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

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

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

Neurorehabilitation and Neural Repair ◽

10.1177/1545968313508227 ◽

2013 ◽

Vol 28 (3) ◽

pp. 260-272 ◽

Cited By ~ 12

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.

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Predicting MEG resting-state functional connectivity from microstructural information

Network Neuroscience ◽

10.1162/netn_a_00187 ◽

2021 ◽

pp. 1-42

Author(s):

Eirini Messaritaki ◽

Sonya Foley ◽

Simona Schiavi ◽

Lorenzo Magazzini ◽

Bethany Routley ◽

...

Keyword(s):

Functional Connectivity ◽

Fractional Anisotropy ◽

Shortest Path ◽

Resting State ◽

Path Length ◽

Structural Connectivity ◽

Imaging Data ◽

Resting State Functional Connectivity ◽

Brain Microstructure ◽

Functional Mechanisms

Understanding how human brain microstructure influences functional connectivity is an important endeavor. In this work, magnetic resonance imaging data from ninety healthy participants were used to calculate structural connectivity matrices using the streamline count, fractional anisotropy, radial diffusivity and a myelin measure (derived from multi-component relaxometry) to assign connection strength. Unweighted binarized structural connectivity matrices were also constructed. Magnetoencephalography resting-state data from those participants were used to calculate functional connectivity matrices, via correlations of the Hilbert envelopes of beamformer timeseries in the delta, theta, alpha and beta frequency bands. Non-negative matrix factorization was performed to identify the components of the functional connectivity. Shortest-path-length and search-information analyses of the structural connectomes were used to predict functional connectivity patterns for each participant. The microstructure-informed algorithms predicted the components of the functional connectivity more accurately than they predicted the total functional connectivity. This provides a methodology to understand functional mechanisms better. The shortest-path-length algorithm exhibited the highest prediction accuracy. Of the weights of the structural connectivity matrices, the streamline count and the myelin measure gave the most accurate predictions, while the fractional anisotropy performed poorly. Overall, different structural metrics paint very different pictures of the structural connectome and its relationship to functional connectivity.

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White Matter Structural Connectivity Is Not Correlated to Cortical Resting-State Functional Connectivity over the Healthy Adult Lifespan

Frontiers in Aging Neuroscience ◽

10.3389/fnagi.2017.00144 ◽

2017 ◽

Vol 9 ◽

Cited By ~ 28

Author(s):

Adrian Tsang ◽

Catherine A. Lebel ◽

Signe L. Bray ◽

Bradley G. Goodyear ◽

Moiz Hafeez ◽

...

Keyword(s):

White Matter ◽

Functional Connectivity ◽

Resting State ◽

Healthy Adult ◽

Structural Connectivity ◽

Resting State Functional Connectivity ◽

Adult Lifespan

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

10.1101/2020.04.14.039065 ◽

2020 ◽

Cited By ~ 1

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.

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Predicting MEG resting-state functional connectivity using microstructural information

10.1101/2020.09.15.298307 ◽

2020 ◽

Cited By ~ 2

Author(s):

Eirini Messaritaki ◽

Sonya Foley ◽

Simona Schiavi ◽

Lorenzo Magazzini ◽

Bethany Routley ◽

...

Keyword(s):

Functional Connectivity ◽

Fractional Anisotropy ◽

Shortest Path ◽

Resting State ◽

Path Length ◽

Structural Connectivity ◽

Imaging Data ◽

Resting State Functional Connectivity ◽

Brain Microstructure ◽

Structural Metrics

AbstractUnderstanding how human brain microstructure influences functional connectivity is an important endeavor. In this work, magnetic resonance imaging data from ninety healthy participants were used to calculate structural connectivity matrices using the streamline count, fractional anisotropy, radial diffusivity and a myelin measure (derived from multi-component relaxometry) to assign connection strength. Unweighted binarized structural connectivity matrices were also constructed. Magnetoencephalography resting-state data from those participants were used to calculate functional connectivity matrices, via correlations of the Hilbert envelopes of beamformer timeseries at four frequency bands: delta (1 − 4 Hz), theta (3 − 8 Hz), alpha (8 − 13 Hz) and beta (13 − 30 Hz). Non-negative matrix factorization was performed to identify the components of the functional connectivity. Shortest-path-length and search-information analyses of the structural connectomes were used to predict functional connectivity patterns for each participant.The microstructurally-informed algorithms predicted the components of the functional connectivity more accurately than they predicted the total functional connectivity. The shortest-path-length algorithm exhibited the highest prediction accuracy. Of the weights of the structural connectivity matrices, the streamline count and the myelin measure gave the most accurate predictions, while the fractional anisotropy performed poorly. Different structural metrics paint very different pictures of the structural connectome and its relationship to functional connectivity.

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