scholarly journals Personalized intrinsic network topography mapping and functional connectivity deficits in Autism Spectrum Disorder

2017 ◽  
Author(s):  
Erin W. Dickie ◽  
Stephanie H. Ameis ◽  
Joseph D. Viviano ◽  
Dawn E. Smith ◽  
Navona Calarco ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Autism Spectrum ◽  
Brain Disorders ◽  
Resting State Networks ◽  
Cross Sectional ◽  
Novel Approach ◽  
Specific Variation ◽  
Spatial Locations

AbstractBackgroundRecent advances demonstrate individually specific variation in brain architecture in healthy individuals using fMRI data. To our knowledge, the effects of individually specific variation in complex brain disorders have not been previously reported.MethodsWe developed a novel approach (Personalized Intrinsic Network topography, PINT) for localizing individually specific resting state networks using conventional resting state fMRI scans. Using cross-sectional data from participants with ASD (n=393) and TD controls (n=496) across 15 sites we tested: 1) effect of diagnosis and age on the variability of intrinsic network locations and 2) whether prior findings of functional connectivity differences in ASD as compared to TD remain after PINT application.ResultsWe found greater variability in the spatial locations of resting state networks within individuals with ASD as compared to TD. In TD participants, variability decreased from childhood into adulthood, and increased again in late-life, following a ‘U-shaped’ pattern, which was not present in those with ASD. Comparison of intrinsic connectivity between groups revealed that the application of PINT decreased the number of hypo-connected regions in ASD.ConclusionsOur results provide a new framework for measuring altered brain functioning in neurodevelopmental disorders that may have implications for tracking developmental course, phenotypic heterogeneity, and ultimately treatment response. We underscore the importance of accounting for individual variation in the study of complex brain disorders.

scholarly journals The effect of global signal regression on DCM estimates of noise and effective connectivity from resting state fMRI

2019 ◽  
Author(s):  
Hannes Almgren ◽  
Frederik Van de Steen ◽  
Adeel Razi ◽  
Karl Friston ◽  
Daniele Marinazzo
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Effective Connectivity ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Measurement Noise ◽  
Resting State Networks ◽  
Cross Sectional ◽  
Global Signal ◽  
Leibler Divergence

AbstractThe influence of the global BOLD signal on resting state functional connectivity in fMRI data remains a topic of debate, with little consensus. In this study, we assessed the effects of global signal regression (GSR) on effective connectivity within and between resting-state networks – as estimated with dynamic causal modelling (DCM) for resting state fMRI (rsfMRI). DCM incorporates a forward (generative) model that quantifies the contribution of different types of noise (including global measurement noise), effective connectivity, and (neuro)vascular processes to functional connectivity measurements. DCM analyses were applied to two different designs; namely, longitudinal and cross-sectional designs. In the modelling of longitudinal designs, we included four extensive longitudinal resting state fMRI datasets with a total number of 20 subjects. In the analysis of cross-sectional designs, we used rsfMRI data from 361 subjects from the Human Connectome Project. We hypothesized that (1) GSR would have no discernible impact on effective connectivity estimated with DCM, and (2) GSR would be reflected in the parameters representing global measurement noise. Additionally, we performed comparative analyses of the informative value of data with and without GSR. Our results showed negligible to small effects of GSR on connectivity within small (separately estimated) RSNs. For between-network connectivity, we found two important effects: the effect of GSR on between-network connectivity (averaged over all connections) was negligible to small, while the effect of GSR on individual connections was non-negligible. Contrary to our expectations, we found either no effect (in the longitudinal designs) or a non-specific (cross-sectional design) effect of GSR on parameters representing (global) measurement noise. Data without GSR were found to be more informative than data with GSR; however, in small resting state networks the precision of posterior estimates was greater using data after GSR. In conclusion, GSR is a minor concern in DCM studies; however, individual between-network connections (as opposed to average between-network connectivity) and noise parameters should be interpreted quantitatively with some caution. The Kullback-Leibler divergence of the posterior from the prior, together with the precision of posterior estimates, might offer a useful measure to assess the appropriateness of GSR, when nuancing data features in resting state fMRI.

