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Related Concept Videos

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Updated: Jun 30, 2026

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
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Published on: May 8, 2021

Cyborg-swarm cooperation and game via affective-based brain-machine interface.

Zirui Chen1, Lin Zhang2,3, Guiyong Chen2,4

  • 1WINDY Lab, Department of Artificial Intelligence, Westlake University, Hangzhou 310030, China.

National Science Review
|June 29, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a closed-loop cyborg swarm using mouse brain activity to control robots. Fear signals from the mouse brain trigger robots to switch strategies, enabling complex bio-hybrid cooperation.

Keywords:
affective statebio-hybrid roboticsbrain–machine interfacecyborg swarmmulti-agent reinforcement learning

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Area of Science:

  • Bio-hybrid systems engineering
  • Neuroscience and robotics integration
  • Affective computing in artificial intelligence

Background:

  • Current cyborg systems lack cognitive state integration, treating animals as passive bio-actuators.
  • Unidirectional control limits the potential for sophisticated bio-machine interaction.
  • Bridging the gap requires systems that respond to an animal's internal state.

Purpose of the Study:

  • To develop a closed-loop cyborg swarm architecture utilizing affective states for robotic control.
  • To enable cognitive-level bio-hybrid cooperation beyond simple stimulus-response.
  • To validate a scalable framework for emotion-modulated cyborg swarms.

Main Methods:

  • Developed a wireless brain-machine interface (BMI) to record mouse amygdala activity.
  • Implemented a dual-threshold algorithm for real-time fear state decoding, rejecting motion artifacts.
  • Designed a dual-mode control framework switching between exploration and interaction based on decoded fear signals.

Main Results:

  • Biological affective signals successfully triggered millisecond-level control authority switching in the cyborg swarm.
  • Heterogeneous robotic swarms (MouseBot, MAV) executed coordinated adversarial defense strategies.
  • Demonstrated complex bio-machine cooperative behaviors in a search-interference game.

Conclusions:

  • Emotion-modulated cyborg swarms represent a paradigm shift towards cognitive-level bio-hybrid cooperation.
  • The developed framework enables dynamic modulation of robotic swarm strategies by biological affective states.
  • This approach opens new avenues for advanced human-animal-robot interaction and collaboration.