Evidence map›Paper›PMID 42000729›Full record

ArticleNature communications2026

Integrating optogenetic fMRI and spatial transcriptomics to reveal circuit-specific gene signatures in fronto- and hippo-thalamic networks.

Changjiang Zhang, Yijuan Zou, Liangchen Zhuo, Xiya Liu, Suijuan Zhong, Chonghai Yin, Mayuqing Li, Mengdi Wang, Wei Wang, Xin Zhou and 7 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Changjiang Zhang *State Key Laboratory of Cognitive Science and Mental Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.ORCID 0000-0003-3587-3496
Yijuan Zou *Changping Laboratory, Beijing, China.
Liangchen Zhuo *State Key Laboratory of Cognitive Science and Mental Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.ORCID 0009-0009-2488-5089
Xiya Liu *State Key Laboratory of Cognitive Science and Mental Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.
Suijuan Zhong *IDG/McGovern Institute for Brain Research, New Cornerstone Science Laboratory, Beijing Normal University, Beijing, China.ORCID 0000-0003-4382-6577
Chonghai YinChangping Laboratory, Beijing, China.
Mayuqing LiIDG/McGovern Institute for Brain Research, New Cornerstone Science Laboratory, Beijing Normal University, Beijing, China.
Mengdi WangState Key Laboratory of Cognitive Science and Mental Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.
Wei WangState Key Laboratory of Cognitive Science and Mental Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.
Xin ZhouIDG/McGovern Institute for Brain Research, New Cornerstone Science Laboratory, Beijing Normal University, Beijing, China.
Bo ZengChangping Laboratory, Beijing, China.
Changsheng DongState Key Laboratory of Cognitive Science and Mental Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.
Le SunBeijing Institute of Brain Disorders, Capital Medical University, Beijing, China. sunle@ibp.ac.cn.
Zheng WangSchool of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, State Key Laboratory of General Artificial Intelligence, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China. zheng.wang@pku.edu.cn.ORCID 0000-0001-7138-8581
Ang LiState Key Laboratory of Cognitive Science and Mental Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China. al@ibp.ac.cn.ORCID 0000-0002-2309-9811
Qian WuIDG/McGovern Institute for Brain Research, New Cornerstone Science Laboratory, Beijing Normal University, Beijing, China. qianwu@bnu.edu.cn.ORCID 0000-0002-7469-1583
Xiaoqun WangState Key Laboratory of Cognitive Science and Mental Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China. xiaoqunwang@ibp.ac.cn.ORCID 0000-0003-3440-2617

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Elucidating how microscale molecular architecture shapes macroscale brain network organization requires integrative frameworks that link transcriptional profiles, structural connectivity, and functional dynamics across scales. However, existing evidence largely relies on cross-modal data acquired from different individuals, limiting causal and mechanistic inference. To overcome this, we performed concurrent awake optogenetic functional MRI (opto-fMRI) and spatial transcriptomics (opto-ST) within the same mice, enabling coupled analysis of neural activity and gene expression in fronto-thalamic and hippo-thalamic networks. Optogenetic stimulation of the medial prefrontal cortex (mPFC) or subiculum (SUB) evoked distinct thalamic BOLD response patterns. Multivariate spatial modeling revealed that energy metabolism and core biochemical processes underlie these GLM-derived activation patterns-a finding further supported by data-driven PCA, which identified enrichments in similar biological processes. These results suggest that conventional linear models predominantly capture linear gene-process relationships, highlighting the need for nonlinear computational approaches in fMRI analysis. Overall, our multi-omics framework reveals that genes regulating metabolic pathways underlie region-specific neurovascular coupling, thereby bridging local transcriptomics and large-scale functional imaging signatures.

Indexed as

Magnetic Resonance ImagingNerve NetOptogeneticsThalamusTranscriptomeAnimalsBrain MappingMaleMiceMice, Inbred C57BLPrefrontal CortexSpatial Transcriptomics

Identifiers

PMID42000729
PMCPMC13276179

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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.