scholarly journals Strengthened thalamoparietal functional connectivity in patients with hemifacial spasm: a cross-sectional resting-state fMRI study

2020 ◽  
Vol 93 (1108) ◽  
pp. 20190887 ◽  
Author(s):  
Xuan Niu ◽  
Hui Xu ◽  
Chenguang Guo ◽  
Tong Yang ◽  
Dustin Kress ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Hemifacial Spasm ◽  
Resting State ◽  
Resting State Fmri ◽  
Association Cortex ◽  
Resting State Networks ◽  
Supramarginal Gyrus ◽  
Resting State Functional Connectivity ◽  
Cross Sectional ◽  
The Right

Objective: In spite of the well-known importance of thalamus in hemifacial spasm (HFS), the thalamic resting-state networks in HFS is still rarely mentioned. This study aimed to investigate resting-state functional connectivity (FC) of the thalamus in HFS patients and examine its association with clinical measures. Methods: 25 HFS patients and 28 matched healthy controls underwent functional MRI at rest. Using the left and right thalamus as seed regions respectively, we compared the thalamic resting-state networks between patient and control groups using two independent sample t-test. Results: Compared with controls, HFS patients exhibited strengthened bilateral thalamus-seeded FC with the parietal cortex. Enhanced FC between right thalamus and left somatosensory association cortex was linked to worse motor disturbance, and the increased right thalamus-right supramarginal gyrus connection were correlated with improvement of affective symptoms. Conclusion: Our findings indicate that the right thalamus–left somatosensory association cortex hyperconnectivity may represent the underlying neuroplasticity related to sensorimotor dysfunction. In addition, the upregulated FC between the right thalamus and right supramarginal gyrus in HFS, is part of the thalamo-default mode network pathway involved in emotional adaptation. Advances in knowledge: This study provides new insights on the integrative role of thalamo-parietal connectivity, which participates in differential neural circuitry as a mechanism underlying motor and emotional functions in HFS patients.

scholarly journals Increased Functional Connectivity Between Subcortical and Cortical Resting-State Networks in Autism Spectrum Disorder

2015 ◽  
Vol 72 (8) ◽  
pp. 767 ◽  
Author(s):  
Leonardo Cerliani ◽  
Maarten Mennes ◽  
Rajat M. Thomas ◽  
Adriana Di Martino ◽  
Marc Thioux ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Resting State ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Resting State Networks

scholarly journals Local GABA concentration is related to network-level resting functional connectivity

eLife ◽  
2014 ◽  
Vol 3 ◽  
Author(s):  
Charlotte J Stagg ◽  
Velicia Bachtiar ◽  
Ugwechi Amadi ◽  
Christel A Gudberg ◽  
Andrei S Ilie ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Primary Motor Cortex ◽  
Empirical Studies ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Resonance Spectroscopy ◽  
Resting State Networks ◽  
Inhibitory Neurotransmitter ◽  
Motor Network

Anatomically plausible networks of functionally inter-connected regions have been reliably demonstrated at rest, although the neurochemical basis of these ‘resting state networks’ is not well understood. In this study, we combined magnetic resonance spectroscopy (MRS) and resting state fMRI and demonstrated an inverse relationship between levels of the inhibitory neurotransmitter GABA within the primary motor cortex (M1) and the strength of functional connectivity across the resting motor network. This relationship was both neurochemically and anatomically specific. We then went on to show that anodal transcranial direct current stimulation (tDCS), an intervention previously shown to decrease GABA levels within M1, increased resting motor network connectivity. We therefore suggest that network-level functional connectivity within the motor system is related to the degree of inhibition in M1, a major node within the motor network, a finding in line with converging evidence from both simulation and empirical studies.

