Association of Network Connectivity via Resting State Functional MRI with Consciousness, Mortality, and Outcomes in Neonatal Acute Brain Injury

Background An accurate and comprehensive test of integrated brain network function is needed for neonates during the acute brain injury period to inform on morbidity. This retrospective cohort study aimed to assess whether integrated brain network function by resting state functional MRI, acquired during the acute period in neonates with brain injury, is associated with acute exam, neonatal mortality, and 5-month outcomes. Methods This study included 40 consecutive neonates with resting state functional MRI acquired 1-22 days after suspected brain insult from March 2018 to July 2019 at Phoenix Childrens Hospital. Acute period exam and test results were assigned ordinal scores based on severity as documented by respective treating specialists. Analyses (Fisher exact, Wilcoxon-rank sum test, ordinal/multinomial logistic regression) examined association of resting state networks with demographics, presentation, neurological exam, electroencephalogram, anatomical MRI, magnetic resonance spectroscopy, passive task functional MRI, and outcomes of discharge condition, outpatient development, motor tone, seizure, and mortality. Results Subjects had a mean (standard deviation) gestational age of 37.8 (2.6) weeks, a majority were male (63%), with diagnosis of hypoxic ischemic encephalopathy (68%). Other findings at birth included mild distress (48%), moderately abnormal neurological exam (33%), and consciousness characterized as awake but irritable (40%). Significant associations after multiple testing corrections were detected for resting state networks: basal ganglia with outpatient developmental delay (odds ratio [OR], 14.5; 99.4% confidence interval [CI], 2.00-105; P<.001) and motor tone/weakness (OR, 9.98; 99.4% CI, 1.72-57.9; P<.001); language/frontal-parietal network with discharge condition (OR, 5.13; 99.4% CI, 1.22-21.5; P=.002) and outpatient developmental delay (OR, 4.77; 99.4% CI, 1.21-18.7; P=.002); default mode network with discharge condition (OR, 3.72; 99.4% CI, 1.01-13.78; P=.006) and neurological exam (P=.002 (FE); OR, 11.8; 99.4% CI, 0.73-191; P=.01 (OLR)); seizure onset zone with motor tone/weakness (OR, 3.31; 99.4% CI, 1.08-10.1; P=.003). Resting state networks were not detected in only three neonates, who died prior to discharge. Conclusions This study provides level 3 evidence (OCEBM Levels of Evidence Working Group) that the degree of abnormality of resting state networks in neonatal acute brain injury is associated with acute exam and outcomes. Total lack of brain network detection was only found in patients who did not survive.

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GP.04 Network connectivity following a single unprovoked seizure using 7 Tesla resting-state fMRI

Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques ◽

10.1017/cjn.2017.63 ◽

2017 ◽

Vol 44 (S2) ◽

pp. S8-S8

Author(s):

KM Ikeda ◽

SM Mirsattari ◽

AR Khan ◽

I Johnsrude ◽

JG Burneo ◽

...

Keyword(s):

Functional Mri ◽

Resting State ◽

Network Connectivity ◽

Resting State Fmri ◽

Brain Network ◽

Clustering Coefficient ◽

7 Tesla ◽

Unprovoked Seizure ◽

Whole Brain ◽

Network Function

Background: Predicting epilepsy following a first seizure is difficult. Network abnormalities are observed in patients with epilepsy using resting-state functional MRI (rs-fMRI), which worsen with duration of epilepsy. We use rs-fMRI to identify network abnormalities in patients after a first seizure that can be used as a biomarker to predict development of epilepsy. Methods: Patients after a single, unprovoked seizure and age/sex matched healthy controls underwent 7 Tesla structural and resting-state functional MRI. Data were analyzed using graph theory measures. Patients were followed for development of epilepsy. Results: Nine patients and nine control subjects were analyzed. There were no differences in baseline characteristics. No patients developed epilepsy (average follow-up 3 months). No differences between groups occurred on a whole-brain network level. At a 20% threshold, significant differences occurred in the default mode network (DMN). Patients demonstrated an increased local efficiency (p=0.02) and clustering coefficient (p=0.04), and decreased path length (p=0.02) and betweenness centrality (p=0.02). Conclusions: No whole-brain network changes occur after a single unprovoked seizure. No patient has developed epilepsy suggesting this group does not have network alterations after a single seizure. In the DMN, the alterations noted indicate increased segregation of network function.

