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

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.

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

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.

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

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.

scholarly journals Sex Classification by Resting State Brain Connectivity

2019 ◽  
Vol 30 (2) ◽  
pp. 824-835 ◽  
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.

scholarly journals Characterizing Complex Networks Using Entropy-Degree Diagrams: Unveiling Changes in Functional Brain Connectivity Induced by Ayahuasca

Entropy ◽  
2019 ◽  
Vol 21 (2) ◽  
pp. 128 ◽  
Author(s):  
Aline Viol ◽  
Fernanda Palhano-Fontes ◽  
Heloisa Onias ◽  
Draulio de Araujo ◽  
Philipp Hövel ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Human Brain ◽  
Resting State ◽  
Structural Information ◽  
Brain Connectivity ◽  
Functional Brain ◽  
States Of Consciousness ◽  
Functional Brain Networks ◽  
Empirical Networks ◽  
Emergent Behaviors

With the aim of further advancing the understanding of the human brain’s functional connectivity, we propose a network metric which we term the geodesic entropy. This metric quantifies the Shannon entropy of the distance distribution to a specific node from all other nodes. It allows to characterize the influence exerted on a specific node considering statistics of the overall network structure. The measurement and characterization of this structural information has the potential to greatly improve our understanding of sustained activity and other emergent behaviors in networks. We apply this method to study how the psychedelic infusion Ayahuasca affects the functional connectivity of the human brain in resting state. We show that the geodesic entropy is able to differentiate functional networks of the human brain associated with two different states of consciousness in the awaking resting state: (i) the ordinary state and (ii) a state altered by ingestion of the Ayahuasca. The functional brain networks from subjects in the altered state have, on average, a larger geodesic entropy compared to the ordinary state. Finally, we discuss why the geodesic entropy may bring even further valuable insights into the study of the human brain and other empirical networks.

scholarly journals Brain Connectivity Tracks Effects of Chemotherapy Separately from Behavioral Measures

2018 ◽  
Author(s):  
Omid Kardan ◽  
Mary K. Askren ◽  
Misook Jung ◽  
Scott Peltier ◽  
Bratislav Misic ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Cognitive Performance ◽  
Resting State ◽  
Brain Connectivity ◽  
Brain Regions ◽  
Self Report ◽  
Breast Cancer Patients ◽  
Resting State Functional Connectivity ◽  
Behavioral Measures ◽  
Cognitive Health

AbstractSeveral studies in cancer research have suggested that cognitive dysfunction following chemotherapy, referred to in lay terms as “chemobrain”, is a serious problem. At present, the changes in integrative brain function that underlie such dysfunction remains poorly understood. Recent developments in neuroimaging suggest that patterns of functional connectivity can provide a broadly applicable neuromarker of cognitive performance and other psychometric measures. The current study used multivariate analysis methods to identify patterns of disruption in resting state functional connectivity of the brain due to chemotherapy and the degree to which the disruptions can be linked to behavioral measures of distress and cognitive performance. Sixty two women (22 healthy control, 18 patients treated with adjuvant chemotherapy, and 22 treated without chemotherapy) were evaluated with neurocognitive measures followed by self-report questionnaires and open eyes resting-state fMRI scanning at three time points: diagnosis (M0, pre-adjuvant treatment), at least 1 month (M1), and 7 months (M7) after treatment. The results indicated deficits in cognitive health of breast cancer patients immediately after chemotherapy that improved over time. This psychological trajectory was paralleled by a disruption and later recovery of resting-state functional connectivity, mostly in the parietal and frontal brain regions. The functional connectivity alteration pattern seems to be a separable treatment symptom from the decreased cognitive health. More targeted support for patients should be developed to ameliorate these multi-faceted side effects of chemotherapy treatment on neural functioning and cognitive health.

scholarly journals Association between heart rate variability and fluctuations in resting-state functional connectivity

NeuroImage ◽  
2013 ◽  
Vol 68 ◽  
pp. 93-104 ◽  
Author(s):  
Catie Chang ◽  
Coraline D. Metzger ◽  
Gary H. Glover ◽  
Jeff H. Duyn ◽  
Hans-Jochen Heinze ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Functional Connectivity ◽  
Resting State ◽  
Resting State Functional Connectivity

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

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A4-A4
Author(s):  
N Tuovinen ◽  
A Stefani ◽  
T Mitterling ◽  
A Heidbreder ◽  
B Frauscher ◽  
...  
Keyword(s):  
Restless Legs Syndrome ◽  
Resting State ◽  
Brain Connectivity ◽  
Sensory Information ◽  
Brain Regions ◽  
Healthy Controls ◽  
Functional Brain ◽  
Dopaminergic Medication ◽  
Restless Legs ◽  
The Government

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.

scholarly journals Functional Brain Connectivity Patterns Associated with Visual Hallucinations in Dementia with Lewy Bodies

2021 ◽  
pp. 1-10
Author(s):  
Stefania Pezzoli ◽  
Matteo De Marco ◽  
Giovanni Zorzi ◽  
Annachiara Cagnin ◽  
Annalena Venneri
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Dementia With Lewy Bodies ◽  
Brain Connectivity ◽  
Lewy Bodies ◽  
Resting State Fmri ◽  
Group Differences ◽  
Visual Hallucinations ◽  
Functional Brain ◽  
Functional Brain Networks

Background: The presence of recurrent, complex visual hallucinations (VH) is among the core clinical features of dementia with Lewy bodies (DLB). It has been proposed that VH arise from a disrupted organization of functional brain networks. However, studies are still limited, especially investigating the resting-state functional brain features underpinning VH in patients with dementia. Objective: The aim of the present pilot study was to investigate whether there were any alterations in functional connectivity associated with VH in DLB. Methods: Seed-based analyses and independent component analysis (ICA) of resting-state fMRI scans were carried out to explore differences in functional connectivity between DLB patients with and without VH. Results: Seed-based analyses reported decreased connectivity of the lateral geniculate nucleus, the superior parietal lobule and the putamen with the medial frontal gyrus in DLB patients with VH. Visual areas showed a pattern of both decreased and increased functional connectivity. ICA revealed between-group differences in the default mode network (DMN). Conclusion: Functional connectivity analyses suggest dysfunctional top-down and bottom-up processes and DMN-related alterations in DLB patients with VH. These impairments might foster the generation of false visual images that are misinterpreted, ultimately resulting in VH.

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