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Eigenvector centrality mapping and seed-based analysis of resting state fMRI during acute brainstem-coma recovery in the rat

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Pais,  P
Research Group Translational Neuroimaging and Neural Control, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Jiang,  Y
Research Group Translational Neuroimaging and Neural Control, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Stelzer,  J
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Yu,  X
Research Group Translational Neuroimaging and Neural Control, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Pais, P., Edlow, B., Jiang, Y., Stelzer, J., Zou, M., & Yu, X. (2018). Eigenvector centrality mapping and seed-based analysis of resting state fMRI during acute brainstem-coma recovery in the rat. In 13th Annual Meeting of the European Society for Molecular Imaging (EMIM 2018).


Cite as: https://hdl.handle.net/21.11116/0000-0001-8352-E
Abstract
Introduction
Despite the known association between brainstem lesions and coma, a circuit-based understanding of coma pathogenesis and mechanisms of recovery is lacking1. We recently developed a model of coma in the rat with focal injury to the brainstem, which allows investigating the neural mechanisms of coma emergence and recovery2. Resting state functional MRI (rs-fMRI) experiments along coma evolution in the rat provided evidence for an acute recovery mechanism by which subcortical arousal centers outside the brainstem reactivate the cerebral cortex.
Methods
rs-fMRI scans were acquired during the first 8 hours post-coma using a 3D EPI sequence (TE, 12.5 ms; TR, 1s; matrix size, 48x48x32; resolution, 400x400x600 µm; 925 TRs) on a 14.1 T/26 cm magnet interfaced to an Avance III console. Pre-processing was performed in AFNI3 and Lipsia4. For each rs-fMRI scan, a voxel-wise map of eigenvector values was computed (eigenvector centrality map), indicating the importance of the respective voxel within the network, followed by least squares fit regression of the eigenvector values over the temporal succession. This resulted in a certain slope, informative of the increase or decrease in connectivity at a given voxel of the brain (Fig.1). Additionally, seed-based analysis was performed by calculating the Pearson's correlation coefficient between regions.
Results/Discussion
The eigenvector centrality mapping-based whole brain functional connectivity analysis showed increases along the acute recovery from coma in thalamus, basal forebrain and basal ganglia (Fig.1). Additionally, seed-based analysis revealed higher correlations along the post-coma period between the central and reticular thalamus, striatum, globus pallidus and the nuclei in the basal forebrain (Fig.2). Interestingly, the time courses of these nuclei increased their correlation with those in cingulate and somatosensory cortex only after 4 hours post-coma (Fig.2). Concurrent electrophysiology and behavioral assessment in the rats demonstrated recovery of the neurological function during the period of study. This result provides evidence for the participation of the thalamic-basal forebrain-basal ganglia network in recovery of consciousness during acute recovery from coma, a time window that is not accessible in the clinical practice for systematic study of the human brain function.
Conclusions
The convergent results from whole brain and seed-based fMRI analysis of connectivity highly suggest a potential role for the basal forebrain-basal ganglia-thalamocortical network in the initial phase of restoration of consciousness after brainstem injury. This study further verifies the applicability of the rat brainstem coma model to investigate brain dynamics during the acute phase of coma.