DOI: https://doi.org/10.29363/nanoge.neumatdecas.2023.018
Publication date: 9th January 2023
The dream of building a neural inspired platform that offers the adaptability of biology, coupled with the reproducibility of traditional hardware, has made considerable progress in the neuromorphic field[1]. Yet, substantial barriers remain that will require new perspectives and approaches to overcome. Revisiting the basics of how biological neurons behave may offer a window to achieve these next steps. Framing modern neuroscientific understandings in the light of recent breakthroughs in developing Synthetic Biological Intelligence (SBI) offers one pathway to progress. Recent work[2] by our group has enabled a monolayer of neurons to dynamically adapt behavior in a goal-directed manner in simulated game-worlds - such as a simplified version of pong. It was found that neural cells from both human and mouse sources could be embodied using electrophysiological recording and stimulation to form a real-time closed loop environment. Implications from the Free Energy Principle were tested to determine whether these neurons would display a rudimentary form of intelligence to show learning by improving at the game. Extending beyond basic performance, the underlying electrophysiological network activity changes that occurred provides insight into the fundamental features that drive intelligence in neural systems. Coupled with the high sample efficiency and network wide adaptability of these living neurons, this data provides compelling implications that may be useful in future neuromorphic engineering efforts.
Acknowledgements are offered to the Cortical Labs team and collaborators for their support and involvement in all past and ongoing research, in particular Dr Alon Loeffler for their advice with this presentation.
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