3D Neural Network Composed of Neurospheroid and Bionanohybrid on Microelectrode Array to Realize the Spatial Input Signal Recognition in Neurospheroid. Issue 8 (20th May 2022)

• Record Type: Journal Article
• Authors: Yoon, Jinho; Kim, Hyun‐Woong; Shin, Minkyu; Lim, Joungpyo; Lee, Ji‐Young; Lee, Sang‐Nam; Choi, Jeong‐Woo
• Is Part Of: Small methods. Volume 6:Issue 8(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-05-20
• Subjects: 3D neural networks -- 3D neurospheroids -- bioelectronics -- bionanohybrids -- electrophysiological signals; Nanotechnology -- Methodology -- Periodicals; Nanotechnology -- Periodicals; Periodicals; 620.5028
• DOI: 10.1002/smtd.202200127
• Languages: English
• ISSNs: 2366-9608

Abstract

Abstract: There have been several studies for demonstration of 2D neural network using living cells or organic/inorganic molecules, but to date, there is no report of development of a 3D neural network in vitro. Based on developed bionanohybrid composed of protein, DNA, molybdenum disulfide nanoparticles, and peptides for controlling electrophysiological states of living cells, here, the in vitro 3D neural network composed of the bionanohybrid, 3D neurospheroid and the microelectrode array (MEA) is developed. After production of the 3D neurospheroid derived from human neural stem cells, the bionanohybrid developed on the MEA successfully semi‐penetrates the neurites of the 3D neurospheroid and forms the 3D neural network. The developed 3D neural network successfully exhibited the electrophysiological output signals of the 3D neurospheroid by transmitting the input signal applied by the bionanohybrid. Moreover, by using the selectively immobilized bionanohybrid on the MEA, the spatial input signal recognition in the neurospheroid of 3D neural network is realized for the first time. This newly developed in vitro 3D neural network provides a promising strategy to be applied in brain‐on‐a‐chip, brain disease‐related drug efficacy evaluation, bioelectronics, and bioelectronic medicine. Abstract : A novel method is proposed for developing an in vitro 3D neural network composed of the bionanohybrid, 3D neurospheroid, and the microelectrode array corresponding to 'Input layer', 'Hidden layer', and 'Output layer' in the classical neural network. In the developed 3D neural network, the spatial input signal recognition in the 3D neurospheroid was realized and measured as spatially recognized electrophysiological output signals.