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Related Experiment Video

Updated: Jan 22, 2026

Brain State-dependent Brain Stimulation with Real-time Electroencephalography-Triggered Transcranial Magnetic Stimulation
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Improving an open-source commercial system to reliably perform activity-dependent stimulation.

Maxwell Murphy1,2, Stefano Buccelli3,4, Yannick Bornat5

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Summary

This study improved activity-dependent stimulation (ADS) for brain injury recovery by enhancing spike detection accuracy in rats. The open-source system ensures reliable neural circuit stimulation, aiding neuroprosthetic research.

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Activity-dependent stimulation (ADS) shows promise for neurophysiological reorganization after brain injury.
  • Effective ADS requires accurate spike detection and low-latency stimulation delivery.
  • Existing systems face challenges with noise and biological artifacts in awake, behaving animals.

Purpose of the Study:

  • To enhance noise rejection in a low-cost commercial system for reliable ADS in awake, behaving rats.
  • To maintain strict latency requirements for spike detection and stimulation delivery.
  • To improve the feasibility of ADS for promoting recovery from brain injury.

Main Methods:

  • Implemented a spike detection state machine on a field-programmable gate array (FPGA).
  • Developed a waveform tracking system with programmable thresholds to reject biological artifacts.
  • Utilized offline analyses to evaluate system performance in simulated noisy conditions.

Main Results:

  • The FPGA-based system achieved 72%–97% accuracy in triggering stimulation during artifact epochs.
  • Demonstrated a fixed computational latency of 167 µs and algorithmic latency of 300 µs–800 µs.
  • Successfully filtered biological artifacts to enable reliable spike detection.

Conclusions:

  • The improved system reliably performs ADS in awake, behaving rats, overcoming biological artifact challenges.
  • Open-source availability facilitates adoption in closed-loop neuroprosthetic research.
  • The enhancements are easily integrated into existing Intan Stimulation and Recording Controller workflows.