journal article·2026-02Open access

Behavior‐ and Cell Type‐Specific Cortico‐Striatal Decoupling in a Parkinson's Disease‐Like Mouse Model

Xu‐Ran Yao, Yang Liu, Wei‐Tong Zheng, Mao‐Qing Huang, Kai‐Wen He

Advanced Science· Volume 13· Issue 10

Abstract

ABSTRACT Inter‐brain region activity coupling is essential for enabling coordinated neural communication, facilitating complex brain processes including motor behaviors. In Parkinson's Disease (PD) patients, cortico‐striatal decoupling is widely reported while its onset and cellular mechanism remain largely unclear. Using dual‐site fiber photometry and Cre transgenic mouse lines, we examined activity coordination between the primary motor (M1) cortex and dorsal striatum (cortico‐striatal coupling) with cell‐type resolution. This method identifies motor behavior‐specific coupling patterns with different contributions from striatal D1R‐ and D2R‐expressing medium spiny neurons (MSNs). In an α‐synuclein preformed fibrils (PFF) induced PD‐like mouse model, cortico‐striatal coupling associated with digging behavior is selectively disrupted as early as two months post‐induction, whose progressive deterioration correlates with later‐onset behavioral deficits. Optogenetic disruption or enhancement of cortico‐striatal coupling is sufficient to induce digging deficits in wild‐type mice or rescue such deficits in PFF‐injected mice, respectively. Furthermore, such decoupling is mainly mediated by impaired D1R MSNs, which can be rescued by D1 receptor activation or L‐DOPA. These findings demonstrate that early‐onset, behavior‐ and cell type‐specific cortico‐striatal decoupling emerges early during the development of PD‐like symptoms.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Neurological disorders and treatments · Transcranial Magnetic Stimulation Studies · Parkinson's Disease Mechanisms and Treatments

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Interdisciplinary Research Center on Biology and Chemistry Shanghai Institute of Organic Chemistry Chinese Academy of Sciences Shanghai China

University of Chinese Academy of Sciences Beijing China

Shanghai Key Laboratory of Aging Studies Shanghai China

Funding

National Natural Science Foundation of China · Science and Technology Commission of Shanghai Municipality

References (86)

