scholarly journals Intrinsic, dynamic and effective connectivity among large-scale brain networks modulated by oxytocin

2020 ◽  
Author(s):  
Xi Jiang ◽  
Xiaole Ma ◽  
Yayuan Geng ◽  
Zhiying Zhao ◽  
Feng Zhou ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Emotional Processing ◽  
Large Scale ◽  
Effective Connectivity ◽  
Brain Networks ◽  
Emotional Behavior ◽  
Dependent Manner ◽  
Social Emotional ◽  
Using Data

AbstractThe neuropeptide oxytocin is a key modulator of social-emotional behavior and its intranasal administration can influence the functional connectivity of brain networks involved in the control of attention, emotion and reward reported in humans. However, no studies have systematically investigated the effects oxytocin on dynamic or directional aspects of functional connectivity. The present study employed a novel computational framework to investigate these latter aspects in 15 oxytocin-sensitive regions using data from randomized placebo-controlled between-subject resting state functional MRI studies incorporating 200 healthy subjects. Results showed that oxytocin extensively modulated effective connectivity both between and within emotion, reward, salience and social cognition processing networks and their interactions with the default mode network, but had no effect on the frequency of dynamic changes. Top-down control over emotional processing regions such as the amygdala was particularly affected. Oxytocin effects were also sex-dependent, being more extensive in males. Overall, these findings suggest that modulatory effects of oxytocin on both within- and between-network interactions may underlie its functional influence on social-emotional behaviors, although in a sex-dependent manner. Furthermore, they demonstrate a useful approach to determining pharmacological influences on resting state effective connectivity and support oxytocin’s potential therapeutic use in psychiatric disorders.

scholarly journals Large-scale DCMs for resting-state fMRI

2017 ◽  
Vol 1 (3) ◽  
pp. 222-241 ◽  
Author(s):  
Adeel Razi ◽  
Mohamed L. Seghier ◽  
Yuan Zhou ◽  
Peter McColgan ◽  
Peter Zeidman ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Effective Connectivity ◽  
Directed Graphs ◽  
Resting State Fmri ◽  
Causal Modeling ◽  
Large Graphs ◽  
Model Inversion ◽  
Graph Theoretic

This paper considers the identification of large directed graphs for resting-state brain networks based on biophysical models of distributed neuronal activity, that is, effective connectivity. This identification can be contrasted with functional connectivity methods based on symmetric correlations that are ubiquitous in resting-state functional MRI (fMRI). We use spectral dynamic causal modeling (DCM) to invert large graphs comprising dozens of nodes or regions. The ensuing graphs are directed and weighted, hence providing a neurobiologically plausible characterization of connectivity in terms of excitatory and inhibitory coupling. Furthermore, we show that the use of Bayesian model reduction to discover the most likely sparse graph (or model) from a parent (e.g., fully connected) graph eschews the arbitrary thresholding often applied to large symmetric (functional connectivity) graphs. Using empirical fMRI data, we show that spectral DCM furnishes connectivity estimates on large graphs that correlate strongly with the estimates provided by stochastic DCM. Furthermore, we increase the efficiency of model inversion using functional connectivity modes to place prior constraints on effective connectivity. In other words, we use a small number of modes to finesse the potentially redundant parameterization of large DCMs. We show that spectral DCM—with functional connectivity priors—is ideally suited for directed graph theoretic analyses of resting-state fMRI. We envision that directed graphs will prove useful in understanding the psychopathology and pathophysiology of neurodegenerative and neurodevelopmental disorders. We will demonstrate the utility of large directed graphs in clinical populations in subsequent reports, using the procedures described in this paper.

scholarly journals Variability and reliability of effective connectivity within the core default mode network: A longitudinal spectral DCM study

2018 ◽  
Author(s):  
Hannes Almgren ◽  
Frederik Van de Steen ◽  
Simone Kühn ◽  
Adeel Razi ◽  
Karl Friston ◽  
...  
Keyword(s):  
Resting State ◽  
Hemispheric Asymmetry ◽  
Large Scale ◽  
Effective Connectivity ◽  
Brain Networks ◽  
Resting State Fmri ◽  
Global Signal ◽  
Cognitive Behavioural ◽  
Connectivity Patterns ◽  
Within Subjects

