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The brain-machine interface (BMIs) has the potential for the restoration of the sensory and the motor function in people with neurological and clinical disorders.

Based on the white paper, Neuralink develops ultra-high bandwidth brain-machine interfaces to connect humans and computers. 

The BMI has a high-channel count and a single-spike resolution based on the flexible polymer probes, a robotic insertion system, and a custom low-power electronics. 

The system uses a form of wired connection to maximize the bandwidth for raw data streaming for performance assessments and development of the signal processing and decoding algorithms.

Interestingly, clinical devices that will be used on this platform have to be fully implantable and needs hermetic packaging, have on-board signal compression, a reduced power consumption, wireless power transmission, and a data telemetry through the skin without percutaneous leads.

Thread implantation and packaging. A. An example peri-operative image showing the cortical surface with implanted threads and minimal bleeding. B. Packaged sensor device (“System B”) chronically implanted in a rat.

The BMI will consist of arrays of small and flexible electrode “threads”, with as many as 3,072 electrodes per array distributed across 96 threads.

Additionally, there is the neurosurgical robot that is capable of inserting six threads (192 electrodes) per minute. Each of the thread can be individually inserted into the brain with micron precision for avoidance of surface vasculature and targeting specific brain regions.

These electrode arrays are packaged into small implantable device that contains custom chips for low-power on-board amplification and digitization. For example, the package for 3,072 channels occupies less than (23 × 18.5 × 2) mm3.

One single USB-C cable provides a full-bandwidth data streaming from the device, recording from all channels simultaneously.

The robotic electrode inserter; enlarged view of the inserter-head shown in the inset. A. Loaded needle pincher cartridge. B. Low-force contact brain position sensor. C. Light modules with multiple independent wavelengths. D. Needle motor. E. One of four cameras focused on the needle during insertion. F. Camera with wide angle view of surgical field. G. Stereoscopic cameras.

Furthermore, The system has been found to have achieved a spiking yield of up to 85.5 % in chronically implanted electrodes. This is because Neuralink’s approach to BMI has unprecedented packaging density and scalability in a clinically relevant package.

Therefore, to satisfy the functional requirements for a high-bandwidth BMI, the Neuralink takes advantage of the properties of the thin-film devices, using the robotic approach. The approach works whereby large numbers of fine and flexible polymer probes are efficiently and independently inserted across multiple brain regions.

The BMI system has been identified to possess various advantages for its application, for instance;

1) The size and the composition of the thin-film probes are a better match for the material properties of brain tissue than the commonly used silicon probes, thereby exhibiting enhanced biocompatibility.

2) The ability to choose where the probes are to be inserted into the sub-cortical structures, will allow one to create custom array geometries for targeting specific brain regions while avoiding vasculature creating high-performance BMI, as the distribution of electrodes can be customized depending on the task requirements.

3) Also, the miniturization and the design of the Neuralink ASIC affords great flexibility in system design and supports very high channel counts within practical size and power constraints.

Neuralink ASIC: A packaged sensor device. A. individual neural processing ASIC capable of processing 256 channels of data. This particular packaged device contains 12 of these chips for a total of 3,072 channels. B. Polymer threads on parylene-c substrate. C. Titanium enclosure (lid removed). D. Digital USB-C connector for power and data.

It is evident that the Neuralink ASIC will be important in modulating the neural activity for the next-generation clinical brain-machine interfaces. When combined with a rapidly improving spinal stimulation techniques, the approach could restore motor function.

Sources and references: Elon Musk, Neuralinkdoi: https://doi.org/10.1101/703801. https://www.biorxiv.org

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