Inter-Hemispherical Investigations on the Functional Connectivity in Controls and Autism Spectrum Using Resting State fMRI

2020 ◽  
pp. 169-186
Author(s):  
S. Vidhusha ◽  
A. Kavitha
Keyword(s):  
Functional Connectivity ◽  
Granger Causality ◽  
Resting State ◽  
Cognitive Task ◽  
Resting State Fmri ◽  
Autism Spectrum ◽  
Control Group ◽  
Neural Connectivity ◽  
Activation Patterns ◽  
The Brain

Autism spectrum disorders are connected with disturbances of neural connectivity. Functional connectivity is typically examined during a cognitive task, but also exists in the absence of a task. While a number of studies have performed functional connectivity analysis to differentiate controls and autism individuals, this work focuses on analyzing the brain activation patterns not only between controls and autistic subjects, but also analyses the brain behaviour present within autism spectrum. This can bring out more intuitive ways to understand that autism individuals differ individually. This has been performed between autism group relative to the control group using inter-hemispherical analysis. Indications of under connectivity were exhibited by the Granger Causality (GC) and Conditional Granger Causality (CGC) in autistic group. Results show that as connectivity decreases, the GC and CGC values also get decreased. Further, to demark the differences present within the spectrum of autistic individuals, GC and CGC values have been calculated.

scholarly journals Concurrent tACS-fMRI reveals causal influence of power synchronized neural activity on resting state fMRI connectivity

2017 ◽  
Author(s):  
Marc Bächinger ◽  
Valerio Zerbi ◽  
Marius Moisa ◽  
Rafael Polania ◽  
Quanying Liu ◽  
...  
Keyword(s):  
Resting State ◽  
Right Hemisphere ◽  
Brain Connectivity ◽  
Resting State Fmri ◽  
Causal Link ◽  
Resting State Networks ◽  
Novel Approach ◽  
Electrophysiological Signals ◽  
Power Fluctuations ◽  
Transcranial Alternating Current Stimulation

AbstractResting state fMRI (rs-fMRI) is commonly used to study the brain’s intrinsic neural coupling, which reveals specific spatiotemporal patterns in the form of resting state networks (RSN). It has been hypothesized that slow rs-fMRI oscillations (<0.1 Hz) are driven by underlying electrophysiological rhythms that typically occur at much faster timescales (>5 Hz); however, causal evidence for this relationship is currently lacking. Here we measured rs-fMRI in humans while applying transcranial alternating current stimulation (tACS) to entrain brain rhythms in left and right sensorimotor cortices.The two driving tACS signals were tailored to the individual’s alpha rhythm (8-12 Hz) and fluctuated in amplitude according to a 1 Hz power envelope. We entrained the left versus right hemisphere in accordance to two different coupling modes where either alpha oscillations were synchronized between hemispheres (phase-synchronized tACS) or the slower oscillating power envelopes (power-synchronized tACS).Power-synchronized tACS significantly increased rs-fMRI connectivity within the stimulated RSN compared to phase-synchronized or no tACS. This effect outlasted the stimulation period and tended to be more effective in individuals who exhibited a naturally weak interhemispheric coupling. Using this novel approach, our data provide causal evidence that synchronized power fluctuations contribute to the formation of fMRI-based RSNs. Moreover, our findings demonstrate that the brain’s intrinsic coupling at rest can be selectively modulated by choosing appropriate tACS signals, which could lead to new interventions for patients with altered rs-fMRI connectivity.Significance StatementResting state fMRI has become an important tool to estimate brain connectivity. However, relatively little is known about how slow hemodynamic oscillations measured with fMRI relate to electrophysiological processes.It was suggested that slowly fluctuating power envelopes of electrophysiological signals synchronize across brain areas and that the topography of this activity is spatially correlated to resting state networks derived from rs-fMRI. Here we take a novel approach to address this problem and establish a causal link between the power fluctuations of electrophysiological signals and rs-fMRI via a new neuromodulation paradigm, which exploits these power-synchronization mechanisms.These novel mechanistic insights bridge different scientific domains and are of broad interest to researchers in the fields of Medical Imaging, Neuroscience, Physiology and Psychology.

