AI-driven high-throughput automation of behavioral analysis and dual-channel wireless optogenetics for multiplexing brain dynamics Institutional Repository Document uri icon


  • AbstractAdvances in behavioral optogenetics are limited by the absence of high-throughput pipelines for the automated analysis of behavior in freely behaving animals. Although a variety of AI algorithms has been proposed that enable automation of behavioral analysis, existing methods are generally low-throughput. In addition, optogenetic manipulation of neural circuits typically requires physical tethers to light sources, which limits the number of brain areas that can be targeted and thus constrains behavioral testing. Here, we develop a new wireless platform that combines a battery-free dual-channel optogenetic implant with an AI algorithm for high-throughput behavioral analysis. In our platform, a customized AI algorithm detected and quantified freezing behavior of rats that had undergone fear conditioning. Notably, our platform allows up to four enclosures to be monitored simultaneously. Wireless dual-channel optogenetic devices were implanted in the basolateral amygdala (BLA) to permit independent modulation of BLA principal neurons (red light, AAV-CaMKII-JAWS) or BLA interneurons (blue light, AAV-mDlx-ChR2) in freely behaving animals. In vivo validation with behaving rats demonstrates the utility of the telemetry system for large-scale optogenetic studies.SignificanceAI algorithms can enable automation of behavioral analysis and thereby facilitate the progress on behavioral optogenetics. Successful integration of advanced wireless dual-channel optoelectronic devices with biological systems can also yield new tools and techniques for neuroscience research, particularly in the context of techniques for optogenetics. Here, we propose a new approach that combines an advanced AI algorithm with a low power wireless telemetry system, yielding powerful capabilities in the understanding of brain functions and the evaluation of the behavioral consequences of neural circuit manipulations. In vivo studies using optimized systems demonstrate high-throughput automation of behavioral manipulation and analysis via AI-powered wireless telemetry.

altmetric score

  • 0.5

author list (cited authors)

  • Kim, W. S., Liu, J., Li, Q., Hong, S., Qi, K., Cherukuri, R., ... Park, S. I.

citation count

  • 0

complete list of authors

  • Kim, Woo Seok||Liu, Jianfeng||Li, Qinbo||Hong, Sungcheol||Qi, Kezhuo||Cherukuri, Rahul||Yoon, Byung-Jun||Moscarello, Justin||Choe, Yoonsuck||Maren, Stephen||Park, Sung Il

Book Title

  • bioRxiv

publication date

  • September 2021