In one paragraphArticle in bioRxiv : the preprint server for biology, 2025. 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
–field-weighted citation impact
1 · What the graph read from itWhat 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 registryThe 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.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
5 · Who and what moneyAuthors and funding
11 authors.
Jian LiCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School.ORCID 0000-0002-1691-8727 Alexander S AtalayCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School.ORCID 0009-0009-1511-7782 Mark OlchanyiCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School.ORCID 0000-0001-7112-2118 Morgan K CambareriCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School.ORCID 0009-0006-9179-461X Andreas HornCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School.ORCID 0000-0002-0695-6025 Laura LewisAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School.ORCID 0000-0002-6552-3481 Emery N BrownDepartment of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital and Harvard Medical School.ORCID 0000-0003-2668-7819 Bruce FischlAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School.ORCID 0000-0002-2413-1115 Brian L EdlowCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School.ORCID 0000-0001-7235-8456 Funding
Functionally guided adult whole brain cell atlas in human and NHPUM1MH130981 · NIMH · ALLEN INSTITUTE · PI Ed Lein, Hongkui Zeng · 2022 to 2026
$91.9MCenter for Multi-Scale Multi-Omic Human and non-human primate Brain AtlasUM1MH134812 · NIMH · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Kwanghun Chung, PATRICK R HOF · 2025 to 2026
$21.7MBRAIN CONNECTS: The center for Large-scale Imaging of Neural Circuits (LINC)UM1NS132358 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Suzanne N Haber, Elizabeth M. C. Hillman · 2023 to 2026
$17.5MMRI, Genetics &Cognitive Precursors of AD &DementiaR01AG016495 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI AU, RHODA · 1999 to 2016
$12.5MThe Human Connectome Project (HCP)U01MH093765 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI ROSEN, BRUCE R · 2010 to 2014
$12.1MTraining and Dissemination CoreP41EB030006 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI Susie Yi Huang · 2020 to 2026
$10.9MThe Late Effects of TBI (LETBI) Study: Injury Patterns and Biological Markers of Post-Traumatic NeurodegenerationRF1NS115268 · NINDS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Kristen Dams-O'Connor · 2019 to 2026
$10.3MImaging and Analysis Techniques to Construct a Cell Census Atlas of the Human Brain Admin SupplementU01MH117023 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI BOAS, DAVID A, FISCHL, BRUCE · 2018 to 2022
$7.6MUsing human brain connectivity to identify the causal neuroanatomical substrate of depression symptomsR01MH113929 · NIMH · BRIGHAM AND WOMEN'S HOSPITAL · PI MICHAEL D FOX · 2017 to 2026
$6.9MAn Acquisition and Analysis Pipeline for Integrating MRI and Neuropathology in TBI-related Dementia and VCIDU24NS135561 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Bruce Fischl, Susie Yi Huang · 2023 to 2026
$6.1MFreeSurfer Development, Maintenance, and HardeningR01EB023281 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI Bruce Fischl, Douglas Nowlin Greve · 2016 to 2026
$5.6MA Longitudinal Analysis Stream for FreeSurferR01NS083534 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Bruce Fischl · 2014 to 2026
$4.6MNCRR NIH HHS S10 RR019307NCRR NIH HHS S10 RR023043NCRR NIH HHS S10 RR023401NIA NIH HHS R01 AG016495NIA NIH HHS R01 AG064027NIA NIH HHS R01 AG070988NIA NIH HHS R21 AG082082NIBIB NIH HHS P41 EB030006NIBIB NIH HHS R01 EB019956NIBIB NIH HHS R01 EB023281NIBIB NIH HHS R21 EB018907NICHD NIH HHS DP2 HD101400NIMH NIH HHS R01 MH113929NIMH NIH HHS R01 MH130666NIMH NIH HHS RF1 MH121885NIMH NIH HHS RF1 MH123195NIMH NIH HHS U01 MH093765NIMH NIH HHS U01 MH117023NIMH NIH HHS UM1 MH130981NIMH NIH HHS UM1 MH134812NINDS NIH HHS R01 NS070963NINDS NIH HHS R01 NS083534NINDS NIH HHS R01 NS105820NINDS NIH HHS R01 NS127892NINDS NIH HHS R01 NS128961NINDS NIH HHS R01 NS138257NINDS NIH HHS R21 NS109627NINDS NIH HHS R25 NS125599NINDS NIH HHS RF1 NS115268NINDS NIH HHS U01 NS132181NINDS NIH HHS U24 NS135561NINDS NIH HHS UM1 NS132358
6 · The paper itselfAbstract
Brain network mapping plays a crucial role in advancing our understanding of human brain organization and the neuroanatomic foundations of cognition. Historically, the identification of large-scale brain networks has focused on the cerebral cortex. Some cortical networks have been fractionated into subnetworks, yielding valuable insights into their domain-specific cognitive functions. In contrast, functional mapping of large-scale brain networks within subcortical regions remains an emerging and challenging field, hindered by a low signal-to-noise ratio in subcortical functional MRI data and an inability to distinguish networks with substantial spatiotemporal overlap. In this study, we fractionated and identified fifteen spatially overlapped and temporally correlated subnetworks, which can be categorized into four large-scale brain networks. The subcortical functional connectivity patterns of these subnetworks exhibited distinct, yet overlapping, spatial configurations, with widely connected hub nodes identified in the caudate, putamen, hippocampus, and thalamus. These subnetworks are highly reproducible across healthy human brains and provide normative functional atlases, which we release here as a resource for the academic community. As a proof-of-principle demonstration of how the atlases can be used to elucidate the pathophysiology of neuropsychiatric disorders, we show that the spatial patterns of the subnetworks predict the level of consciousness in patients with severe traumatic brain injury. These observations indicate a highly conserved and spatially overlapped subcortical functional architecture in the human brain, providing opportunities to elucidate pathophysiologic mechanisms and develop new neuromodulatory therapies for a broad spectrum of neuropsychiatric diseases.
Identifiers
PMID41509362
PMCPMC12776100
What OpenQuestion holds
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