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Multifractal analysis of Resting State Networks in functional MRI

2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro ◽

10.1109/isbi.2011.5872448 ◽

2011 ◽

Cited By ~ 3

Author(s):

Philippe Ciuciu ◽

Gael Varoquaux ◽

Patrice Abry ◽

Moty Almog

Keyword(s):

Functional Mri ◽

Resting State ◽

Multifractal Analysis ◽

Resting State Networks

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Detecting functional connectivity disruptions in a translational pediatric traumatic brain injury porcine model using resting-state and task-based fMRI

Scientific Reports ◽

10.1038/s41598-021-91853-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Gregory Simchick ◽

Kelly M. Scheulin ◽

Wenwu Sun ◽

Sydney E. Sneed ◽

Madison M. Fagan ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Functional Connectivity ◽

Resting State ◽

Correlation Coefficients ◽

Brain Network ◽

Network Activity ◽

Anatomical Structures ◽

Healthy Control ◽

And Task

AbstractFunctional magnetic resonance imaging (fMRI) has significant potential to evaluate changes in brain network activity after traumatic brain injury (TBI) and enable early prognosis of potential functional (e.g., motor, cognitive, behavior) deficits. In this study, resting-state and task-based fMRI (rs- and tb-fMRI) were utilized to examine network changes in a pediatric porcine TBI model that has increased predictive potential in the development of novel therapies. rs- and tb-fMRI were performed one day post-TBI in piglets. Activation maps were generated using group independent component analysis (ICA) and sparse dictionary learning (sDL). Activation maps were compared to pig reference functional connectivity atlases and evaluated using Pearson spatial correlation coefficients and mean ratios. Nonparametric permutation analyses were used to determine significantly different activation areas between the TBI and healthy control groups. Significantly lower Pearson values and mean ratios were observed in the visual, executive control, and sensorimotor networks for TBI piglets compared to controls. Significant differences were also observed within several specific individual anatomical structures within each network. In conclusion, both rs- and tb-fMRI demonstrate the ability to detect functional connectivity disruptions in a translational TBI piglet model, and these disruptions can be traced to specific affected anatomical structures.

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Childhood Trauma Associated With Abnormal Resting-State Brain Network Connectivity in First-Episode Schizophrenia Patients

10.21203/rs.3.rs-73545/v1 ◽

2020 ◽

Author(s):

Xiangyun Long ◽

Jiaxin Wu ◽

Fei Liu ◽

Ansi Qi ◽

Nan Huang ◽

...

Keyword(s):

Childhood Trauma ◽

Resting State ◽

Network Connectivity ◽

Brain Network ◽

Traumatic Experiences ◽

First Episode ◽

Resting State Networks ◽

Attention Network ◽

Brain Network Connectivity ◽

First Episode Schizophrenia

Abstract Childhood trauma is a central risk factor for schizophrenia. We explored the correlation between early traumatic experiences and the functional connectivity of resting-state networks. This fMRI study included 28 first-episode schizophrenia patients and 27 healthy controls. In first-episode schizophrenia patients, higher levels of childhood trauma associated with abnormal connections of resting-state networks, and these anomalies distributed among task-positive networks (i.e., ventral attention network, dorsal-ventral attention network and frontal-parietal network), and sensory networks (i.e., visual network and auditory network). These findings mentioned that childhood traumatic experiences may impact resting-state network connectivity in adulthood, mainly involving systems related to attention and execution control.

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Increased soluble amyloid-beta causes early aberrant brain network hypersynchronisation in a mature-onset mouse model of amyloidosis

Acta Neuropathologica Communications ◽

10.1186/s40478-019-0810-7 ◽

2019 ◽

Vol 7 (1) ◽

Author(s):

Inès R. H. Ben-Nejma ◽

Aneta J. Keliris ◽

Jasmijn Daans ◽

Peter Ponsaerts ◽

Marleen Verhoye ◽

...

Keyword(s):