AbstractDynamic causal modelling (DCM) for resting state fMRI – namely spectral DCM – is a recently developed and widely adopted method for inferring effective connectivity in intrinsic brain networks. Most research applying spectral DCM has focused on group-averaged connectivity within large-scale intrinsic brain networks; however, the consistency of subject- and session-specific estimates of effective connectivity has not been evaluated. Establishing reliability (within subjects) is crucial for its clinical use; e.g., as a neurophysiological phenotype of disease progression. Effective connectivity during rest is likely to vary due to changes in cognitive, behavioural, and physical states. Determining the sources of fluctuations in effective connectivity may yield greater understanding of brain processes and inform clinical applications about potential confounds. In the present study, we investigated the consistency of effective connectivity within and between subjects, as well as potential sources of variability (e.g., hemispheric asymmetry). We further investigated how standard procedures for data processing and signal extraction affect this consistency. DCM analyses were applied to four longitudinal resting state fMRI datasets. Our sample consisted of 20 subjects with 653 resting state fMRI sessions in total. These data allowed to quantify the robustness of connectivity estimates for each subject, and to draw conclusions beyond specific data features. We found that subjects contributing to all datasets showed systematic and reliable patterns of hemispheric asymmetry. When asymmetry was taken into account, subjects showed very similar connectivity patterns. We also found that various processing procedures (e.g. global signal regression and ROI size) had little effect on inference and reliability of connectivity for the majority of subjects. Bayesian model reduction increased reliability (within-subjects) and stability (between-subjects) of connectivity patterns.

scholarly journals Reduced Inter-hemispheric Resting State Functional Connectivity and Its Association With Social Deficits in Autism

2021 ◽  
Vol 12 ◽  
Author(s):  
Shuxia Yao ◽  
Benjamin Becker ◽  
Keith M. Kendrick
Keyword(s):  
Functional Connectivity ◽  
Functional Mri ◽  
Resting State ◽  
Early Onset ◽  
Large Scale ◽  
Brain Networks ◽  
Autism Spectrum ◽  
Classification Performance ◽  
Functional Impairments ◽  
Resting State Functional Connectivity

Autism spectrum disorder (ASD) is an early onset developmental disorder which persists throughout life and is increasing in prevalence over the last few decades. Given its early onset and variable cognitive and emotional functional impairments, it is generally challenging to assess ASD individuals using task-based behavioral and functional MRI paradigms. Consequently, resting state functional MRI (rs-fMRI) has become a key approach for examining ASD-associated neural alterations and revealed functional alterations in large-scale brain networks relative to typically developing (TD) individuals, particularly those involved in social-cognitive and affective processes. Recent progress suggests that alterations in inter-hemispheric resting state functional connectivity (rsFC) between regions in the 2 brain hemispheres, particularly homotopic ones, may be of great importance. Here we have reviewed neuroimaging studies examining inter-hemispheric rsFC abnormities in ASD and its associations with symptom severity. As an index of inter-hemispheric functional connectivity, we have additionally reviewed previous studies on corpus callosum (CC) volumetric and fiber changes in ASD. There are converging findings on reduced inter-hemispheric (including homotopic) rsFC in large-scale brain networks particularly in posterior hubs of the default mode network, reduced volumes in the anterior and posterior CC, and on decreased FA and increased MD or RD across CC subregions. Associations between the strength of inter-hemispheric rsFC and social impairments in ASD together with their classification performance in distinguishing ASD subjects from TD controls across ages suggest that the strength of inter-hemispheric rsFC may be a more promising biomarker for assisting in ASD diagnosis than abnormalities in either brain wide rsFC or brain structure.

