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Artificial Retina: A Future Cellular-Resolution Brain-Machine Interface

  • Dante G. MuratoreEmail author
  • E. J. Chichilnisky
Chapter
Part of the The Frontiers Collection book series (FRONTCOLL)

Abstract

Brain-machine interfaces (BMIs) of the future will be used to treat diverse neurological disorders and augment human capabilities. However, to realize this futuristic promise will require a major leap forward in how electronic devices interact with the nervous system. Current BMIs provide coarse communication with the target neural circuitry, because they fail to respect its cellular and cell-type specificity. Instead, they indiscriminately activate or record many cells at the same time and provide only partial restoration of lost abilities. A future BMI that may pave the path forward is an artificial retina—a device that can restore vision to people blinded by retinal degeneration. Because the retina is relatively well understood and easily accessible, it is an ideal neural circuit in which to develop a BMI that can approach or exceed the performance of the biological circuitry. This chapter summarizes the basic neuroscience of vision, identifies the requirements for an effective retinal interface, and describes some of the necessary circuits and systems. Based on these ideas and the lessons from first-generation retinal prostheses, a novel neuroengineering approach is proposed: the first BMI that will interact with neural circuitry at cellular and cell-type resolution.

Notes

Acknowledgements

The authors would like to thank Marty Breidenbach, Ruwan Silva, Stephen Weinreich, Matthias Kuhl, Daniel Palanker, Nishal Shah and the Stanford Artificial Retina Group [54] for useful discussions and comments, and Peter Li, Chris Sekirnjak, and Nora Brackbill for figure contributions. DM, EJC and the Stanford Artificial Retina Project are funded by the Wu Tsai Neurosciences Institute. EJC is funded by NEI grant EY021271 and a Stein Innovation Award from Research to Prevent Blindness.

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Electrical EngineeringStanford UniversityStanfordUSA
  2. 2.Wu Tsai Neurosciences InstituteStanford UniversityStanfordUSA
  3. 3.Department of NeurosurgeryStanford UniversityStanfordUSA
  4. 4.Department of OphthalmologyStanford UniversityStanfordUSA

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