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StriX Neurotech Debuts CereLite Animal EEG/EMG System at CNS 2026

Brain-Computer Interface (BCI) firm BrainCo debuted its self-developed CereLite small animal EEG/EMG collection and analysis system at the 19th Annual Academic Meeting of the Chinese Neuroscience Society (CNS 2026), according to reports from Xinmin Evening News. The system…

Brain-Computer Interface (BCI) firm BrainCo debuted its self-developed CereLite small animal EEG/EMG collection and analysis system at the 19th Annual Academic Meeting of the Chinese Neuroscience Society (CNS 2026), according to reports from Xinmin Evening News. The system is designed for long-term, stable neurophysiological recording in freely moving small animals.

The annual conference, held in China, brought together thousands of domestic and international experts and scholars to discuss frontier breakthroughs in neuroscience. Within that setting, BrainCo introduced CereLite as an integrated hardware and software platform built to handle continuous multi-day experiments under natural behavioral conditions, according to event coverage.

Hardware Architecture of the CereLite System

The CereLite platform features a comprehensive hardware configuration designed to support direct in vivo electrophysiological experiments on small animals. According to technical specifications detailed by Xinmin Evening News, the system comprises seven core components:

  • NSPL8 Host
  • NSPR Remote Processor
  • NSPA Preamplifier
  • LiteCB Amplifier Connection Cable
  • LiteRing Micro Low-Noise Commutator
  • LiteHome Dedicated Silent Experimental Cage
  • ME Lite Professional Collection and Analysis Software Platform

According to project developers speaking with Xinmin Evening News, a single system host supports simultaneous recording for up to eight small animals, streamlining throughput for laboratory environments.

Automated Sleep Staging and Data Processing

Traditional sleep studies often require intensive labor for overnight recording, manual staging annotations, and statistical organization. CereLite addresses this bottleneck by incorporating a dual-engine processing architecture that combines deep learning convolutional neural networks (CNN) with classical threshold algorithms, as reported by Xinmin Evening News.

The software automatically categorizes states into wakefulness (WAKE), non-rapid eye movement (NREM), and rapid eye movement (REM) sleep stages. This automation generates immediate sleep structure reports. Furthermore, the software integrates experimental group parameters to execute group-level statistical analyses, producing publication-ready charts directly from the platform.

Support for Closed-Loop Experimental Research

Beyond observational studies, the system accommodates advanced experimental setups. According to reporting from Xinmin Evening News, CereLite provides real-time sleep state detection paired with synchronized transistor-transistor logic (TTL) signal output. This functional capability establishes a dedicated pathway for closed-loop regulation experiments within neuroscience research.

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