It was recently suggested that in brain disorders neuronal alterations does not occur randomly, but tend to form patterns that resemble those of cerebral connectivity. Following this hypothesis, we studied the network formed by co-altered brain regions in patients with chronic pain. We used a meta-analytical network approach in order to: i) find out whether the neuronal alterations distribute randomly across the brain; ii) find out (in the case of a non-random pattern of distribution) whether a disease-specific pattern of brain co-alterations can be identified and characterized in terms of altered areas (nodes) and propagation links between them (edges); iii) verify whether the co-alteration pattern overlaps with the pattern of functional connectivity; iv) describe the topological properties of the co-alteration network and identify the highly connected nodes that are supposed to have a pre-eminent role in the diffusion timing of neuronal alterations across the brain. Our results indicate that: i) gray matter (GM) alterations do not occur randomly; ii) a symptom-related pattern of structural co-alterations can be identified for chronic pain; iii) this co-alteration pattern resembles the pattern of brain functional connectivity; iv) within the co-alteration network a set of highly connected nodes can be identified. This study provides further support to the hypothesis that neuronal alterations may spread according to the logic of a network-like diffusion suggesting that this type of distribution may also apply to chronic pain.

How do morphological alterations caused by chronic pain distribute across the brain? A meta-analytic co-alteration study

Tatu, Karina;Costa, Tommaso;Nani, Andrea;Diano, Matteo;Cauda, Franco
2018

Abstract

It was recently suggested that in brain disorders neuronal alterations does not occur randomly, but tend to form patterns that resemble those of cerebral connectivity. Following this hypothesis, we studied the network formed by co-altered brain regions in patients with chronic pain. We used a meta-analytical network approach in order to: i) find out whether the neuronal alterations distribute randomly across the brain; ii) find out (in the case of a non-random pattern of distribution) whether a disease-specific pattern of brain co-alterations can be identified and characterized in terms of altered areas (nodes) and propagation links between them (edges); iii) verify whether the co-alteration pattern overlaps with the pattern of functional connectivity; iv) describe the topological properties of the co-alteration network and identify the highly connected nodes that are supposed to have a pre-eminent role in the diffusion timing of neuronal alterations across the brain. Our results indicate that: i) gray matter (GM) alterations do not occur randomly; ii) a symptom-related pattern of structural co-alterations can be identified for chronic pain; iii) this co-alteration pattern resembles the pattern of brain functional connectivity; iv) within the co-alteration network a set of highly connected nodes can be identified. This study provides further support to the hypothesis that neuronal alterations may spread according to the logic of a network-like diffusion suggesting that this type of distribution may also apply to chronic pain.
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http://www.journals.elsevier.com/neuroimage-clinical/
Chronic pain; Co-alteration network; Network analysis; Neuronal alterations; Pathoconnectomics; Voxel-based morphometry; Brain; Chronic Pain; Humans; Magnetic Resonance Imaging; Nerve Net; Neuronal Plasticity; Radiology, Nuclear Medicine and Imaging; Neurology; Neurology (clinical); Cognitive Neuroscience
Tatu, Karina; Costa, Tommaso; Nani, Andrea; Diano, Matteo; Quarta, Danilo G.; Duca, Sergio; Apkarian, A. Vania; Fox, Peter T.; Cauda, Franco
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/1689720
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