Article in Science advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Enida GjoniDepartment of Neurobiology, Center for Neural Circuits and Behavior, Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0003-4028-9294
Ram Dyuthi SristiDepartment of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0002-3234-9413
Haixin LiuDepartment of Neurobiology, Center for Neural Circuits and Behavior, Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.
Shahar DrorDepartment of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA.
Xinlei LinDepartment of Neurobiology, Center for Neural Circuits and Behavior, Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.
Keelin O'NeilDepartment of Neurobiology, Center for Neural Circuits and Behavior, Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0002-7920-9653
Oscar M ArroyoDepartment of Neurobiology, Center for Neural Circuits and Behavior, Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0002-6025-9255
Sun Woo HongDepartment of Neurobiology, Center for Neural Circuits and Behavior, Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.ORCID 0009-0002-5104-0670
Hannah KimDepartment of Neurobiology, Center for Neural Circuits and Behavior, Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.
Jeffrey LiuDepartment of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA.ORCID 0009-0007-6371-4982
Sonja BlumenstockDepartment of Neurobiology, Center for Neural Circuits and Behavior, Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0002-8124-3295
Byungkook LimDepartment of Neurobiology, Center for Neural Circuits and Behavior, Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0002-3766-5415
Gal MishneDepartment of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0002-5287-3626
Takaki KomiyamaDepartment of Neurobiology, Center for Neural Circuits and Behavior, Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.ORCID 0000-0001-9609-4600
Funding
Cortical Control of Motor LearningR01NS091010 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KOMIYAMA, TAKAKI · 2015 to 2024
$3.7M
Deconstructing Functional Circuits of Motor Cortex During Motor Learning - Microscope Repair Administrative SupplementR01NS125298 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Takaki Komiyama · 2022 to 2026
$2.8M
Cortical plasticity during reinforcement learning - Diversity SupplementR01MH128746 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Takaki Komiyama · 2022 to 2026
$2.3M
Context-dependent plasticity of adult-born neuronsR01DC018545 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KOMIYAMA, TAKAKI · 2020 to 2024
Coordinated motor behavior emerges from information flow across brain regions. How long-range inputs drive cell type-specific activity within motor circuits remains unclear. The dorsolateral striatum (DLS) contains direct- and indirect-pathway medium spiny neurons (dMSNs and iMSNs) with distinct roles in movement control. In mice performing skilled locomotion, we recorded from dMSNs, iMSNs, and their cortical and thalamic inputs identified by monosynaptic rabies tracing. A recurrent neural network (RNN) classifier and clustering analysis revealed functionally heterogeneous subpopulations in each population, with dMSNs preferentially activated at movement onset and offset, and iMSNs during execution. Cortical and thalamic inputs were preferentially activated during onset/offset and execution, respectively, though dMSN- and iMSN-projecting neurons in each region showed similar patterns. Locomotion phase-specific rhythmic activity was found in a subset of thalamic dMSN-projecting neurons and dMSNs. Cortex or thalamus inactivation reduced MSN activity. These findings suggest that corticostriatal and thalamostriatal inputs convey complementary motor signals via shared and cell type-specific pathways.
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Complementary cortical and thalamic contributions to cell type-specific striatal activity dynamics during movement. · full record | OpenQuestion