scholarly journals Multimodal Classification of Mild Traumatic Brain Injury Reveals Local Coupling Between Structural and Functional Connectomes

2021 ◽  
Author(s):  
Ajay Peddada ◽  
Kevin Holly ◽  
Tejaswi D Sudhakar ◽  
Christina Ledbetter ◽  
Christopher E. Talbot ◽  
...  
Keyword(s):  
White Matter ◽  
Functional Connectivity ◽  
Temporal Lobe ◽  
Resting State ◽  
Classification Accuracy ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Group Differences ◽  
Functional Connections ◽  
White Matter Tractography

Background: Following mild traumatic brain injury (mTBI) compromised white matter structural integrity can result in alterations in functional connectivity of large-scale brain networks and may manifest in functional deficit including cognitive dysfunction . Advanced magnetic resonance neuroimaging techniques, specifically diffusion tensor imaging (DTI) and resting state functional magnetic resonance imaging (rs-fMRI), have demonstrated an increased sensitivity for detecting microstructural changes associated with mTBI. Identification of novel imaging biomarkers can facilitate early detection of these changes for effective treatment. In this study, we hypothesize that feature selection combining both structural and functional connectivity increases classification accuracy. Methods: 16 subjects with mTBI and 20 healthy controls underwent both DTI and resting state functional imaging. Structural connectivity matrices were generated from white matter tractography from DTI sequences. Functional connectivity was measured through pairwise correlations of rs-fMRI between brain regions. Features from both DTI and rs-fMRI were selected by identifying five brain regions with the largest group differences and were used to classify the generated functional and structural connectivity matrices, respectively. Classification was performed using linear support vector machines and validated with leave-one-out cross validation. Results: Group comparisons revealed increased functional connectivity in the temporal lobe and cerebellum as well as decreased structural connectivity in the temporal lobe. After training on structural connections only, a maximum classification accuracy of 78% was achieved when structural connections were selected based on their corresponding functional connectivity group differences. After training on functional connections only, a maximum classification accuracy of 69% was achieved when functional connections were selected based on their structural connectivity group differences. After training on both structural and functional connections, a maximum classification accuracy of 69% was achieved when connections were selected based on their structural connectivity. Conclusions: Our multimodal approach to ROI selection achieves at highest, a classification accuracy of 78%. Our results also implicate the temporal lobe in the pathophysiology of mTBI. Our findings suggest that white matter tractography can serve as a robust biomarker for mTBI when used in tandem with resting state functional connectivity.

Altered Resting-State Functional and White Matter Tract Connectivity in Stroke Patients With Dysphagia

2013 ◽  
Vol 28 (3) ◽  
pp. 260-272 ◽  
Author(s):  
Shasha Li ◽  
Zhenxing Ma ◽  
Shipeng Tu ◽  
Muke Zhou ◽  
Sihan Chen ◽  
...  
Keyword(s):  
White Matter ◽  
Functional Connectivity ◽  
Fractional Anisotropy ◽  
Resting State ◽  
Structural Connectivity ◽  
White Matter Tract ◽  
Stroke Patients ◽  
Hemispheric Stroke ◽  
Swallowing Dysfunction ◽  
The Mean

Background. Swallowing dysfunction is intractable after acute stroke. Our understanding of the alterations in neural networks of patients with neurogenic dysphagia is still developing. Objective. The aim was to investigate cerebral cortical functional connectivity and subcortical structural connectivity related to swallowing in unilateral hemispheric stroke patients with dysphagia. Methods. We combined a resting-state functional connectivity with a white matter tract connectivity approach, recording 12 hemispheric stroke patients with dysphagia, 12 hemispheric stroke patients without dysphagia, and 12 healthy controls. Comparisons of the patterns in swallowing-related functional connectivity maps between patient groups and control subjects included ( a) seed-based functional connectivity maps calculated from the primary motor cortex (M1) and the supplementary motor area (SMA) to the entire brain, ( b) a swallowing-related functional connectivity network calculated among 20 specific regions of interest (ROIs), and ( c) structural connectivity described by the mean fractional anisotropy of fibers bound through the SMA and M1. Results. Stroke patients with dysphagia exhibited dysfunctional connectivity mainly in the sensorimotor-insula-putamen circuits based on seed-based analysis of the left and right M1 and SMA and decreased connectivity in the bilateral swallowing-related ROIs functional connectivity network. Additionally, white matter tract connectivity analysis revealed that the mean fractional anisotropy of the white matter tract was significantly reduced, especially in the left-to-right SMA and in the corticospinal tract. Conclusions. Our results indicate that dysphagia secondary to stroke is associated with disruptive functional and structural integrity in the large-scale brain networks involved in motor control, thus providing new insights into the neural remodeling associated with this disorder.

