Simultaneous fMRI and Fast-Scan Cyclic Voltammetry: Methodological Considerations and In Vivo Oxygen Measurements
Lindsay Walton1, Matthew Verber2, R. Mark Wightman2, and Yen-Yu Ian Shih1

1Biomedical Research Imaging Center and Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, 2Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States


fMRI is based on the dogma that neuronal activity couples to local hemodynamic changes; however, exceptions to this rule exist with little explanation why. Additional neurophysiological context, such as concurrent release of vasoactive neurotransmitters, is required to discern how other underlying factors contribute to evoked hemodynamic responses. Fast-scan cyclic voltammetry (FSCV) is a minimally-invasive technique capable of detecting neurotransmitters and tissue oxygen with high temporal and spatial resolution. Here, we design a multimodal platform to perform simultaneous fMRI and FSCV, prove its feasibility in vitro, and expand its use to characterize evoked oxygen detection in vivo.


BOLD fMRI has been a cornerstone of dissecting brain functionality by measuring the cerebral blood oxygenation changes in response to stimuli.1 Though most changes are attributed to neuronal activity, the roles of vasoactive neurotransmitters in fMRI signal generation are poorly understood.2-4 Fast-scan cyclic voltammetry (FSCV) quantifies electroactive neurotransmitters and oxygen concentrations with high spatiotemporal resolution by oxidizing and/or reducing analytes at a microelectrode.5,6 The additional context of evoked neurotransmitter release and higher resolution oxygen measurements makes FSCV an ideal complement to BOLD. Presently, technical limitations have stymied simultaneous FSCV/fMRI development beyond proof-of-concept.7,8 The present study addresses these limitations by providing: 1) an experimental setting optimized for simultaneous FSCV/fMRI recordings, 2) a custom hardware and software filtering setup that diminishes gradient-induced electromagnetic noise without impacting FSCV sensitivity, and 3) an in vivo demonstration of simultaneous FSCV/BOLD fMRI recording evoked oxygen changes. This optimized methodology can quantify evoked neurotransmitter release and more sensitive tissue oxygen changes during fMRI, which will enhance our ability to interpret functional neuroimaging data.


Carbon-fiber microelectrodes were fabricated using fused-silica/polyimide capillaries (Fig.1A,B).5 A flow injection setup was adapted for use inside the MR bore (Fig.1C).9 A syringe pump flowed phosphate/saline buffer (pH=7.4) to the microelectrode at 2.0mL/min, and dopamine HCl boluses were injected via 6-port injector valve (Fig.1C). FSCV data was obtained and analyzed with custom-designed High-Definition Cyclic Voltammetry software and instrumentation.10 A dopamine-sensing waveform (-0.4V to +1.3V, then back to -0.4V versus Ag/AgCl at 400 V/s) was applied at 5Hz (Fig.1D).5 Dopamine solutions were injected in triplicate, in random concentration order. FSCV data collection was synchronized with per-RF-excitation MR TTLs, delayed to avoid the gradient-encoding artifacts from single-shot EPI sequences (see below), filtered, and background-subtracted (Fig.1E,F). Principal component analysis extracted analyte currents for analysis.11

An oxygen-sensing waveform (0 to +0.8V, then to –1.4V, then back to 0V at 200 V/s) was applied at 5Hz (Fig.1D) in a rat brain.6 A twisted tungsten stimulating electrode was implanted near the ventral tegmental area (VTA) to evoke oxygen changes near the nucleus accumbens (NAc) (4s at 60Hz, pulse width=2ms). A carbon-fiber microelectrode and an Ag/AgCl reference were implanted in the ipsilateral NAc and contralateral cortex, respectively. BOLD fMRI was acquired simultaneously (TR/TE=1000/15ms, matrix=80x80, FOV=2.56cm2, 5 slices, thickness=1.0mm). FSCV time-courses were decimated by a factor of 5 to match BOLD time-scales and assess the correlation between evoked measurements. Contrast-to-noise ratios were calculated as [(Oxygen Peak Amplitude-Average Baseline)/Standard Deviation]*100.

Results and Discussion

To assess whether simultaneous FSCV/fMRI data could be collected, we synchronized voltammetry data collection to MR TTL outputs. The encoding gradient caused significant electromagnetic interference, especially with the additional 50 kHz gradient amplifier switching frequency noise. The latter was mostly removed with a digital Bessel filter (Fig.1E,F).10 A 50ms wait time was introduced to interleave the encoding gradient and FSCV waveforms, which eliminated the MR interference (Fig.1D,F). Thus, FSCV and fMRI data can be collected concurrently when the gradient artifact and waveforms are interleaved.

