High-resolution recordings of electrical signals from the surface of the brain could provide neurosurgeons with the capability to extract brain tumors and treat epilepsy, unlocking new potentialities for medium- and long-term brain-computer interfaces.
Led by University of California San Diego researchers, a collaborative team of neurosurgeons, engineers, and medical academics have published new data from rats and humans showing how these brain sensors sophisticatedly record electrical brain signals in record-breaking detail.
The novel brain sensors are made up of an array of embedded electrocorticography (ECoG) sensors densely packed into grids of either 1,024 or 2,048. Published in the journal Science Translational Medicine, the paper describes how the technology could transform clinical mapping and research with brain-machine interfaces.
If authorized for clinical use, these new brain sensors would theoretically provide neuroscientists with brain-signal information directly from the brain’s cortex at resolutions that exceed what is currently available by up to100x.
This could improve guidance and protocols leading to surgeries for the removal of brain tumors. Furthermore, long-term access to this detailed perspective on which particular areas of the cerebral cortex, or brain tissue, are active and when could also enable the surgical treatment of drug-resistant epilepsy.
Additionally, the new brain sensor technology could also improve the lives of people who suffer from neurodegenerative diseases or varying forms of paralysis as there is scope for permanent implantation and treatment via electrical stimulation.
Neurosurgeons are already using sensors to record brain activity when undertaking brain tumor removal procedures or treating drug-resistant epilepsy. However, these sensors only contain between 16 and 24 ECoG sensors.
Hence, when compared to the 1,024 or 2,048 possible with the new brain sensors, resolutions are limited in the existing technology.
Another key feature of the new sensors is that damage to healthy tissue could be minimized. Recording so much information at such high resolutions means that tumors could effectively be removed, thus preserving as much healthy tissue as possible.
Recording brain signals at such high resolutions is made possible due to the ability to position sensors so close together while mitigating interference. Existing ECog grids are typically 1 cm apart, while the new brain sensors are just 1 mm. Thus for grids with 100 sensors per unit area, the resolution would be 100 times better.
The novel application of platinum is also driving the technology as nanoscale platinum rods deliver more sensing surface area than conventional flat platinum sensors. This heightens the sensitivity of the new brain sensors.
The platinum nano-rods can accurately record where neurons are firing on or at the surface of the cerebral cortex close to real-time. So, as charged ions pass through a neuron when it fires, this results in a changing voltage potential in the cerebrospinal fluid that the neurons are bathed in.
As the human brain is consistently in flux with each flow of blood generated by the heartbeat, the new brain sensors must be able to move in sync with the brain. The flexibility and thinness of the new brain sensors enable the sensor grids to travel with the brain, facilitating better connections and enhanced readings.
The platinum nano-rod-based sensor grids also allow more precise functional mapping, which addresses one of the challenges of removing brain tumors – changing what areas of the brain are involved in what functions.
Going forward, the team aims to gain approval and develop the technology for long-term use, focusing on developing the sensing system further and taking the next step – a clinical trial for people with treatment-resistant epilepsy.
References and Further Reading
Kane, D., (2022) New Sensor Grids Record Human Brain Signals in Record-Breaking Resolution. [online] Ucsdnews.ucsd.edu. Available at: https://today.ucsd.edu/story/new-sensor-grids-record-human-brain-signals-in-record-breaking-resolution
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