Gait variability is associated with the strength of functional connectivity between the default and dorsal attention brain networks: evidence from multiple cohorts

2021 ◽  
Author(s):  
On-Yee Lo ◽  
Mark A Halko ◽  
Kathryn J Devaney ◽  
Peter M Wayne ◽  
Lewis A Lipsitz ◽  
...  
Keyword(s):  
Older Adults ◽  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Brain Networks ◽  
Gait Variability ◽  
Default Network ◽  
Attention Network ◽  
Dorsal Attention Network ◽  
Age And Sex

Abstract Background In older adults, elevated gait variability when walking has been associated with both cognitive impairment and future falls. This study leveraged three existing datasets to determine relationships between gait variability and the strength of functional connectivity within and between large-scale brain networks in healthy older adults, those with mild-to-moderate functional impairment, and those with Parkinson’s disease (PD). Method Gait and resting-state fMRI data were extracted from existing datasets on: 1) 12 older adults without overt disease yet with slow gait and mild executive dysfunction; 2) 12 older adults with intact cognitive-motor function and age- and sex-matched to the first cohort; and 3) 15 individuals with PD. Gait variability (%, coefficient of variation of stride time) during preferred walking speed was measured and correlated with the degree of functional connectivity within and between seven established large-scale functional brain networks. Results Regression models adjusted for age and sex revealed that in each cohort, those with less gait variability exhibited greater negative correlation between fluctuations in resting-state brain activity between the default network and the dorsal attention network (Functionally-limited older: β=4.38, p=.027; Healthy older: β=1.66, p=.032; PD: β=1.65, p=.005). No other within- or between- network connectivity outcomes were consistently related to gait variability across all three cohorts. Conclusion These results provide strong evidence that gait variability is uniquely related to functional connectivity between the default network and the dorsal attention network, and that this relationship may be independent of both functional status and underlying brain disease.

scholarly journals A randomized trial shows dose-frequency and genotype may determine the therapeutic efficacy of intranasal oxytocin

2020 ◽  
Author(s):  
Juan Kou ◽  
Yingying Zhang ◽  
Feng Zhou ◽  
Cornelia Sindermann ◽  
Christian Montag ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Emotional Behavior ◽  
Resting State Functional Connectivity ◽  
Social Emotional ◽  
Dose Frequency ◽  
Double Blind ◽  
Anxious Arousal ◽  
Male Subjects ◽  
Treatment Sensitivity

Abstract Background. The neuropeptide oxytocin is proposed as a promising therapy for social dysfunction by modulating amygdala-mediated social-emotional behavior. Although clinical trials report some benefits of chronic treatment it is unclear whether efficacy may be influenced by dose frequency or genotype. Methods. In a randomized, double blind, placebo-controlled pharmaco-fMRI trial (150 male subjects) we investigated acute and different chronic (every day or on alternate days for 5 days) intranasal oxytocin (24IU) effects and oxytocin receptor genotype-mediated treatment sensitivity on amygdala responses to face emotions. We also investigated similar effects on resting state functional connectivity between the amygdala and prefrontal cortex. Results. A single dose of oxytocin reduced amygdala responses to all face emotions but for threatening (fear and anger) and happy faces this effect was abolished after daily doses for 5 days but maintained by doses given every other day. The latter dose regime also enhanced associated anxious-arousal attenuation for fear faces. Oxytocin effects on reducing amygdala responses to face emotions only occurred in AA homozygotes of rs53576 and A carriers of rs2254298. The effects of oxytocin on resting state functional connectivity were not influenced by either dose-frequency or receptor genotype. Conclusions. Infrequent chronic oxytocin administration may be therapeutically most efficient and its anxiolytic neural and behavioral actions are highly genotype-dependent in males.

scholarly journals Reconfiguration of directed functional connectivity among triple networks with aging: Considering the role of thalamo-cortical interactions

2019 ◽  
Author(s):  
Moumita Das ◽  
Vanshika Singh ◽  
Lucina Uddin ◽  
Arpan Banerjee ◽  
Dipanjan Roy
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Effective Connectivity ◽  
Network Connectivity ◽  
Young Group ◽  
Resting State Functional Connectivity ◽  
Functional Changes ◽  
Age Related ◽  
Directional Connectivity