Mouse Model ◽

Postnatal Development ◽

Amyloid Beta ◽

Resting State ◽

Inflammatory Responses ◽

Ex Vivo ◽

Fold Increase ◽

Brain Network ◽

Resting State Networks ◽

The Impact

AbstractAlzheimer’s disease (AD) is the most common form of dementia in the elderly. According to the amyloid hypothesis, the accumulation and deposition of amyloid-beta (Aβ) peptides play a key role in AD. Soluble Aβ (sAβ) oligomers were shown to be involved in pathological hypersynchronisation of brain resting-state networks in different transgenic developmental-onset mouse models of amyloidosis. However, the impact of protein overexpression during brain postnatal development may cause additional phenotypes unrelated to AD. To address this concern, we investigated sAβ effects on functional resting-state networks in transgenic mature-onset amyloidosis Tet-Off APP (TG) mice. TG mice and control littermates were raised on doxycycline (DOX) diet from 3d up to 3 m of age to suppress transgenic Aβ production. Thereafter, longitudinal resting-state functional MRI was performed on a 9.4 T MR-system starting from week 0 (3 m old mice) up to 28w post DOX treatment. Ex-vivo immunohistochemistry and ELISA analysis was performed to assess the development of amyloid pathology. Functional Connectivity (FC) analysis demonstrated early abnormal hypersynchronisation in the TG mice compared to the controls at 8w post DOX treatment, particularly across regions of the default mode-like network, known to be affected in AD. Ex-vivo analyses performed at this time point confirmed a 20-fold increase in total sAβ levels preceding the apparition of Aβ plaques and inflammatory responses in the TG mice compared to the controls. On the contrary at week 28, TG mice showed an overall hypoconnectivity, coinciding with a widespread deposition of Aβ plaques in the brain. By preventing developmental influence of APP and/or sAβ during brain postnatal development, we demonstrated FC abnormalities potentially driven by sAβ neurotoxicity on resting-state neuronal networks in mature-induced TG mice. Thus, the Tet-Off APP mouse model could be a powerful tool while used as a mature-onset model to shed light into amyloidosis mechanisms in AD.

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Investigation of spectrally coherent resting-state networks using non-negative matrix factorization for functional MRI data

International Journal of Imaging Systems and Technology ◽

10.1002/ima.20276 ◽

2011 ◽

Vol 21 (2) ◽

pp. 211-222 ◽

Cited By ~ 16

Author(s):

Jong-Hwan Lee ◽

Ryuichiro Hashimoto ◽

Cynthia G. Wible ◽

Seung-Schik Yoo

Keyword(s):

Functional Mri ◽

Matrix Factorization ◽

Resting State ◽

Resting State Networks ◽

Non Negative Matrix Factorization

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Electrophysiological correlates of thalamocortical function in acute severe traumatic brain injury

10.1101/2021.09.08.21262992 ◽

2021 ◽

Author(s):

William H. Curley ◽

Yelena G. Bodien ◽

David W. Zhou ◽

Mary M. Conte ◽

Andrea S. Foulkes ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Severe Traumatic Brain Injury ◽

Resting State ◽

Chronic Phase ◽

Post Injury ◽

Network Function ◽

Power Spectral ◽

Level Of Consciousness ◽

Thalamocortical Network

Few reliable biomarkers of consciousness exist for patients with acute severe brain injury. Tools assaying the neural networks that modulate consciousness may allow for tracking of recovery. The mesocircuit model, and its instantiation as the ABCD framework, classifies resting-state EEG power spectral densities into categories reflecting widely separated levels of thalamocortical network function and correlates with outcome in post-cardiac arrest coma. We applied the ABCD framework to acute severe traumatic brain injury and tested four hypotheses: 1) EEG channel-level ABCD classifications are spatially heterogeneous and temporally variable; 2) ABCD classifications improve longitudinally, commensurate with the degree of behavioural recovery; 3) ABCD classifications correlate with behavioural level of consciousness; and 4) the Coma Recovery Scale-Revised arousal facilitation protocol improves EEG dynamics along the ABCD scale. In this longitudinal cohort study, we enrolled 20 patients with acute severe traumatic brain injury requiring intensive care and 16 healthy controls. Through visual inspection, channel-level spectra from resting-state EEG were classified based on spectral peaks within frequency bands defined by the ABCD framework: A = no peaks above delta (<4 Hz) range (complete thalamocortical disruption); B = theta (4-8 Hz) peak (severe thalamocortical disruption); C = theta and beta (13-24 Hz) peaks (moderate thalamocortical disruption); or D = alpha (8-13 Hz) and beta peaks (normal thalamocortical function). We assessed behavioural level of consciousness with the Coma Recovery Scale-Revised or neurological examination and, in 12 patients, performed repeat EEG and behavioural assessments at ≥6-months post-injury. Acutely, 95% of patients demonstrated D signals in at least one channel but exhibited heterogeneity in the proportion of different channel-level ABCD classifications (mean percent D signals: 37%, range: 0-90%). By contrast, healthy participants and patients at follow-up predominantly demonstrated signals corresponding to intact thalamocortical network function (mean percent D signals: 94%). In patients studied acutely, ABCD classifications improved after the Coma Recovery Scale-Revised arousal facilitation protocol (P<0.05), providing electrophysiological evidence for the effectiveness of this commonly performed technique. ABCD classification did not correspond with behavioural level of consciousness acutely, where patients demonstrated substantial within-session temporal variability in ABCD classifications. However, ABCD classification distinguished patients with and without command-following in the subacute-to-chronic phase of recovery (P<0.01). Patients also demonstrated significant longitudinal improvement in EEG dynamics along the ABCD scale (median change in D signals: 37%, P<0.05). These findings support the use of the ABCD framework to characterize channel-level EEG dynamics and track fluctuations in functional thalamocortical network integrity in spatial detail.