scholarly journals Using structural connectivity to augment community structure in EEG functional connectivity

2020 ◽  
Vol 4 (3) ◽  
pp. 761-787 ◽  
Author(s):  
Katharina Glomb ◽  
Emeline Mullier ◽  
Margherita Carboni ◽  
Maria Rubega ◽  
Giannarita Iannotti ◽  
...  
Keyword(s):  
Community Structure ◽  
White Matter ◽  
Functional Connectivity ◽  
Large Scale ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Source Analysis ◽  
Volume Conduction ◽  
Functional Relationships ◽  
The Impact

Recently, EEG recording techniques and source analysis have improved, making it feasible to tap into fast network dynamics. Yet, analyzing whole-cortex EEG signals in source space is not standard, partly because EEG suffers from volume conduction: Functional connectivity (FC) reflecting genuine functional relationships is impossible to disentangle from spurious FC introduced by volume conduction. Here, we investigate the relationship between white matter structural connectivity (SC) and large-scale network structure encoded in EEG-FC. We start by confirming that FC (power envelope correlations) is predicted by SC beyond the impact of Euclidean distance, in line with the assumption that SC mediates genuine FC. We then use information from white matter structural connectivity in order to smooth the EEG signal in the space spanned by graphs derived from SC. Thereby, FC between nearby, structurally connected brain regions increases while FC between nonconnected regions remains unchanged, resulting in an increase in genuine, SC-mediated FC. We analyze the induced changes in FC, assessing the resemblance between EEG-FC and volume-conduction- free fMRI-FC, and find that smoothing increases resemblance in terms of overall correlation and community structure. This result suggests that our method boosts genuine FC, an outcome that is of interest for many EEG network neuroscience questions.

scholarly journals 3046 Reduced structural and functional connectivity in infants with prenatal opioid exposure

2019 ◽  
Vol 3 (s1) ◽  
pp. 52-52
Author(s):  
Stephanie Merhar ◽  
Adebayo Braimah ◽  
Traci Beiersdorfer ◽  
Brenda Poindexter ◽  
Nehal Parikh
Keyword(s):  
White Matter ◽  
Functional Connectivity ◽  
Fractional Anisotropy ◽  
Behavioral Problems ◽  
Resting State ◽  
Maternal Education ◽  
Structural Connectivity ◽  
Resting State Functional Connectivity ◽  
Small Pilot Study ◽  
Sensorimotor Network

OBJECTIVES/SPECIFIC AIMS:. This study aims to understand the effects of prenatal opioid exposure on structural and functional connectivity in the neonatal brain. Our central hypothesis is that infants with prenatal opioid exposure will have decreased structural and functional connectivity as compared to non-exposed controls. Our overarching goal is to improve neurodevelopmental and behavioral outcomes in infants with prenatal opioid exposure. METHODS/STUDY POPULATION:. Infants with prenatal opioid exposure were recruited from 2 birth hospitals in our area. Control infants were recruited from the larger community. Infants underwent MRI between 4-6 weeks of age in the Cincinnati Children’s Hospital Imaging Research Center. MRI sequences included 3D structural T1 and T2-weighted imaging, resting state functional connectivity MRI, and multi-shell DTI (36 directions at b=800 and 68 directions at b=2000). Tract-based spatial statistics (TBSS) was used to identify differences in fractional anisotropy (a measure of white matter integrity) between groups. Group independent component analysis was used to identify differences in resting-state networks between groups RESULTS/ANTICIPATED RESULTS:. There were 5 subjects enrolled in the study with evaluable imaging, 3 infants with prenatal opioid exposure and 2 unexposed controls. Structural MRI was normal in all cases. Infants with prenatal opioid exposure had reduced structural connectivity as measured by fractional anisotropy (FA) in the genu and splenium of the corpus callosum as compared with controls. The orange/red color represents areas in which the FA of the opioid-exposed group was lower than controls and green represents the white matter skeleton common to both groups. Infants with prenatal opioid exposure also had significantly reduced within-network functional connectivity strength (z-transformed partial correlation coefficient 0.358 vs 0.199, p = 0.03) in the sensorimotor network as compared with controls. DISCUSSION/SIGNIFICANCE OF IMPACT:. In this small pilot study, both structural and functional connectivity were reduced in opioid-exposed infants compared with controls. This data suggests that differences in structural and functional connectivity may underlie the later developmental and behavioral problems seen in opioid-exposed children. These findings must be validated in a larger population with correction for confounding factors such as maternal education

scholarly journals New graph-theoretical-multimodal approach using temporal and structural correlations reveal disruption in the thalamo-cortical network in patients with schizophrenia