Show source-provided references
1. 10.1016/j.conb.2016.02.00510.1016/j.conb.2016.02.005 ↗
2. 10.1016/j.conb.2010.08.02210.1016/j.conb.2010.08.022 ↗
3. 10.7554/eLife.6430310.7554/eLife.64303 ↗
4. 10.7554/eLife.0942310.7554/eLife.09423 ↗
5. 10.1038/s41593‐019‐0407‐210.1038/s41593‐019‐0407‐2 ↗
6. 10.1016/S0140‐6736(14)61393‐310.1016/S0140‐6736(14)61393‐3 ↗
7. 10.1111/jnc.1369110.1111/jnc.13691 ↗
8. 10.1186/s40035‐016‐0066‐010.1186/s40035‐016‐0066‐0 ↗
9. 10.3233/JPD‐19159210.3233/JPD‐191592 ↗
10. 10.1002/mdc3.1273010.1002/mdc3.12730 ↗
11. 10.1016/j.nicl.2020.10225210.1016/j.nicl.2020.102252 ↗
12. 10.3389/fneur.2021.72029310.3389/fneur.2021.720293 ↗
13. 10.1016/j.nicl.2018.01.01510.1016/j.nicl.2018.01.015 ↗
14. 10.1016/j.neulet.2012.02.09510.1016/j.neulet.2012.02.095 ↗
15. 10.1016/B978-0-12-815950-7.00025-410.1016/B978-0-12-815950-7.00025-4 ↗
16. 10.1038/nn.310010.1038/nn.3100 ↗
17. 10.1016/j.tins.2007.03.00810.1016/j.tins.2007.03.008 ↗
18. 10.1016/j.cell.2016.06.03210.1016/j.cell.2016.06.032 ↗
19. 10.1038/nn.363210.1038/nn.3632 ↗
20. 10.1016/j.tins.2024.11.00310.1016/j.tins.2024.11.003 ↗
21. 10.1002/jnr.2451910.1002/jnr.24519 ↗
22. 10.1523/JNEUROSCI.0658‐17.201710.1523/JNEUROSCI.0658‐17.2017 ↗
23. 10.1016/j.neuron.2017.05.00410.1016/j.neuron.2017.05.004 ↗
24. 10.1523/JNEUROSCI.4439‐05.200610.1523/JNEUROSCI.4439‐05.2006 ↗
25. 10.1016/j.neuron.2015.12.03810.1016/j.neuron.2015.12.038 ↗
26. 10.1038/s41586‐018‐0090‐610.1038/s41586‐018‐0090‐6 ↗
27. 10.1016/j.celrep.2018.05.05910.1016/j.celrep.2018.05.059 ↗
28. 10.1016/S0140‐6736(21)00218‐X10.1016/S0140‐6736(21)00218‐X ↗
29. 10.1126/science.122715710.1126/science.1227157 ↗
30. 10.1073/pnas.201243511810.1073/pnas.2012435118 ↗
31. 10.1038/s41467-025-56737-610.1038/s41467-025-56737-6 ↗
32. 10.1016/j.physbeh.2007.05.04710.1016/j.physbeh.2007.05.047 ↗
33. 10.1159/00036491310.1159/000364913 ↗
34. 10.3174/ajnr.A326310.3174/ajnr.A3263 ↗
35. 10.1016/j.neuron.2023.09.00610.1016/j.neuron.2023.09.006 ↗
36. 10.1038/ncomms531510.1038/ncomms5315 ↗
37. 10.1016/B978-0-12-802206-1.00007-610.1016/B978-0-12-802206-1.00007-6 ↗
38. 10.1038/nature1184610.1038/nature11846 ↗
39. 10.1038/s41467‐017‐02817‐110.1038/s41467‐017‐02817‐1 ↗
40. 10.1002/hbm.2270110.1002/hbm.22701 ↗
41. 10.1093/cercor/bhy25910.1093/cercor/bhy259 ↗
42. 10.1073/pnas.201243511810.1073/pnas.2012435118 ↗
43. 10.1038/s41593‐019‐0457‐510.1038/s41593‐019‐0457‐5 ↗
44. 10.1016/j.neuron.2023.12.01710.1016/j.neuron.2023.12.017 ↗
45. 10.1016/j.neuron.2019.03.00410.1016/j.neuron.2019.03.004 ↗
46. 10.1038/s41467‐020‐15352‐310.1038/s41467‐020‐15352‐3 ↗
47. 10.1371/journal.pone.020259710.1371/journal.pone.0202597 ↗
48. 10.1016/j.expneurol.2016.10.00510.1016/j.expneurol.2016.10.005 ↗
49. 10.3389/fnins.2019.0061110.3389/fnins.2019.00611 ↗
50. 10.1038/3506755010.1038/35067550 ↗
51. 10.1146/annurev‐neuro‐071714‐03411110.1146/annurev‐neuro‐071714‐034111 ↗
52. 10.1002/mds.2103310.1002/mds.21033 ↗
53. 10.1016/j.tics.2010.02.00110.1016/j.tics.2010.02.001 ↗
54. 10.1146/annurev‐neuro‐072116‐03103310.1146/annurev‐neuro‐072116‐031033 ↗
55. 10.1016/j.conb.2017.10.02310.1016/j.conb.2017.10.023 ↗
56. 10.1016/j.celrep.2021.10984710.1016/j.celrep.2021.109847 ↗
57. 10.1073/pnas.190171211610.1073/pnas.1901712116 ↗
58. 10.15252/embj.202211130410.15252/embj.2022111304 ↗
59. 10.1016/j.neuron.2017.06.01910.1016/j.neuron.2017.06.019 ↗
60. 10.1126/science.125526310.1126/science.1255263 ↗
61. 10.1016/j.neuron.2017.09.01910.1016/j.neuron.2017.09.019 ↗
62. 10.1523/JNEUROSCI.5027‐04.200510.1523/JNEUROSCI.5027‐04.2005 ↗
63. 10.1016/j.tins.2012.06.00810.1016/j.tins.2012.06.008 ↗
64. 10.1016/j.bbr.2017.12.01810.1016/j.bbr.2017.12.018 ↗
65. 10.1152/jn.00754.200110.1152/jn.00754.2001 ↗
66. 10.1523/JNEUROSCI.3366‐04.200410.1523/JNEUROSCI.3366‐04.2004 ↗
67. 10.1016/j.bbr.2016.02.02310.1016/j.bbr.2016.02.023 ↗
68. 10.1016/j.jneumeth.2012.12.02210.1016/j.jneumeth.2012.12.022 ↗
69. 10.1007/BF0087351710.1007/BF00873517 ↗
70. 10.1002/mds.2936210.1002/mds.29362 ↗
71. 10.1523/JNEUROSCI.0492‐15.201610.1523/JNEUROSCI.0492‐15.2016 ↗
72. 10.1016/j.neuron.2024.12.02410.1016/j.neuron.2024.12.024 ↗
73. 10.1038/s41467‐021‐26275‐y10.1038/s41467‐021‐26275‐y ↗
74. 10.1007/s00429‐014‐0749‐110.1007/s00429‐014‐0749‐1 ↗
75. 10.1016/j.jns.2016.08.02810.1016/j.jns.2016.08.028 ↗
76. 10.1016/j.neuroimage.2010.11.07410.1016/j.neuroimage.2010.11.074 ↗
77. 10.3389/fneur.2014.0018010.3389/fneur.2014.00180 ↗
78. 10.1093/cercor/bhu13510.1093/cercor/bhu135 ↗
79. 10.1016/j.neurobiolaging.2013.08.01810.1016/j.neurobiolaging.2013.08.018 ↗
80. 10.1007/s12264‐017‐0174‐610.1007/s12264‐017‐0174‐6 ↗
81. 10.5665/sleep.322210.5665/sleep.3222 ↗
82. 10.1038/s44220-024-00259-510.1038/s44220-024-00259-5 ↗
83. 10.3390/jpm1002003410.3390/jpm10020034 ↗
84. 10.1002/ana.2148110.1002/ana.21481 ↗
85. 10.1016/j.cell.2023.10.00410.1016/j.cell.2023.10.004 ↗
86. 10.1038/nn.428710.1038/nn.4287 ↗