2.5D Heterogeneously Integrated Microsystem for High-Density Neural Sensing Applications

Abstract

Heterogeneously integrated and miniaturized neural sensing microsystems are crucial for brain function investigation. In this paper, a 2.5D heterogeneously integrated bio-sensing microsystem with μ-probes and embedded through-silicon-via (TSVs) is presented for high-density neural sensing applications. This microsystem is composed of μ-probes with embedded TSVs, 4 dies and a silicon interposer. For capturing 16-channel neural signals, a 24 × 24 μ-probe array with embedded TSVs is fabricated on a 5×5 mm(2) chip and bonded on the back side of the interposer. Thus, each channel contains 6 × 6 μ -probes with embedded TSVs. Additionally, the 4 dies are bonded on the front side of the interposer and designed for biopotential acquisition, feature extraction and classification via low-power analog front-end (AFE) circuits, area-power-efficient analog-to-digital converters (ADCs), configurable discrete wavelet transforms (DWTs), filters, and a MCU. An on-interposer bus ( μ-SPI) is designed for transferring data on the interposer. Finally, the successful in-vivo test demonstrated the proposed 2.5D heterogeneously integrated bio-sensing microsystem. The overall power of this microsystem is only 676.3 μW for 16-channel neural sensing.

Neural Interfaces for Intracortical Recording: Requirements, Fabrication Methods, and Characteristics

“…The volume of the whole system can be significantly decreased by employing single-chip integration scheme. This can be achieved by the same substrate-integration and through-silicon-vias connectivity (Chou et al, 2014 ; Huang et al, 2014 ; Chang et al, 2015 ). Full system integration was achieved for UEAs integrated with data processing units, power supply, and telemetry link in multi-level hybrid assembly containing flip chip bonding, reflow soldering, and adhesive bonding to form compact standalone package (Kim et al, 2009 ).…”

Integrated neural interfaces

“…Efforts have been made to combine electronics with both rigid and flexible materials that act as substrates for recording and stimulation sites [5]- [13], but the community still lacks a platform technology of this nature that is robust, accessible, and extensible. Existing devices have proven to be difficult and expensive to create, requiring multidisciplinary expertise in materials, physiology, and electronics.…”

“…This article describes a new "Chiplet" approach to integrated neural interfaces that creates modularity, reduces design time and effort, removes failure modes, and facilitates sharing and deployment of technology from different sources. Compared to similar efforts [5], [8], [10], [13], this approach breaks a large multichannel ASIC design into much smaller Chiplets that offer greater modularity and more potential for system optimization, enabled by state-of-the-art assembly and 978-1-5090-6389-5/17/$31.00 ©2017 IEEEpackaging. The Chiplet approach is described here in the context of silicon electrode arrays, but has broad implications for other types of electrodes, optogenetic interfaces, and in vivo imaging.…”