2018 ◽  
Author(s):  
Paolo Finotteli ◽  
Caroline Garcia Forlim ◽  
Paolo Dulio ◽  
Leonie Klock ◽  
Alessia Pini ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Brain Connectivity ◽  
Brain Networks ◽  
Structural Connectivity ◽  
Network Models ◽  
Brain Regions ◽  
Cortical Network ◽  
Future Research ◽  
Connectivity Matrix

Schizophrenia has been understood as a network disease with altered functional and structural connectivity in multiple brain networks compatible to the extremely broad spectrum of psychopathological, cognitive and behavioral symptoms in this disorder. When building brain networks, functional and structural networks are typically modelled independently: functional network models are based on temporal correlations among brain regions, whereas structural network models are based on anatomical characteristics. Combining both features may give rise to more realistic and reliable models of brain networks. In this study, we applied a new flexible graph-theoretical-multimodal model called FD (F, the functional connectivity matrix, and D, the structural matrix) to construct brain networks combining functional, structural and topological information of MRI measurements (structural and resting state imaging) to patients with schizophrenia (N=35) and matched healthy individuals (N=41). As a reference condition, the traditional pure functional connectivity (pFC) analysis was carried out. By using the FD model, we found disrupted connectivity in the thalamo-cortical network in schizophrenic patients, whereas the pFC model failed to extract group differences after multiple comparison correction. We interpret this observation as evidence that the FD model is superior to conventional connectivity analysis, by stressing relevant features of the whole brain connectivity including functional, structural and topological signatures. The FD model can be used in future research to model subtle alterations of functional and structural connectivity resulting in pronounced clinical syndromes and major psychiatric disorders. Lastly, FD is not limited to the analysis of resting state fMRI, and can be applied to EEG, MEG etc.

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.

scholarly journals Interhemispheric Integration for Complex Behaviors, Absent the Corpus Callosum in Normal Ontogeny

2018 ◽  
Author(s):  
Elliot A. Layden ◽  
Kathryn E. Schertz ◽  
Sarah E. London ◽  
Marc G. Berman
Keyword(s):  
White Matter ◽  
Functional Connectivity ◽  
Corpus Callosum ◽  
Zebra Finch ◽  
Resting State ◽  
Hemispheric Specialization ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Human Language ◽  
Brain Functions

AbstractFunctional homotopy, or synchronous spontaneous activity between symmetric, contralateral brain regions, is a fundamental characteristic of the mammalian brain’s functional architecture(1–6). In mammals, functional homotopy may be predominantly mediated by the corpus callosum (CC), a white matter structure thought to balance the interhemispheric coordination and hemispheric specialization critical for many complex brain functions, including lateralized human language abilities(7, 8). The CC first emerged with the Eutherian (placental) mammals ~160 MYA and is not found in other vertebrates(9, 10). Despite this, other vertebrates also exhibit complex brain functions requiring bilateral integration and lateralization(11). For example, much as humans acquire speech, the zebra finch (Taeniopygia guttata) songbird learns to sing from tutors and must balance hemispheric specialization(12) with interhemispheric coordination to successfully learn and produce song(13). We therefore tested whether the zebra finch brain also exhibits functional homotopy despite lacking the CC. Implementing custom resting-state fMRI (rs-fMRI) functional connectivity (FC) analyses, we demonstrate widespread functional homotopy between pairs of contralateral brain regions required for learned song but which lack direct anatomical projections (i.e., structural connectivity; SC). We believe this is the first demonstration of functional homotopy in a non-Eutherian vertebrate; however, it is unlikely to be the only instance of it. The remarkable congruence between functional homotopy in the zebra finch and Eutherian brains indicates that alternative mechanisms must exist for balanced interhemispheric coordination in the absence of a CC. This insight may have broad implications for understanding complex, bilateral neural processing across phylogeny and how information is integrated between hemispheres.Significance StatementThe mammalian brain exhibits strongly synchronized hemodynamic activity (i.e., functional connectivity) between symmetric, contralateral (i.e., homotopic) brain regions. This pattern is thought to be largely mediated by the corpus callosum (CC), a large white matter tract unique to mammals, which balances interhemispheric coordination and lateralization. Many complex brain functions, including human language, are thought to critically rely upon this balance. Despite lacking the CC, the zebra finch exhibits a song learning process with striking parallels to human speech acquisition, including lateralization and interhemispheric coordination. Using resting-state fMRI, we show that the zebra finch brain exhibits widespread homotopic functional connectivity within a network critical for learned song, suggesting that this symmetrical activity pattern may phylogenetically precede the evolution of the CC.