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Impact of anaesthesia on static and dynamic functional connectivity in mice

10.1101/2021.03.18.436098 ◽

2021 ◽

Author(s):

Tomokazu Tsurugizawa ◽

Daisuke Yoshimaru

Keyword(s):

Functional Connectivity ◽

Functional Mri ◽

Resting State ◽

Low Frequency ◽

Resting State Fmri ◽

Brain Network ◽

List Type ◽

Thalamic Nuclei ◽

Dynamic Functional Connectivity ◽

Subcortical Regions

AbstractA few studies have compared the static functional connectivity between awake and anaesthetized states in rodents by resting-state fMRI. However, impact of anaesthesia on static and dynamic fluctuations in functional connectivity has not been fully understood. Here, we developed a resting-state fMRI protocol to perform awake and anaesthetized functional MRI in the same mice. Static functional connectivity showed a widespread decrease under anaesthesia, such as when under isoflurane or a mixture of isoflurane and medetomidine. Several interhemispheric connections were key connections for anaesthetized condition from awake. Dynamic functional connectivity demonstrates the shift from frequent broad connections across the cortex, the hypothalamus, and the auditory-visual cortex to frequent local connections within the cortex only. Fractional amplitude of low frequency fluctuation in the thalamic nuclei decreased under both anaesthesia. These results indicate that typical anaesthetics for functional MRI alters the spatiotemporal profile of the dynamic brain network in subcortical regions, including the thalamic nuclei and limbic system.HighlightsResting-state fMRI was compared between awake and anaesthetized in the same mice.Anaesthesia induced a widespread decrease of static functional connectivity.Anaesthesia strengthened local connections within the cortex.fALFF in the thalamus was decreased by anaesthesia.

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Brain Resting State Functional Networks in Infants with Prenatal Opioid Exposure

Proceedings of IMPRS ◽

10.18060/25736 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Nicole Steinhardt ◽

Ramana Vishnubhotla ◽

Yi Zhao ◽

David M. Haas ◽

Gregory M. Sokol ◽

...

Keyword(s):

Functional Connectivity ◽

Functional Mri ◽

Gestational Age ◽

Resting State ◽

Brain Regions ◽

Brain Network ◽

Anterior Cingulate ◽

Global Network ◽

Neurodevelopmental Outcomes ◽

Distinct Component

Purpose: Infants of mothers with opioid and substance use can present with postnatal withdrawal symptoms and are at risk of poor neurodevelopmental outcomes in later childhood. Identifying methods to evaluate the consequences of substance exposure on the developing brain can help initiate proactive therapies to improve outcomes for opioid-exposed neonates. Additionally, early brain imaging in infancy has the potential to identify early brain developmental alterations that could prognosticate neurodevelopmental outcomes in these children. In this study, we aim to identify differences in global brain network connectivity in infants with prenatal opioid exposure compared to healthy control infants, using resting-state functional MRI performed at less than 2 months completed gestational age. Materials and Methods: In this prospective, IRB-approved study, we recruited 20 infants with prenatal opioid exposure and 20 healthy, opioid naïve infants. Anatomic imaging and resting-state functional MRI were performed at less than 48 weeks corrected gestational age, and rs-fMRI images were co-registered to the UNC neonate brain template and 90 anatomic atlas-labelled regions. Covariate Assisted Principal (CAP) regression was performed to identify brain network functional connectivity that was significantly different among infants with prenatal opioid exposure compared to healthy neonates. Results: Of the 5 significantly different CAP components identified, the most distinct component (CAP5, p= 3.86 x 10-6) spanned several brain regions, including the right inferior temporal gyrus, bilateral Hesch’s gyrus, left thalamus, left supramarginal gyrus, left inferior parietal lobule, left superior parietal gyrus, right anterior cingulate gyrus, right gyrus rectus, left supplementary motor area, and left pars triangularis. Functional connectivity in this network was lower in the infants with prenatal opioid exposure compared to non-opioid exposed infants. Conclusion: This study demonstrates global network alterations in infants with prenatal opioid exposure compared to non-opioid exposed infants. Future studies should be aimed at identifying clinical significance of this altered connectivity.

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