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Related Experiment Video

Updated: Apr 29, 2026

Author Spotlight: Advancements in Multichannel Extracellular Recording for Studying Neuronal Activity in Freely Moving Mice
08:59

Author Spotlight: Advancements in Multichannel Extracellular Recording for Studying Neuronal Activity in Freely Moving Mice

Published on: May 26, 2023

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A multi-region flexible neural interface for behavioral state decoding in freely moving mice.

Ye Tian1,2,3,4, Gen Li1,2,3,4,5, Haoyang Su1,2,3,4

  • 1State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China.

Microsystems & Nanoengineering
|April 27, 2026
PubMed

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Summary

Researchers developed a new platform for stable, whole-brain recordings and decoding of neural activity. This technology enhances accuracy and generalizability for neuroscience research and therapies.

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Bioengineering

Background:

  • Decoding whole-brain function requires high-density, long-term stable neural interfaces.
  • Existing methods face challenges in scalability, long-term stability, and algorithm generalizability across time and subjects.

Purpose of the Study:

  • To develop an integrated platform for accurate, stable, and generalizable decoding of behavioral states from whole-brain activity.
  • To address limitations in current neural recording and decoding technologies.

Main Methods:

  • Development of multi-region flexible probes (MRFPs) for distributed, long-term recordings (months) from 128 sites across eight brain regions.
  • Implementation of a Conformer-based deep learning framework optimized for brain-wide neural dynamics.

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  • Comparative analysis of distributed versus concentrated electrode configurations for decoding performance.

    • Main Results:

    • Achieved accurate (up to 89%) and stable decoding of behavioral states (resting, roaming, feeding, flash).
    • Demonstrated that distributed neural sampling from five or more regions significantly improves decoding performance compared to concentrated configurations.
    • Showcased robust generalization of decoding models across days and individuals without retraining.

    Conclusions:

    • The integrated platform provides a foundation for stable, high-fidelity multi-region electrophysiology.
    • Offers a generalizable approach for decoding internal states from complex neural dynamics, advancing longitudinal and large-scale neuroscience studies.
    • Enables progress in basic neuroscience research and the development of neural disorder therapies.