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Deciphering Neural Mechanisms Underlying Marmoset Dynamic Natural Behaviors Using a Miniaturized Wireless Large-Scale

Hongru Liu1, Xinyuan Cao2, Jiyong Li1

  • 1School of Biomedical Engineering, Tsinghua University, Beijing, 100084, China.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|October 27, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a wireless neural recorder for long-term brain activity monitoring in freely moving marmosets. The device enables detailed analysis of neural dynamics linked to natural behaviors, achieving over 87% accuracy in identifying drinking phases.

Keywords:
freely moving neural recordinghigh‐density flexible µECoG arrayneural dynamics underlying natural behaviorsnon‐human primatewireless neural recorder

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Area of Science:

  • Neuroscience
  • Bioengineering
  • Animal Behavior

Background:

  • Understanding neural mechanisms of natural behaviors requires large-scale, long-term brain recordings.
  • Conventional neural recorders face limitations in weight, coverage, and signal throughput.

Purpose of the Study:

  • To develop and evaluate a miniaturized wireless neural recorder for real-time, large-scale brain activity monitoring.
  • To investigate neural dynamics associated with natural behaviors in freely moving marmosets.

Main Methods:

  • Utilized a custom-designed 120-channel flexible micro-Electrocorticography (µECoG) array in a miniaturized wireless neural recorder.
  • Recorded brain activity from frontal and temporal cortices of freely moving marmosets during various natural behaviors.
  • Applied signal processing and machine learning to analyze spatiotemporal neural dynamics and identify behavioral phases.

Main Results:

  • Observed behavior-specific neural dynamics, including alpha-band activation during drinking and high-gamma increase during vigilance.
  • Successfully identified three phases of drinking behavior with >87% accuracy using multi-area neural features.
  • Demonstrated high signal fidelity and low attenuation over 16 months of continuous recording.

Conclusions:

  • The wireless µECoG recorder enables effective long-term, large-scale neural recordings in freely moving animals.
  • This technology facilitates the dissection of neural mechanisms underlying complex natural behaviors.
  • The findings provide a foundation for future studies on brain function in naturalistic settings.