计算机科学
知觉
推论
具身认知
神经科学
感觉系统
人工智能
生物神经网络
人机交互
机器学习
心理学
作者
Brett J. Kagan,Andy C. Kitchen,Nhi T. Tran,Forough Habibollahi,Moein Khajehnejad,Bradyn J. Parker,Anjali Bhat,Ben Rollo,Adeel Razi,Karl Friston
出处
期刊:Neuron
[Cell Press]
日期:2022-10-12
卷期号:110 (23): 3952-3969.e8
被引量:183
标识
DOI:10.1016/j.neuron.2022.09.001
摘要
Integrating neurons into digital systems may enable performance infeasible with silicon alone. Here, we develop DishBrain, a system that harnesses the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins are integrated with in silico computing via a high-density multielectrode array. Through electrophysiological stimulation and recording, cultures are embedded in a simulated game-world, mimicking the arcade game "Pong." Applying implications from the theory of active inference via the free energy principle, we find apparent learning within five minutes of real-time gameplay not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organize activity in a goal-directed manner in response to sparse sensory information about the consequences of their actions, which we term synthetic biological intelligence. Future applications may provide further insights into the cellular correlates of intelligence.
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