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ARViS Robotic System Enhances Precision in Brain Studies

In a recent article published in Nature Communications, researchers introduced an innovative automated robotic virus injection system (ARViS) for precise, fast, and bleed-free delivery of viruses to the cerebral cortex of living mice and marmosets. This device aims to address the limitations of manual injection, facilitating more precise and consistent studies of brain function and neurological disorders.

ARViS Robotic System Enhances Precision in Brain Studies
Study: ARViS: a bleed-free multi-site automated injection robot for accurate, fast, and dense delivery of virus to mouse and marmoset cerebral cortex. Image Credit: Gorodenkoff/Shutterstock.com

Background

Viral vectors/injections, such as adeno-associated viruses (AAVs) and lentiviruses, are commonly used in neuroscience to deliver genetically encoded sensors and actuators to specific brain regions.

These tools help study gene functions and their roles in neurological processes by monitoring and manipulating neuronal and glial activity with high precision.

For example, genetically encoded calcium indicators (GECIs) track neuronal activity, while optogenetic tools control neurons with light. However, manual viral infections are labor-intensive and prone to errors, often causing bleeding, tissue damage, and inconsistent viral delivery. These issues can impact research accuracy and reliability, highlighting the need for a more effective method.

About the Research

In this paper, the authors developed and tested ARViS. This system combines image recognition and robotic control for precise, bleed-free virus injections into the cerebral cortex of rodents and non-human primates (NHPs). ARViS uses image recognition to map cortical blood vessels and identify safe injection sites, and robotic control to insert a micropipette with 50 μm precision.

To ensure accuracy, the researchers created a deep learning-based convolutional neural network (CNN) called the Spatial Attention U-Shaped Encoder-Decoder Network (SA-UNet).

This network detects blood vessels on the cortical surface and adjusts the injection path in real time to avoid vessels and reduce bleeding risk. CNN was trained with retinal and cortical surface images to identify narrow and thick blood vessels accurately.

The study also addressed the challenge of controlling the micropipette's position and orientation during the injection process. A robust calibration procedure corrected errors in the robot's movements and compensated for cortical surface deformation, allowing for precise targeting. The pipette tip was consistently positioned within 50 μm of the target site.

For precise insertion, ARViS employed a six-degrees-of-freedom robot equipped with a laser distance sensor and a CMOS camera. The system’s movements were calibrated for high accuracy, with a tool center point (TCP) calibration process minimizing positioning errors. The closed-loop function ensured real-time vessel avoidance during injections, enhancing precision and safety.

Research Findings

The ARViS system was tested in mice and marmosets. In mice, 100 injections were completed in 100 minutes with a bleeding rate of 0.1% per site. Injection precision was confirmed using a fluorescent dye, showing an average misalignment of 50 μm.

Additionally, the successful expression of GCaMP6s, a genetically encoded calcium indicator, in the mouse cortex without noticeable cell death demonstrated the system's effectiveness.

In marmosets, ARViS performed 266 injections in the frontoparietal cortex with zero bleeding incidents. Wide-field one-photon calcium imaging in an awake marmoset showed distinct neuronal representations of orofacial and body movements, confirming broad and uniform fluorescence expression. This highlighted the system's capability to achieve large-scale biosensor expression with minimal tissue damage.

ARViS also demonstrated a high degree of spatial and temporal precision. The system could target specific brain regions with a spatial resolution of 50 μm and a temporal resolution of 1 second, surpassing the accuracy of manual injection methods. This precision is crucial for studying complex neural circuits and neurological processes and disorders.

Furthermore, the authors validated the accuracy of ARViS by tracing micropipette trajectories with fluorescent dyes. The results indicated that the pipette tip was consistently positioned within 50 μm of the target depth, with a lateral offset of only 38 μm, showcasing the exceptional precision and reliability of the system.

Applications

The proposed robotic system has significant potential for advancing neuroscience research by enabling high-precision viral injections into targeted brain regions. This technology offers novel opportunities to study gene functions in neurological processes and disorders.

By automating virus injections, ARViS reduces the time and effort needed for such procedures, making it suitable for large-scale studies. The increased precision supports detailed investigations of neural circuits, helping researchers understand cognitive, sensory, and motor functions, as well as neurodegenerative diseases like Alzheimer’s, Parkinson’s, and Huntington’s.

Its minimally invasive design reduces bleeding and tissue damage, improving the reliability and reproducibility of experiments. This can help develop more effective therapeutic interventions and advance brain research.

Conclusion

In summary, ARViS proved to be a transformative tool in neuroscience, allowing for broad biosensor expression across multiple cortical areas in NHPs. Its ability to perform accurate, rapid, and targeted virus injections with minimal bleeding risk offers new possibilities for studying cortical activity.

This advancement could revolutionize neuroscience research by enabling more reliable and reproducible investigations into brain function and neurological disorders.

Future work should address limitations like lengthy calibration times and limited pipette volume capacity to enhance ARViS’s efficiency and expand its applications in neuroscience research.

Journal Reference

Nomura, S., Terada, SI., Ebina, T. et al. ARViS: a bleed-free multi-site automated injection robot for accurate, fast, and dense delivery of virus to mouse and marmoset cerebral cortex. Nat Commun 15, 7633 (2024). DOI: 10.1038/s41467-024-51986-3, https://www.nature.com/articles/s41467-024-51986-3

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Muhammad Osama

Written by

Muhammad Osama

Muhammad Osama is a full-time data analytics consultant and freelance technical writer based in Delhi, India. He specializes in transforming complex technical concepts into accessible content. He has a Bachelor of Technology in Mechanical Engineering with specialization in AI & Robotics from Galgotias University, India, and he has extensive experience in technical content writing, data science and analytics, and artificial intelligence.

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