Journal Article

FZJ-2020-02668

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Joint Multi-modal Parcellation of the Human Striatum: Functions and Clinical Relevance

Liu, X.FZJ* ; Eickhoff, S. B.FZJ* ; Hoffstaedter, F.FZJ* ; Genon, S.FZJ* ; Caspers, S.FZJ* ; Reetz, K.FZJ* ; Dogan, I. ; Eickhoff, C. R.FZJ* ; Chen, J.FZJ* ; Caspers, J. ; Reuter, N.FZJ* ; Mathys, C. ; Aleman, A. ; Jardri, R. ; Riedl, V. ; Sommer, I. E. ; Patil, K. R. (Corresponding author)FZJ*

2020
Tongfang Knowledge Network Technology Co., Ltd. Beijing

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Please use a persistent id in citations: http://hdl.handle.net/2128/26169  doi:10.1007/s12264-020-00543-1

Abstract: The human striatum is essential for both low- and high-level functions and has been implicated in the pathophysiology of various prevalent disorders, including Parkinson's disease (PD) and schizophrenia (SCZ). It is known to consist of structurally and functionally divergent subdivisions. However, previous parcellations are based on a single neuroimaging modality, leaving the extent of the multi-modal organization of the striatum unknown. Here, we investigated the organization of the striatum across three modalities-resting-state functional connectivity, probabilistic diffusion tractography, and structural covariance-to provide a holistic convergent view of its structure and function. We found convergent clusters in the dorsal, dorsolateral, rostral, ventral, and caudal striatum. Functional characterization revealed the anterior striatum to be mainly associated with cognitive and emotional functions, while the caudal striatum was related to action execution. Interestingly, significant structural atrophy in the rostral and ventral striatum was common to both PD and SCZ, but atrophy in the dorsolateral striatum was specifically attributable to PD. Our study revealed a cross-modal convergent organization of the striatum, representing a fundamental topographical model that can be useful for investigating structural and functional variability in aging and in clinical conditions.

Note: This work was supported by the DeutscheForschungsgemeinschaft (GE 2835/1-1, EI 816/4-1), the HelmholtzPortfolio Theme ‘Supercomputing and Modelling for the HumanBrain’ and the European Union’s Horizon 2020 Research andInnovation Programme under Grant Agreement No. 785907 (HBPSGA2). We gratefully acknowledge financial support from the ChinaScholarship Council (201606750003)

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Contributing Institute(s):

1. Gehirn & Verhalten (INM-7)
2. Strukturelle und funktionelle Organisation des Gehirns (INM-1)

Research Program(s):

1. 571 - Connectivity and Activity (POF3-571) (POF3-571)
2. SMHB - Supercomputing and Modelling for the Human Brain (HGF-SMHB-2013-2017) (HGF-SMHB-2013-2017)
3. HBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907) (785907)

Appears in the scientific report 2020

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Database coverage:
; ; Allianz-Lizenz / DFG ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; DEAL Springer ; Essential Science Indicators ; IF < 5 ; JCR ; NCBI Molecular Biology Database ; Nationallizenz ; PubMed Central ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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