A new tool called the Apollo implant makes it possible to reversibly implant Neuropixel probes to track hundreds of neurons over a long period. Image credit: Bimbard et al. (CC BY 4.0)
Certain cognitive processes, such as learning, develop over relatively long periods (hours or days). Others, including navigation – the ability to move through a space based on our knowledge of it – usually take place when the subject is free to explore its environment. This can make studying these processes challenging, as researchers need to record brain activity for long periods and in freely moving subjects.
Electrophysiology allows researchers to record brain activity at the millisecond timescale, but technical constraints have made it difficult to record more than a few neurons for any length of time. However, a set of electrophysiology probes called Neuropixels have been developed to allow the recording of hundreds of neurons at once. These probes can be permanently implanted in the brain to track neural activity over long periods. Unfortunately, these implants make it impossible to recover the probes, making their use too expensive for most researchers.
To address this issue, Bimbard et al. set out to develop an implant that would allow the reversible implantation of Neuropixel probes, allowing researchers to track hundreds of cells at fast timescales and over long periods. The device they developed, called the Apollo implant, is a lightweight, reusable device with an open-source design that can be adjusted to suit experimental needs.
Bimbard et al. combined data from eight independent laboratories using the Apollo implant to demonstrate that it can be easily reproduced and modified. These data show that the implant can measure neural data stably for over 100 days after the initial implantation. Additionally, Bimbard et al. show that it is possible to reimplant the same probes many times without losing recording quality.
The Apollo implant makes long-term tracking of groups of neurons reliable and affordable, which will facilitate cognition studies across different model systems.
