4.8 Article

Graphene Electric Field Sensor Enables Single Shot Label-Free Imaging of Bioelectric Potentials

Journal

NANO LETTERS
Volume 21, Issue 12, Pages 4944-4949

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.nanolett.1c00543

Keywords

graphene; photonics; bioelectricity; electrophysiology; voltage sensing imaging; microscopy

Funding

  1. U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division [DE-AC02-05CH11231, KC1203]
  2. National Institutes of Health [1R01NS121934]
  3. National Science Foundation [DMR-1344302]
  4. Stanford Bowes Bio-X Graduate Fellowship
  5. NSF Graduate Research Fellowship [DGE 1106400]

Ask authors/readers for more resources

The measurement of electrical activity across systems of excitable cells presents significant technological challenges due to the vast differences in intensity, space, and time. Developing methods for high spatial resolution network-scale recordings remains crucial for studying electrogenic cells, emergent networks, and bioelectric computation.
The measurement of electrical activity across systems of excitable cells underlies current progress in neuroscience, cardiac pharmacol-ogy, and neurotechnology. However, bioelectricity spans orders of magnitude in intensity, space, and time, posing substantial technological challenges. The development of methods permitting network-scale recordings with high spatial resolution remains key to studies of electrogenic cells, emergent networks, and bioelectric computation. Here, we demonstrate single-shot and label-free imaging of extracellular potentials with high resolution across a wide field-of-view. The critically coupled waveguide-amplified graphene electric field (CAGE) sensor leverages the field-sensitive optical transitions in graphene to convert electric potentials into the optical regime. As a proof-of-concept, we use the CAGE sensor to detect native electrical activity from cardiac action potentials with tens-of-microns resolution, simultaneously map the propagation of these potentials at tissue-scale, and monitor their modification by pharmacological agents. This platform is robust, scalable, and compatible with existing microscopy techniques for multimodal correlative imaging.

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