Review in Nature protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
0numbers the graph read from it
0cells of the map it votes in
3citing 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.
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
8 authors.
Tatiana A ShnitkoCenter for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. shnitko@email.unc.edu.
Lindsay R WaltonCenter for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Tong-Yu Rainey PengCenter for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Sung-Ho LeeCenter for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Tzu-Hao Harry ChaoCenter for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Matthew D VerberCenter for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
R Mark WightmanDepartment of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Yen-Yu Ian ShihCenter for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. shihy@neurology.unc.edu.ORCID 0000-0001-6529-911X
Funding
UNC ARC Information/Dissemination CoreP60AA011605 · NIAAA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Clyde W Hodge · 2003 to 2026
$46.3M
Preclinical CoreP50HD103573 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI GABRIEL S DICHTER · 2020 to 2026
$9.7M
UNC-CH NADIA Underage Drinking and Adult Brain Morphology in RatsU01AA020023 · NIAAA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI CREWS, FULTON T · 2010 to 2024
$7.5M
MOLECULAR AND CELLULAR PATHOGENESIS IN ALCOHOLISMP50AA011605 · NIAAA · UNIVERSITY OF NORTH CAROLINA CHAPEL HILL · PI BREESE, GEORGE R · 1998 to 2002
$4.9M
Circuit Mechanisms Governing the Default Mode NetworkR01MH126518 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Vinod Menon, Yen-Yu Ian Shih · 2021 to 2026
$4.3M
Mechanisms underlying positive and negative BOLD in the striatumRF1MH117053 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SHIH, YEN-YU IAN · 2018 to 2019
$4.0M
Chemogenetic Dissection of Neuronal and Astrocytic Compartment of the BOLD SignalR01MH111429 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SHIH, YEN-YU IAN · 2016 to 2020
$2.7M
SORDINO-fMRI for mouse brain applicationsR01EB033790 · NIBIB · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Yen-Yu Ian Shih · 2023 to 2026
$2.5M
Functional dissection of therapeutic deep brain stimulation circuitryR01NS091236 · NINDS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SHIH, YEN-YU IAN · 2015 to 2019
$2.0M
9.4T Small Animal MRI scanner at UNCS10OD026796 · OD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SHIH, YEN-YU IAN · 2020 to 2020
$2.0M
AVANCE NEO upgrade for the BioSpec 9.4T/30cm MRI system at UNCS10MH124745 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SHIH, YEN-YU IAN · 2020 to 2020
$600k
Accurate and Individualized Prediction of Excitation-Inhibition Imbalance in Alzheimer's Disease using Data-driven Neural ModelR21AG083589 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LI, GUOSHI, SHIH, YEN-YU IAN · 2023 to 2023
$428k
NIAAA NIH HHS P50 AA011605NIAAA NIH HHS P60 AA011605NIAAA NIH HHS U01 AA020023NIA NIH HHS R21 AG083589NIBIB NIH HHS R01 EB033790NICHD NIH HHS P50 HD103573NIDA NIH HHS R21 DA057503NIH HHS S10 OD026796NIMH NIH HHS F32 MH115439NIMH NIH HHS R01 MH111429NIMH NIH HHS R01 MH126518NIMH NIH HHS R41 MH113252NIMH NIH HHS RF1 MH117053NIMH NIH HHS S10 MH124745NINDS NIH HHS R01 NS091236NINDS NIH HHS R21 NS133913U.S. Department of Health & Human Services | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) P50HD103573U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering (NIBIB) R01EB033790U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) F32MH115439U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) RF1MH117053, R01MH126518, R01MH111429, S10MH124745U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS) R01NS091236, R21NS133913U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse (NIDA) R21DA057503
6 · The paper itself
Abstract
One of the challenges associated with functional magnetic resonance imaging (MRI) studies is integrating and causally linking complementary functional information, often obtained using different modalities. Achieving this integration requires synchronizing the spatiotemporal multimodal datasets without mutual interference. Here we present a protocol for integrating electrochemical measurements with functional MRI, enabling the simultaneous assessment of neurochemical dynamics and brain-wide activity. This Protocol addresses challenges such as artifact interference and hardware incompatibility by providing magnetic resonance-compatible electrode designs, synchronized data acquisition settings and detailed in vitro and in vivo procedures. Using dopamine as an example, the protocol demonstrates how to measure neurochemical signals with fast-scan cyclic voltammetry (FSCV) in a flow-cell setup or in vivo in rats during MRI scanning. These procedures are adaptable to various analytes measurable by FSCV or other electrochemical techniques, such as amperometry and aptamer-based sensing. By offering step-by-step guidance, this Protocol facilitates studies of neurovascular coupling with the neurochemical basis of large-scale brain networks in health and disease and could be adapted in clinical settings. The procedure requires expertise in MRI, FSCV and stereotaxic surgeries and can be completed in 7 days.
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.
Measurement of electrochemical brain activity with fast-scan cyclic voltammetry during functional magnetic resonance imaging. · full record | OpenQuestion