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Engineered conductive polymer for neural activity recording

Engineered conductive polymer for neural activity recording

Unmet Need

Dysfunctions in neural circuit activity underlie complex psychiatric diseases such as depression, schizophrenia, Alzheimer’s disease, and others. Neural activity recording is critical to understand brain function and how aberrations in neural circuits lead to psychiatric diseases. Neural activity recording requires the ability to simultaneously record thousands of neurons with millisecond resolution and knowledge of each cell’s genetic identity. However, no recording technology encompassing all these features is currently available. Current technologies such as electrodes and genetically encoded activity indicators are slow, have limited stability, and can only record a few neurons at a time. In addition, current tools are not compatible with neural activity recording in freely-behaving animals. To overcome these technological barriers, there is a need for an inexpensive, scalable method for simultaneous recording of many genetically defined neurons with milisecond precision.


Duke inventors have engineered an electroconductive polymer that covalently attaches neurons to electrodes. This is intended to be used as a research tool to record electrophysiological readouts from neural activity. Specifically, the inventors have synthesized novel chemical derivatives of 3,4-ethylenedioxythiophene monomers containing the HaloTag ligand (EDOT-HTL) that covalently attaches to neurons genetically expressing the HaloTag protein. The monomers can be electro-polymerized on a multielectrode array to enable electrical signal recording. As a proof of concept, the inventors have shown that light-stimulated neural activity from covalently attached, HaloTag-expressing primary rat hippocampal neurons can be detected by a multielectrode array coated with polymerized EDOT-HTL. The inventors are also developing this approach to record neural activity in vivo using implanted electrode arrays.

Other Applications

This approach can be scaled up for high-throughput screening platforms based on electrophysiological readouts. Beyond its use as a research tool, this approach can be adapted to improve brain-machine interface technologies.


  • Stable neural activity recording in genetically-defined cells with millisecond precision
  • Compatible with neural activity recording in freely behaving animals
  • Does not require a complex analysis pipeline
  • Cost-effective, scalable, and modular

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