst, we corroborated the role of the VMPFC in cardiac autonomic regulation. We found that temporal changes of HRV were correlated to dynamic changes of prefrontal connectivity, especially to the middle cingulate cortex, left anterior insula, right amygdala, supplementary motor area, dorsal and ventral lateral prefrontal regions. The biofeedback group showed a drop in heart rate by 5.5 beats/min and an increased RMSSD as a measure of HRV by 10.1ms (33%) after the intervention. Functional connectivity of the VMPFC increased mainly to the right anterior insula, the dorsal anterior cingulate cortex and the dorsolateral prefrontal cortex after biofeedback intervention when compared to changes in the control group. Network-based statistic showed that biofeedback had an influence on a broad functional network of brain regions.ConclusionOur results show that increased vagal modulation induced by HRV-biofeedback is accompanied by changes in functional brain connectivity during resting state.

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Dissociating tinnitus patients from healthy controls using resting-state cyclicity analysis and clustering

Network Neuroscience ◽

10.1162/netn_a_00053 ◽

2019 ◽

Vol 3 (1) ◽

pp. 67-89 ◽

Cited By ~ 7

Author(s):

Benjamin J. Zimmerman ◽

Ivan Abraham ◽

Sara A. Schmidt ◽

Yuliy Baryshnikov ◽

Fatima T. Husain

Keyword(s):

Resting State ◽

Classification Accuracy ◽

Brain Connectivity ◽

Brain Regions ◽

Fmri Data ◽

Healthy Controls ◽

Functional Magnetic Resonance ◽

Resonance Imaging ◽

Physiological Models ◽

Analysis Stability

Chronic tinnitus is a common and sometimes debilitating condition that lacks scientific consensus on physiological models of how the condition arises as well as any known cure. In this study, we applied a novel cyclicity analysis, which studies patterns of leader-follower relationships between two signals, to resting-state functional magnetic resonance imaging (rs-fMRI) data of brain regions acquired from subjects with and without tinnitus. Using the output from the cyclicity analysis, we were able to differentiate between these two groups with 58–67% accuracy by using a partial least squares discriminant analysis. Stability testing yielded a 70% classification accuracy for identifying individual subjects’ data across sessions 1 week apart. Additional analysis revealed that the pairs of brain regions that contributed most to the dissociation between tinnitus and controls were those connected to the amygdala. In the controls, there were consistent temporal patterns across frontal, parietal, and limbic regions and amygdalar activity, whereas in tinnitus subjects, this pattern was much more variable. Our findings demonstrate a proof-of-principle for the use of cyclicity analysis of rs-fMRI data to better understand functional brain connectivity and to use it as a tool for the differentiation of patients and controls who may differ on specific traits.

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Long-term treatment of patients suffering from Restless Legs syndrome does not improve satisfaction with life and sleep compared to healthy controls

Pharmacopsychiatry ◽

10.1055/s-0029-1240090 ◽

2009 ◽

Vol 42 (05) ◽

Author(s):

S Brand ◽

M Hatzinger ◽

J Beck ◽

E Holsboer-Trachsler

Keyword(s):

Restless Legs Syndrome ◽

Satisfaction With Life ◽

Term Treatment ◽

Healthy Controls ◽

Restless Legs ◽

Long Term Treatment

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Plasma thiol/disulphide homeostasis changes in patients with restless legs syndrome

Clinical Chemistry and Laboratory Medicine (CCLM) ◽

10.1515/cclm-2020-1659 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Ertan Kucuksayan ◽

Serkan Ozben ◽

Selma Topaloglu Tuac ◽

Mesrure Koseoglu ◽

Ozcan Erel ◽

...

Keyword(s):

Oxidative Stress ◽

Restless Legs Syndrome ◽

Rating Scales ◽

Spectrophotometric Analysis ◽

Healthy Controls ◽

Restless Legs ◽

Severity Rating ◽

Total Thiol ◽

Disease Rating ◽

Positive Correlations

Abstract Objectives Restless legs syndrome (RLS) is a common neurological condition. Oxidative stress plays an important role in its pathogenesis. Thiol-disulphide homeostasis (TDH) is a new biomarker of oxidative stress. We studied plasma TDH to determine whether TDH could be used as a new biomarker for RLS and evaluated correlations between TDH and various disease severity rating scales. Methods A total of 25 RLS patients and 25 healthy controls were included into the study. TDH status was determined using an automated spectrophotometric analysis method and correlations were analyzed between the TDH status and various disease rating scales in the RLS patients. Results Plasma total (401 ± 27 μmol/L) and native thiol (354 ± 30 μmol/L) levels were significantly lower, but disulphide level (24 ± 6 μmol/L) was significantly (<0.0001) higher in the RLS patients compared to the controls (455 ± 36, 424 ± 37, 15 ± 5 μmol/L, respectively). The disulphide/native thiol and disulphide/total thiol ratios increased, in contrast, native thiol/total thiol ratio decreased significantly in the RLS patients compared to the healthy controls (<0.0001). The disulphide levels correlated positively with age and various rating scores of the RLS patients. International Restless Legs Syndrome Study Group (IRLSSG) rating score and age correlated negatively with the total and native thiol levels. Conclusions Our findings indicate increased oxidative stress in the RLS patients reflected by decreased native and total thiol, and increased disulphide levels and positive correlations between the disulphide levels and various rating scores. We suggest dynamic TDH status to be used as a novel biomarker for the diagnosis and follow-up of the RLS patients.

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