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Measurement of electrochemical brain activity with fast-scan cyclic voltammetry during functional magnetic resonance imaging

Nature Protocols (2025)Cite this article

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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.

Key points

  • This Protocol covers the simultaneous use of fast-scan cyclic voltammetry and functional magnetic resonance imaging to measure local tissue oxygen and neurotransmitter dynamics, enabling reliable benchmarking of neurochemical signals. This in vivo approach allows a direct comparison of neurochemical and hemodynamic information across spatiotemporal scales.

  • This translational method provides an alternative to fiber photometry-based measurements of genetically encoded fluorescent biosensors, which are confined to preclinical animal studies and lack potential for use in humans.

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Fig. 1: Procedures to ensure optimal voltammetric recording practices in a high magnetic field.
Fig. 2: Overview of the procedure.
Fig. 3: Principle behind dopamine and BOLD signals detection using FSCV–fMRI.
Fig. 4: Software modifications enabling FSCV recording of dopamine under condition of EPI-based MRI.
Fig. 5: HDCV data acquisition interface with options for adjusting parameters of FSCV recording.
Fig. 6: HDCV software interface for FSCV data analysis.
Fig. 7: The oscilloscope and color plot for ensuring quality control for FSCV recordings.
Fig. 8: Experimental results obtained using FSCV/fMRI approach in the microfluidic flow cell and anesthetized rats.

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Data availability

All data in this Protocol were previously published in supporting primary research article8.

Code availability

Standard AFNI codes were used for BOLD fMRI preprocessing and traditional functional activation map analysis (https://afni.nimh.nih.gov). The Python codes to obtain statistical response maps are available via GitHub at https://github.com/waltonlr/FSCV-fMRI_analysis_stats.

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Acknowledgements

This work was supported in part by the National Institute of Mental Health (grants RF1MH117053, R01MH126518, R01MH111429 and S10MH124745 to Y.-Y.I.S. and F32MH115439 to L.R.W.), National Institute of Biomedical Imaging and Bioengineering (grant R01EB033790 to Y.-Y.I.S. and S.-H.L.), National Institute of Neurological Disorders and Stroke (grants R01NS091236 and R21NS133913 to Y.-Y.I.S.), National Institute on Alcohol Abuse and Alcoholism (grants P60AA011605 and U01AA020023 to Y.-Y.I.S. and S.H.L.), National Institute of Drug Abuse (grant R21DA057503 to Y.-Y.I.S.), National Institute of Child Health and Human Development (grant P50HD103573 to Y.-Y.I.S. and S.H.L.), National Institute of Health Office of the Director (grant S10OD026796 to Y.-Y.I.S.) and W.M. Keck Foundation (Y.-Y.I.S.).

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Authors and Affiliations

  1. Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Tatiana A. Shnitko, Lindsay R. Walton, Tong-Yu Rainey Peng, Sung-Ho Lee, Tzu-Hao Harry Chao, Matthew D. Verber & Yen-Yu Ian Shih

  2. Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Tatiana A. Shnitko, Lindsay R. Walton, Tong-Yu Rainey Peng, Sung-Ho Lee, Tzu-Hao Harry Chao & Yen-Yu Ian Shih

  3. Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Matthew D. Verber & R. Mark Wightman

  4. Green Level High School, Cary, NC, USA

    Tong-Yu Rainey Peng

Authors
  1. Tatiana A. Shnitko
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  2. Lindsay R. Walton
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  3. Tong-Yu Rainey Peng
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  4. Sung-Ho Lee
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  8. Yen-Yu Ian Shih
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Contributions

L.R.W., S.H.L., T.H.H.C., R.M.W. and Y.-Y.I.S. coauthored the original study that formed the foundation for this protocol. Conceptualization: Y.-Y.I.S. Methodology and protocol development: L.R.W. and T.A.S. Investigation and data collection: L.R.W., T.A.S., T.H.H.C. and T.Y.R.P. Data analysis: T.A.S., L.R.W. and S.H.L. Technical support: R.M.W. and M.D.V. Writing—original draft: T.A.S. and T.Y.R.P. Writing—review and editing: all authors. Funding acquisition and supervision: S.H.L. and Y.-Y.I.S.

Corresponding authors

Correspondence to Tatiana A. Shnitko or Yen-Yu Ian Shih.

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Nature Protocols thanks Paul Min and Alex Leong for their contribution to the peer review of this work.

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Key reference

Walton, L. R. et al. Neuroimage 244, 118634 (2021): https://doi.org/10.1016/j.neuroimage.2021.118634

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Shnitko, T.A., Walton, L.R., Peng, TY.R. et al. Measurement of electrochemical brain activity with fast-scan cyclic voltammetry during functional magnetic resonance imaging. Nat Protoc (2025). https://doi.org/10.1038/s41596-025-01250-9

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