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Motif Analysis of Resting-state and Stimulus-driven fMRI Networks with Special Focus on Neurotransmitter-specific Subnetworks 2023

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Bildverarbeitung für die Medizin 2023 (BVM 2023)

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Abstract

Complex large scale brain networks can be broken down to small, repetitive building blocks, termed motifs. Here, motif-compositions were investigated in functional brain networks of different mouse models of A) resting state (RS) corresponding to brain function in absence of a specific task, and B) peripheral heat stimulation with warm and hot temperatures. The brain-wide networks obtained were decomposed to subnetworks of different neurotransmitters (NT): glutamate, acetylcholine, serotonin, dopamine, noradrenaline, substance P and α-CGRP based on expression data of neurotransmitters and their receptors from Allen Mouse Brain Atlas (ABA), a genome-wide, high-resolution database of gene expression. Those NT-specific subnetworks and their motif composition allow for deeper insight into specific brain functions.

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Correspondence to Drăgălina Dulea .

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© 2023 Der/die Autor(en), exklusiv lizenziert an Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature

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Dulea, D. et al. (2023). Motif Analysis of Resting-state and Stimulus-driven fMRI Networks with Special Focus on Neurotransmitter-specific Subnetworks 2023. In: Deserno, T.M., Handels, H., Maier, A., Maier-Hein, K., Palm, C., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2023. BVM 2023. Informatik aktuell. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-41657-7_59

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