scholarly journals Unsupervised clustering of track-weighted dynamic functional connectivity reveals white matter substrates of functional connectivity dynamics

2021 ◽  
Author(s):  
Gianpaolo Antonio Basile ◽  
Salvatore Bertino ◽  
Victor Nozais ◽  
Alessia Bramanti ◽  
Rosella Ciurleo ◽  
...  
Keyword(s):  
White Matter ◽  
Functional Connectivity ◽  
Resting State ◽  
Time Course ◽  
Brain Connectivity ◽  
Structural Connectivity ◽  
Resting State Fmri ◽  
Dynamic Changes ◽  
Dynamic Functional Connectivity ◽  
Dynamic Connectivity

AbstractThe contribution of structural connectivity to functional connectivity dynamics is still far from being fully elucidated. Herein, we applied track-weighted dynamic functional connectivity (tw-dFC), a model integrating structural, functional, and dynamic connectivity, on high quality diffusion weighted imaging and resting-state fMRI data from two independent repositories. The tw-dFC maps were analyzed using independent component analysis, aiming at identifying spatially independent white matter components which support dynamic changes in functional connectivity. Each component consisted of a spatial map of white matter bundles that show consistent fluctuations in functional connectivity at their endpoints, and a time course representative of such functional activity. These components show high intra-subject, inter-subject, and inter-cohort reproducibility. We provided also converging evidence that functional information about white matter activity derived by this method can capture biologically meaningful features of brain connectivity organization, as well as predict higher-order cognitive performance.

scholarly journals White matter hyperintensity-associated structural disconnection, resting state functional connectivity, and cognitive control in older adults

2020 ◽  
Author(s):  
Abhishek Jaywant ◽  
Katharine Dunlop ◽  
Lindsay W. Victoria ◽  
Lauren Oberlin ◽  
Charles Lynch ◽  
...  
Keyword(s):  
Older Adults ◽  
White Matter ◽  
Functional Connectivity ◽  
Cognitive Control ◽  
Resting State ◽  
Structural Connectivity ◽  
Control Network ◽  
Cognitive Inhibition ◽  
Resting State Functional Connectivity ◽  
Cognitive Control Network

AbstractWhite matter hyperintensities (WMH) are linked to cognitive control; however, the structural and functional mechanisms are largely unknown. We investigated the relationship between WMH-associated disruptions of structural connectivity, resting state functional connectivity (RSFC), and cognitive control in older adults. Fifty-eight cognitively-healthy older adults completed cognitive control tasks, structural MRI, and resting state fMRI scans. We estimated inferred, WMH-related disruptions in structural connectivity between pairs of subcortical and cortical regions by overlaying each participant’s WMH mask on a normative tractogram dataset. For region-pairs in which structural disconnection was associated with cognitive control, we calculated RSFC between nodes in those same regions. WMH-related structural disconnection and RSFC in the cognitive control network and default mode network were both associated with poorer cognitive inhibition. These regionally-specific, WMH-related structural and functional changes were more strongly associated with cognitive inhibition compared to standard rating of WMH burden. Our findings highlight the role of circuit-level disruptions to the cognitive control network and default mode network that are related to WMH and impact cognitive control in aging.

scholarly journals Benchmarking functional connectivity by the structure and geometry of the human brain

2021 ◽  
Author(s):  
Zhen-Qi Liu ◽  
Richard F. Betzel ◽  
Bratislav Misic
Keyword(s):  
Functional Connectivity ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Underlying Structure ◽  
Functional Connections ◽  
Co Activation ◽  
Natural Frame ◽  
Structural Connections ◽  
Electrical Impulses ◽  
The Brain

The brain’s structural connectivity supports the propagation of electrical impulses, manifesting as patterns of co-activation, termed functional connectivity. Functional connectivity emerges from the underlying sparse structural connections, particularly through poly-synaptic communication. As a result, functional connections between brain regions without direct structural links are numerous, but their organization is not completely understood. Here we investigate the organization of functional connections without direct structural links. We develop a simple, data-driven method to benchmark functional connections with respect to their underlying structural and geometric embedding. We then use this method to re-weigh and re-express functional connectivity. We find evidence of unexpectedly strong functional connectivity within the canonical intrinsic networks of the brain. We also find unexpectedly strong functional connectivity at the apex of the unimodal-transmodal hierarchy. Our results suggest that both phenomena – functional modules and functional hierarchies – emerge from functional interactions that transcend the underlying structure and geometry. These findings also potentially explain recent reports that structural and functional connectivity gradually diverge in transmodal cortex. Collectively, we show how structural connectivity and geometry can be used as a natural frame of reference with which to study functional connectivity patterns in the brain.

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