A Miniaturized 256-Channel Neural Recording Interface With Area-Efficient Hybrid Integration of Flexible Probes and CMOS Integrated Circuits
Sung‐Yun Park, Kyounghwan Na, Mihály Vöröslakos, Hyunsoo Song, Nathan Slager, Sungjin Oh, John P. Seymour, György Buzsáki, Euisik Yoon
Abstract
We report a miniaturized, minimally invasive high-density neural recording interface that occupies only a 1.53 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> footprint for hybrid integration of a flexible probe and a 256-channel integrated circuit chip. To achieve such a compact form factor, we developed a custom flip-chip bonding technique using anisotropic conductive film and analog circuit-under-pad in a tiny pitch of 75 μm. To enhance signal-to-noise ratios, we applied a reference-replica topology that can provide the matched input impedance for signal and reference paths in low-noise aimpliers (LNAs). The analog front-end (AFE) consists of LNAs, buffers, programmable gain amplifiers, 10b ADCs, a reference generator, a digital controller, and serial-peripheral interfaces (SPIs). The AFE consumes 51.92 μW from 1.2 V and 1.8 V supplies in an area of 0.0161 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> per channel, implemented in a 180 nm CMOS process. The AFE shows > 60 dB mid-band CMRR, 6.32 μV <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rms</sub> input-referred noise from 0.5 Hz to 10 kHz, and 48 MΩ input impedance at 1 kHz. The fabricated AFE chip was directly flip-chip bonded with a 256-channel flexible polyimide neural probe and assembled in a tiny head-stage PCB. Full functionalities of the fabricated 256-channel interface were validated in both <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vitro</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vivo</i> experiments, demonstrating the presented hybrid neural recording interface is suitable for various neuroscience studies in the quest of large scale, miniaturized recording systems.