Assembly and operation of an open-source, computer numerical controlled (CNC) robot for performing cranial microsurgical procedures

Mathew L. Rynes, Leila Ghanbari, Daniel Sousa Schulman, Samantha Linn, Michael Laroque, Judith Dominguez, Zahra S. Navabi, Peter Sherman, Suhasa B. Kodandaramaiah

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Cranial microsurgery is an essential procedure for accessing the brain through the skull that can be used to introduce neural probes that measure and manipulate neural activity. Neuroscientists have typically used tools such as high-speed drills adapted from dentistry to perform these procedures. As the number of technologies available for neuroscientists has increased, the corresponding cranial microsurgery procedures to deploy them have become more complex. Using a robotic tool that automatically performs these procedures could standardize cranial microsurgeries across neuroscience laboratories and democratize the more challenging procedures. We have recently engineered a robotic surgery platform that utilizes principles of computer numerical control (CNC) machining to perform a wide variety of automated cranial procedures. Here, we describe how to adapt, configure and use an inexpensive desktop CNC mill equipped with a custom-built surface profiler for performing CNC-guided microsurgery on mice. Detailed instructions are provided to utilize this ‘Craniobot’ for performing circular craniotomies for coverslip implantation, large craniotomies for implanting transparent polymer skulls for cortex-wide imaging access and skull thinning for intact skull imaging. The Craniobot can be set up in <2 weeks using parts that cost <$1,500, and we anticipate that the Craniobot could be easily adapted for use in other small animals.

Original languageEnglish (US)
Pages (from-to)1992-2023
Number of pages32
JournalNature Protocols
Issue number6
StatePublished - Jun 1 2020

Bibliographical note

Funding Information:
S.B.K. acknowledges funds from the Mechanical Engineering Department, College of Science and Engineering, MnDRIVE RSAM initiative of the University of Minnesota, Minnesota Department of Higher Education and NIH 1R21NS103098-01, 1R01NS111028, 1R34NS111654, 1R21NS112886 and 1R21 NS111196. L.G. was supported by the University of Minnesota Informatics Institute’s (UMII) graduate fellowship. We thank Dr. Eric Yttri, Alan Lai and Mark Nicholas of the Yttri laboratory at Carnegie Mellon University for useful feedback during beta-testing of the Craniobot. We also thank Luiz Bueno and Dr. York Winter of, who provided insights and suggested improvements to streamline hardware assembly. We also thank Dr. Spencer Smith (@Labrigger) for discussions on automated technologies for cranial microsurgeries and the strategies for wide adoption of such technologies, which partially motivated the documentation of this protocol.

Publisher Copyright:
© 2020, The Author(s), under exclusive licence to Springer Nature Limited.

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't


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