To test whether physiologically relevant concentrations of electroactive neurotransmitters can be detected using FSCV inside an MR bore, bolus injections of dopamine were introduced. With the gradient disabled, no gradient amplifier noise was present and concentrations ≥50nM could be detected (Fig.2A). With the gradient enabled, concentrations >100nM could be detected after digital filtering (Fig.2B,D). When the input signal was sent through a 2 kHz low-pass analog filter,12 concentrations ≥50 nM could be detected (Fig.2C,D). All calibration constants were >10nA/µM, consistent with the sensitivity of in vitro electrodes in a shielded environment.

With timing and filtering optimized, we electrically stimulated the VTA to evoke oxygen changes in the NAc (Fig.3A). Both evoked oxygen changes scaled with stimulation intensity (Fig.3B); however, a temporal offset was observed that may be attributed to the mismatched fMRI ROI size versus the microelectrode sampling volume and the different blood-versus-tissue oxygen diffusion therein. In addition to having 5x higher temporal resolution, FSCV had superior contrast-to-noise ratios (Fig.3C). After downsampling FSCV time-courses to match BOLD temporal resolution, we performed an unbiased voxel-wise correlation analysis between them and found strong, significant correlations near the microelectrode, the nearby NAc, and ventral pallidum (Fig.3D). When corrected for the slight diffusion shift, the oxygen metrics significantly correlated (Fig.3E). The agreement between changes in evoked tissue oxygen timing and amplitudes using simultaneous FSCV/fMRI lends credence to the functionality of our experimental setup.


We optimized a simultaneous FSCV and MRI experimental setup for in vitro and in vivo use. FSCV is faster, more sensitive, and can detect electroactive neurotransmitters, but BOLD provides unbiased, brain-wide measurements. This multimodality holds great promise for BOLD noise removal and improving our current understanding of fMRI data with neurochemical context at multiple temporal and spatial scales.


We thank the Shih lab members for their helpful discussions and critiques. We acknowledge the help of Philip Summers for 3D modeling the electrode holder prototype. Our team is supported by NIMH R01MH111429, R41MH113252, R21 MH106939, NINDS R01NS091236, NIAAA U01AA020023, R01AA025582, NICHD U54HD079124, American Heart Association 15SDG23260025, and Brain & Behavior Research Foundation.


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Optimizing simultaneous in vitro FSCV and fMRI. (A) Carbon-fiber microelectrode fabrication. (B) Finished microelectrode tip (30x magnification). (C) 6-port valve flow-injection cartoon. Buffer (white arrows) or dopamine from the sample loop (purple arrows) flows to the microelectrode depending on valve position. (D) Schematic for interleaved dopamine or oxygen FSCV waveforms and fMRI (inset=shaded box). (E,F) FSCV data with MR gradient interference (E) versus interleaved (F) and digital Bessel filtering. Color plot y-axes are applied voltage, x-axes are time, and current amplitude is false color. Current time-courses taken from the white dashed line of its corresponding color plot.

In vitro flow injection color plots and calibration curves for dopamine. (A) Data collected with the gradient disabled. (B) With the gradient enabled, high frequency, 50kHz amplifier noise masked the signal (left), but was removed with a digital Bessel filter (right). (C) Gradient amplifier noise was removed by filtering input signal with a 2kHz low-pass analog filter. Each color plot depicts the average of three 25s boluses of 500nM dopamine. (D) Calibration plots from A-C. The slopes, denoting sensitivity to dopamine, are as follows: A, 12.61±0.70 nA/µM (R2=0.98); B, 14.81±1.23 nA/µM (R2=0.97); C, 19.96±0.66 nA/µM (R2=0.99).

Simultaneous in vivo oxygen FSCV and BOLD fMRI. (A) Sagittal view of intracranial FSCV implants and applied oxygen waveform. (B) Time-courses for evoked BOLD and FSCV oxygen changes, acquired simultaneously. The slight temporal mismatch may result from mismatched spatial sampling. Red bar denotes stim duration. (C) FSCV was significantly more sensitive to evoked changes than BOLD (unpaired t-test, F(2,31)=25.34, P<0.0001). (D) fMRI correlation coefficient maps derived from the downsampled FSCV oxygen time-course. (E) The evoked amplitude changes from BOLD and FSCV, when the temporal alignment in B is corrected, highly correlate (uncorrected Pearson's r=0.44, P<0.0001).

Proc. Intl. Soc. Mag. Reson. Med. 26 (2018)