A novel low-noise movement tracking system with real-time analog output for closed-loop experiments

Nora Gaspar, Ronny Eichler, Eran Stark

Research output: Contribution to journalArticlepeer-review


Background: Modern electrophysiological experiments are moving towards closing the loop, where the extrinsic (behavioral) and intrinsic (neuronal) variables automatically affect stimulation parameters. Rodent experiments targeting spatial behavior require animal 2D kinematics to be continuously monitored in a reliable and accurate manner. Cameras provide a robust, flexible, and simple way to track kinematics on the fly. Indeed, several available camera-based systems yield high spatiotemporal resolution. However, the acquired kinematic data cannot be accessed with sufficient temporal resolution for precise real-time feedback. New method: Here, we describe a novel software and hardware system for movement tracking based on color-markers with real-time low-noise output that works in both light and dark conditions. The analog outputs precisely represent 2D movement features including position, orientation, and their temporal derivatives, velocity and angular velocity. Results: Using adaptive windowing, contour extraction, and rigid-body Kalman filtering, a 640-by-360 pixel frame is processed in 28 ms with less than 4 ms jitter, for 100 frames per second. The system is robust to outliers, has low noise, and maintains a smooth, accurate output even when one or more markers are temporarily missing. Using freely-moving mice, we demonstrate novel applications such as replacing conventional sensors in a behavioral arena and inducing novel place fields via closed-loop optogenetic stimulation. Comparison with existing method(s): To the best of our knowledge, this is the first tracking system that yields analog output in real-time. Conclusions: This modular system for closed-loop experiment tracking can be implemented by downloading an open-source software and assembling low-cost hardware circuity.

Original languageEnglish
Pages (from-to)69-77
Number of pages9
JournalJournal of Neuroscience Methods
StatePublished - 15 Apr 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019 Elsevier B.V.


  • Closed-loop
  • Design for experiments
  • Electrophysiology
  • Image processing
  • Kalman filter
  • Open-source

ASJC Scopus subject areas

  • General Neuroscience


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