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The impact of Parkinson's disease on striatal network connectivity and corticostriatal drive: An in silico study
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST). KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0001-8210-8709
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematics (Div.).ORCID iD: 0000-0001-6007-9273
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST).ORCID iD: 0000-0002-9302-0750
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST). Karolinska Inst, Dept Neurosci, Stockholm, Sweden.ORCID iD: 0000-0003-3994-0799
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2024 (English)In: Network Neuroscience, ISSN 2472-1751, Vol. 8, no 4, p. 1149-1172Article in journal (Refereed) Published
Abstract [en]

This in silico study predicts the impact that the single-cell neuronal morphological alterations will have on the striatal microcircuit connectivity. We find that the richness in the topological striatal motifs is significantly reduced in Parkinson's disease (PD), highlighting that just measuring the pairwise connectivity between neurons gives an incomplete description of network connectivity. Moreover, we predict how the resulting electrophysiological changes of striatal projection neuron excitability together with their reduced number of dendritic branches affect their response to the glutamatergic drive from the cortex and thalamus. We find that the effective glutamatergic drive is likely significantly increased in PD, in accordance with the hyperglutamatergic hypothesis.

Place, publisher, year, edition, pages
MIT Press , 2024. Vol. 8, no 4, p. 1149-1172
Keywords [en]
Parkinson's disease, Striatum, Computational modeling, Topological data analysis, Directed cliques, Network higher order connectivity, Neuronal degeneration model
National Category
Neurosciences
Identifiers
URN: urn:nbn:se:kth:diva-359481DOI: 10.1162/netn_a_00394ISI: 001381061600014PubMedID: 39735495Scopus ID: 2-s2.0-105000619120OAI: oai:DiVA.org:kth-359481DiVA, id: diva2:1935118
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Not duplicate with DiVA 1813694

QC 20250206

Available from: 2025-02-06 Created: 2025-02-06 Last updated: 2025-04-03Bibliographically approved

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Carannante, IlariaScolamiero, MartinaHjorth, J. J. JohannesKozlov, AlexanderBekkouche, BoGuo, LihaoKumar, ArvindChachólski, WojciechHellgren Kotaleski, Jeanette

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Carannante, IlariaScolamiero, MartinaHjorth, J. J. JohannesKozlov, AlexanderBekkouche, BoGuo, LihaoKumar, ArvindChachólski, WojciechHellgren Kotaleski, Jeanette
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Computational Science and Technology (CST)Science for Life Laboratory, SciLifeLabMathematics (Div.)
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