Scalable microelectrode arrays: moving beyond time division multiplexing
Sean Weaver, Yiyang Chen, Aline Renz, Woojun Choi, Yashwanth Vyza, Tilman Schlotter, Katarina Vulić, Donghwan Kim, Gabriele Atzeni, Dmitry Momotenko, Nako Nakatsuka, Taekwang Jang, János Vörös · Bernstein Conference 2024
Expanding use of large-scale neural recordings has led to paradigm shifts in how neural computation is understood [1]. Technologies used for collecting these datasets face fundamental limitations ranging from power dissipation, penetration depth, and resolution [2] while facing additional practical challenges related to sensor integration with the subject or patient. While the ultimate goal of simultaneously recording from every neuron in the brain is far out of reach, more modest advancements still need to be made to ensure the proper neural coverage is achieved to construct a sufficient app