Integrating Striatal and Cortical Structural-Functional Architectures
Poster No:
1750
Submission Type:
Abstract Submission
Authors:
Jing Lou1, Kaixin Li2, Xiaohan Tian1, Junxing Xian1, Meng Wang1, Wenkun Lei1, Yuqing Sun3, Bing Liu1
Institutions:
1State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, Beijing, 2State Key Lab of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, Beijing, 3State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing,Beijing
First Author:
Jing Lou
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
Co-Author(s):
Kaixin Li
State Key Lab of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences
Beijing, Beijing
State Key Lab of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences
Beijing, Beijing
Xiaohan Tian
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
Junxing Xian
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
Meng Wang
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
Wenkun Lei
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
Yuqing Sun
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing,Beijing
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing,Beijing
Bing Liu
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
Introduction:
The cortico-striatal circuit, characterized by its complex structural and functional organization, serves as a conduit between multimodal systems implicated in both normal development and disease regulation. To examine this organizational framework in humans, we employed 3T diffusion-weighted imaging alongside resting-state functional MRI (fMRI) to derive multimodal gradients of cortico-striatal connectivity, thereby identifying three primary patterns of cortico-striatal organization. The first mode delineates a hierarchical gradient extending from sensorimotor regions to association regions. The second mode is predominantly associated with projections from the posterior cingulate cortex to the striatum and from the parietal cortex to the striatum, illustrating the functional specialization of cortico-striatal projection patterns. Finally, the third mode is associated with risk factors for psychiatric disorders. Collectively, this study elucidates the critical role of the cortico-striatal circuit in underpinning uniquely human behaviors and highlights its extensive involvement in brain function across both health and disorders.
Methods:
We analyzed 3T MRI datasets from 836 healthy subjects (ages 22-36) from the Human Connectome Project. The main steps included: 1) calculating striatal structural and functional connectopic maps (CMAPs), 2) assessing connectivity patterns between these maps and the neocortex, and 3) using a generalized linear regression model to examine the relationship between functional and structural striatal-cortical connectivity. We employed probabilistic fiber tracking to derive the structural connectivity matrix from striatal voxels to the cortex and calculated the striatum's functional connectivity with the neocortex. Subsequently, we extracted structural and functional similarity matrices within the striatum and conducted dimensionality reduction, yielding three main striatal structural and functional CMAPs. Pearson correlation analysis was performed between CMAPs and cortical connectivity matrices to identify striatum-neocortex connectivity patterns. Then, a linear regression model assessed the structural-functional relationship within these patterns.
Results:
The initial pattern delineates a hierarchical organization extending from sensorimotor regions to association areas, thereby elucidating the interrelationships among various functional regions of the brain within the cortico-striatal circuit. The subsequent pattern predominantly emphasizes the projection circuits between the posterior cingulate and striatum, as well as between the parietal cortex and striatum, thereby reflecting the functional specialization inherent in cortico-striatal projection patterns. Lastly, the third organizational axis demonstrates a correlation with genetic predispositions for mental disorders. In conclusion, the cortico-striatal architectures establish a connection between normal neurodevelopment and the genetic underpinnings of psychiatric disorders.
Conclusions:
The striatum hosts multiple representations of cortical connectivity, reflecting the multidimensional hierarchical structure of the cortico-striatal gradient. It reveals the extensive association between cortico-striatal connectivity and unique human behaviors, as well as brain function in health and disease, providing new insights into the widespread projection relationships between the striatum and the cortex.
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
Diffusion MRI Modeling and Analysis
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Anatomy and Functional Systems
Subcortical Structures 1
Novel Imaging Acquisition Methods:
Multi-Modal Imaging 2
Keywords:
Cortex
Modeling
MRI
Multivariate
Psychiatric
Somatosensory
Statistical Methods
Sub-Cortical
Tractography
White Matter
1|2Indicates the priority used for review
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[2] Cohen, M. X., Schoene-Bake, J. C., Elger, C. E., & Weber, B. (2009). Connectivity-based segregation of the human striatum predicts personality characteristics. Nature neuroscience, 12(1), 32–34. https://doi.org/10.1038/nn.2228
[3] Marquand, A. F., Haak, K. V., & Beckmann, C. F. (2017). Functional corticostriatal connection topographies predict goal directed behaviour in humans. Nature human behaviour, 1(8), 0146. https://doi.org/10.1038/s41562-017-0146
[4] Haber S. N. (2016). Corticostriatal circuitry. Dialogues in clinical neuroscience, 18(1), 7–21. https://doi.org/10.31887/DCNS.2016.18.1/shaber
[5] Thivierge, J. P., & Marcus, G. F. (2007). The topographic brain: from neural connectivity to cognition. Trends in neurosciences, 30(6), 251–259. https://doi.org/10.1016/j.tins.2007.04.004
[6] Huntenburg, J. M., Bazin, P. L., & Margulies, D. S. (2018). Large-Scale Gradients in Human Cortical Organization. Trends in cognitive sciences, 22(1), 21–31. https://doi.org/10.1016/j.tics.2017.11.002
[7] Jarbo, K., & Verstynen, T. D. (2015). Converging structural and functional connectivity of orbitofrontal, dorsolateral prefrontal, and posterior parietal cortex in the human striatum. The Journal of neuroscience : the official journal of the Society for Neuroscience, 35(9), 3865–3878. https://doi.org/10.1523/JNEUROSCI.2636-14.2015