AbstractThe human brain undergoes significant structural and functional changes across the lifespan. Our current understanding of the underlying causal relationships of dynamical changes in functional connectivity with age is limited. On average, functional connectivity within resting-state networks (RSNs) weakens in magnitude, while connections between RSNs tend to increase with age. Recent studies show that effective connectivity within and between large scale resting-state functional networks changes over the healthy lifespan. The vast majority of previous studies have focused primarily on characterizing cortical networks, with little work exploring the influence of subcortical nodes such as the thalamus on large-scale network interactions across the lifespan. Using directed connectivity and weighted net causal outflow measures applied to resting-state fMRI data, we examine the age-related changes in both cortical and thalamocortical causal interactions within and between RSNs. The three core neurocognitive networks from the triple network theory (default mode: DMN, salience: SN, and central executive: CEN) were identified independently using ICA and spatial matching of hub regions with these important RSNs previously reported in the literature. Multivariate granger causal analysis (GCA) was performed to test for directional connectivity and weighted causal outflow between selected nodes of RSNs accounting for thalamo-cortical interactions. Firstly, we observe that within-network causal connections become progressively weaker with age, and network dynamics are substantially reconfigured via strong thalamic drive particularly in the young group. Our findings manifest stronger between-network directional connectivity, which is further strongly mediated by the SN in flexible co-ordination with the CEN, and DMN in the old group compared with the young group. Hence, causal within- and between- triple network connectivity largely reflects age-associated effects of resting-state functional connectivity. Thalamo-cortical causality effects on the triple networks with age were next explored. We discovered that left and right thalamus exhibit substantial interactions with the triple networks and play a crucial role in the reconfiguration of directed connections and within network causal outflow. The SN displayed directed functional connectivity in strongly driving both the CEN and DMN to a greater extent in the older group. Notably, these results were largely replicated on an independent dataset of matched young and old individuals. Our findings based on directed functional connectivity and weighted causal outflow measures strengthen the hypothesis that balancing within and between network connectivity is perhaps critical for the preservation and flexibility of cognitive functioning with aging.

scholarly journals A randomized trial shows dose-frequency and genotype may determine the therapeutic efficacy of intranasal oxytocin

2020 ◽  
pp. 1-10
Author(s):  
Juan Kou ◽  
Yingying Zhang ◽  
Feng Zhou ◽  
Cornelia Sindermann ◽  
Christian Montag ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Emotional Behavior ◽  
Functional Magnetic Resonance ◽  
Resting State Functional Connectivity ◽  
Social Emotional ◽  
Dose Frequency ◽  
Double Blind ◽  
Male Subjects ◽  
Treatment Sensitivity

Abstract Background The neuropeptide oxytocin is proposed as a promising therapy for social dysfunction by modulating amygdala-mediated social-emotional behavior. Although clinical trials report some benefits of chronic treatment, it is unclear whether efficacy may be influenced by dose frequency or genotype. Methods In a randomized, double-blind, placebo-controlled pharmaco-functional magnetic resonance imaging trial (150 male subjects), we investigated acute and different chronic (every day or on alternate days for 5 days) intranasal oxytocin (24 international units) effects and oxytocin receptor genotype-mediated treatment sensitivity on amygdala responses to face emotions. We also investigated similar effects on resting-state functional connectivity between the amygdala and prefrontal cortex. Results A single dose of oxytocin-reduced amygdala responses to all face emotions but for threatening (fear and anger) and happy faces, this effect was abolished after daily doses for 5 days but maintained by doses given every other day. The latter dose regime also enhanced associated anxious-arousal attenuation for fear faces. Oxytocin effects on reducing amygdala responses to face emotions only occurred in AA homozygotes of rs53576 and A carriers of rs2254298. The effects of oxytocin on resting-state functional connectivity were not influenced by either dose-frequency or receptor genotype. Conclusions Infrequent chronic oxytocin administration may be therapeutically most efficient and its anxiolytic neural and behavioral actions are highly genotype-dependent in males.

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