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Brain lesions causing parkinsonism versus seizures map to opposite brain networks

Schaper; Frederic L W V J; Morton-Dutton, Mae; Pacheco-Barrios, Niels; Turner, Joseph I; Drew, William; Khosravani, Sanaz; Joutsa, Juho; Fox, Michael D

Brain lesions causing parkinsonism versus seizures map to opposite brain networks

Schaper
Frederic L W V J
Morton-Dutton, Mae
Pacheco-Barrios, Niels
Turner, Joseph I
Drew, William
Khosravani, Sanaz
Joutsa, Juho
Fox, Michael D
Katso/Avaa
fcae196.pdf (11.26Mb)
Lataukset: 

Oxford University Press
doi:10.1093/braincomms/fcae196
URI
https://academic.oup.com/braincomms/article/6/3/fcae196/7688123
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Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2025082791223
Tiivistelmä
Recent epidemiological studies propose an association between parkinsonism and seizures, but the direction of this association is unclear. Focal brain lesions causing new-onset parkinsonism versus seizures may provide a unique perspective on the causal relationship between the two symptoms and involved brain networks. We studied lesions causing parkinsonism versus lesions causing seizures and used the human connectome to identify their connected brain networks. Brain networks for parkinsonism and seizures were compared using spatial correlations on a group and individual lesion level. Lesions not associated with either symptom were used as controls. Lesion locations from 29 patients with parkinsonism were connected to a brain network with the opposite spatial topography (spatial r = -0.85) compared to 347 patients with lesions causing seizures. A similar inverse relationship was found when comparing the connections that were most specific on a group level (spatial r = -0.51) and on an individual lesion level (average spatial r = -0.042; P < 0.001). The substantia nigra was found to be most positively correlated to the parkinsonism network but most negatively correlated to the seizure network (spatial r > 0.8). Brain lesions causing parkinsonism versus seizures map to opposite brain networks, providing neuroanatomical insight into conflicting epidemiological evidence.
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