Back to articles
Proceedings Paper
Volume: 38 | Article ID: MOBMU-347
Image
Automation of a Stereotaxic Device through Neuroanatomical Atlas Integrated Motion Control: A Modular Retrofit Approach for Precision Neuroscience Applications
  DOI :  10.2352/EI.2026.38.3.MOBMU-347  Published OnlineMarch 2026
Abstract
Abstract

Stereotaxic neurosurgery in small-animal neuroscience remains largely manual and operator-dependent, introducing variability that compromises experimental reproducibility. This paper presents a modular retrofit system that motorises a conventional rodent stereotaxic frame and integrates it with Pinpoint for neuroanatomic positioning via a custom Ephys Link binding, enabling direct software-to-hardware coordinate translation from neuroanatomical atlas-based planning to physical needle insertion. The system uses NEMA 17 stepper motors with a 14:1 planetary gearbox, a Duet 3 Mini 5+ motion controller originally developed for open-source 3D printing and here adapted for neuroscience through developer collaboration, and RepRapFirmware configured in CNC mode. A custom firmware parameter (M203 I0.1) unlocks a minimum feed rate of 0.1 mm/min for tissue-safe brain insertion. The microinjection axis is fully automated for suction and retraction. A custom housing provides structural rigidity, vibration damping, and cable management without modifying the original frame. The system achieves positional accuracy beyond 0.1mm, with a nominal microstep increment of 0.09μm, validated using phantoms and ex vivo specimens

Subject Areas :
Views 45
Downloads 12
 articleview.views 45
 articleview.downloads 12
  Cite this article 

Johnssi Manjunath, Lukasz Rojek, York Winter, "Automation of a Stereotaxic Device through Neuroanatomical Atlas Integrated Motion Control: A Modular Retrofit Approach for Precision Neuroscience Applicationsin Electronic Imaging,  2026,  pp 347-1 - 347-6,  https://doi.org/10.2352/EI.2026.38.3.MOBMU-347

 Copy citation
  Copyright statement 
Copyright ©2026 Society for Imaging Science and Technology 2026
ei
Electronic Imaging
2470-1173
2470-1173
Society for Imaging Science and Technology
IS&T 7003 Kilworth Lane, Springfield, VA 22151 USA