scholarly journals Hypo- and hyper-connectivity in default mode network related to social impairment in tweens with autism spectrum disorder

2016 ◽  
Author(s):  
Wilma Matthysen ◽  
Daniele Marinazzo ◽  
Roma Siugzdaite
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Default Mode Network ◽  
Social Communication ◽  
Resting State ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Connectivity Pattern ◽  
Resting State Networks ◽  
Default Mode

Background. Autism spectrum disorder is a neurodevelopmental disorder, marked by impairment in social communication and restricted, repetitive patterns of behavior, interests, or activities. Accumulating data suggests that alterations in functional connectivity might contribute to these deficits. Whereas functional connectivity in resting state fMRI is expressed by several resting-state networks, for this study we examined several of them, but our particular interest was in the default mode network (DMN), given its age dependent alteration of functional connectivity and its relation to social communication. Methods. Since the studies investigating young children (6-8 years) with autism have found hypo-connectivity in DMN and studies on adolescents (12-16 years old) with autism have found hyper-connectivity in the DMN, we were interested in connectivity pattern during the age of 8 to 12, so we investigated the role of altered intrinsic connectivity in 16 children (mean age 9.75 ±1.6 years) with autism spectrum disorder compared to 16 typically developing controls in the DMN and other resting-state networks. Results. Results show that, compared to controls, the group with autism spectrum disorder showed signs of both hypo- and hyper-connectivity in different regions of the resting-state networks related to social communication. Conclusion. That suggests that transition period from childhood to adolescence carries the complexity of functional connectivity from both age groups. Regions that showed differences in functional connectivity were discussed in relation to social communication difficulties.

scholarly journals Reduced functional connectivity within and between ‘social’ resting state networks in autism spectrum conditions

2012 ◽  
Vol 8 (6) ◽  
pp. 694-701 ◽  
Author(s):  
Elisabeth A. H. von dem Hagen ◽  
Raliza S. Stoyanova ◽  
Simon Baron-Cohen ◽  
Andrew J. Calder
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Autism Spectrum ◽  
Autism Spectrum Conditions ◽  
Resting State Networks

scholarly journals Propagating patterns of intrinsic activity along macroscale gradients coordinate functional connections across the whole brain

2020 ◽  
Author(s):  
Behnaz Yousefi ◽  
Shella Keilholz
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Spatial Organization ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Intrinsic Activity ◽  
Resting State Networks ◽  
Whole Brain ◽  
Functional Connections ◽  
Driving Mechanisms

The intrinsic activity of the human brain, observed with resting-state fMRI (rsfMRI) and functional connectivity, exhibits macroscale spatial organization such as resting-state networks (RSNs) and functional connectivity gradients (FCGs). Dynamic analysis techniques have shown that the time-averaged maps captured by functional connectivity are mere summaries of time-varying patterns with distinct spatial and temporal characteristics. A better understanding of these patterns might provide insight into aspects of the brain intrinsic activity that cannot be inferred by functional connectivity, RSNs or FCGs. Here, we describe three spatiotemporal patterns of coordinated activity across the whole brain obtained by averaging similar ~20-second-long segments of rsfMRI timeseries. In each of these patterns, activity propagates along a particular macroscale FCG, simultaneously across the cortical sheet and in most other brain regions. In some areas, like the thalamus, the propagation suggests previously-undescribed FCGs. The coordinated activity across areas is consistent with known tract-based connections, and nuanced differences in the timing of peak activity between brain regions point to plausible driving mechanisms. The magnitude of correlation within and particularly between RSNs is remarkably diminished when these patterns are regressed from the rsfMRI timeseries, a quantitative demonstration of their significant role in functional connectivity. Taken together, our results suggest that a few recurring patterns of propagating intrinsic activity along macroscale gradients give rise to and coordinate functional connections across the whole brain.

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