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

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Janine Diane Bijsterbosch ◽  
Christian F Beckmann ◽  
Mark W Woolrich ◽  
Stephen M Smith ◽  
Samuel J Harrison
Keyword(s):  
Functional Connectivity ◽  
Spatial Configuration ◽  
Brain Connectivity ◽  
Brain Regions ◽  
Spatial Effects ◽  
Functional Brain ◽  
Spatial Overlap ◽  
Exact Location ◽  
Dual Regression ◽  
The Relationship

Previously 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 (Bijsterbosch et al., 2018). 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.

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 The relationship between spatial configuration and functional connectivity of brain regions

2017 ◽  
Author(s):  
Janine D. Bijsterbosch ◽  
Mark W. Woolrich ◽  
Matthew F. Glasser ◽  
Emma C. Robinson ◽  
Christian F. Beckmann ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Spatial Configuration ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Spatial Arrangement ◽  
Brain Regions ◽  
Imaging Data ◽  
Functional Regions ◽  
Cortical Regions ◽  
The Relationship

AbstractBrain connectivity is often considered in terms of the communication between functionally distinct brain regions. Many studies have investigated the extent to which patterns of coupling strength between multiple neural populations relates to behavior. For example, studies have used "functional connectivity fingerprints" to characterise individuals' brain activity. Here, we investigate the extent to which the exact spatial arrangement of cortical regions interacts with measures of brain connectivity. We find that the shape and exact location of brain regions interact strongly with the modelling of brain connectivity, and present evidence that the spatial arrangement of functional regions is strongly predictive of non-imaging measures of behaviour and lifestyle. We believe that, in many cases, cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Therefore, a better understanding of these effects is important when interpreting the relationship between functional imaging data and cognitive traits.

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

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Janine Diane Bijsterbosch ◽  
Mark W Woolrich ◽  
Matthew F Glasser ◽  
Emma C Robinson ◽  
Christian F Beckmann ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Spatial Configuration ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Spatial Arrangement ◽  
Brain Regions ◽  
Imaging Data ◽  
Functional Regions ◽  
Cortical Regions ◽  
The Relationship

Brain connectivity is often considered in terms of the communication between functionally distinct brain regions. Many studies have investigated the extent to which patterns of coupling strength between multiple neural populations relates to behaviour. For example, studies have used ‘functional connectivity fingerprints’ to characterise individuals' brain activity. Here, we investigate the extent to which the exact spatial arrangement of cortical regions interacts with measures of brain connectivity. We find that the shape and exact location of brain regions interact strongly with the modelling of brain connectivity, and present evidence that the spatial arrangement of functional regions is strongly predictive of non-imaging measures of behaviour and lifestyle. We believe that, in many cases, cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Therefore, a better understanding of these effects is important when interpreting the relationship between functional imaging data and cognitive traits.

scholarly journals Author response: The relationship between spatial configuration and functional connectivity of brain regions

2018 ◽  
Author(s):  
Janine Diane Bijsterbosch ◽  
Mark W Woolrich ◽  
Matthew F Glasser ◽  
Emma C Robinson ◽  
Christian F Beckmann ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Spatial Configuration ◽  
Brain Regions ◽  
Author Response ◽  
The Relationship

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

2019 ◽  
Author(s):  
Janine Diane Bijsterbosch ◽  
Christian F Beckmann ◽  
Mark W Woolrich ◽  
Stephen M Smith ◽  
Samuel J Harrison
Keyword(s):  
Functional Connectivity ◽  
Spatial Configuration ◽  
Brain Regions ◽  
Author Response ◽  
The Relationship

scholarly journals Heritability and interindividual variability of regional structure-function coupling

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zijin Gu ◽  
Keith Wakefield Jamison ◽  
Mert Rory Sabuncu ◽  
Amy Kuceyeski
Keyword(s):  
Functional Connectivity ◽  
Structure Function ◽  
Regional Differences ◽  
Regional Scale ◽  
Brain Regions ◽  
Diffusion Weighted Mri ◽  
Regional Structure ◽  
Human Connectome Project ◽  
Structural Connections ◽  
The Relationship

AbstractWhite matter structural connections are likely to support flow of functional activation or functional connectivity. While the relationship between structural and functional connectivity profiles, here called SC-FC coupling, has been studied on a whole-brain, global level, few studies have investigated this relationship at a regional scale. Here we quantify regional SC-FC coupling in healthy young adults using diffusion-weighted MRI and resting-state functional MRI data from the Human Connectome Project and study how SC-FC coupling may be heritable and varies between individuals. We show that regional SC-FC coupling strength varies widely across brain regions, but was strongest in highly structurally connected visual and subcortical areas. We also show interindividual regional differences based on age, sex and composite cognitive scores, and that SC-FC coupling was highly heritable within certain networks. These results suggest regional structure-function coupling is an idiosyncratic feature of brain organisation that may be influenced by genetic factors.

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