In vitro neurons learn and exhibit sentience when embodied in a simulated game-world.
In vitro neurons learn and exhibit sentience when embodied in a simulated game-world.
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DOI：
10.1016/j.neuron.2022.09.001
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发表时间：
2022-12-07
期刊：
影响因子：
16.2
通讯作者：
Friston, Karl J.
中科院分区：
文献类型：
--
作者：
Kagan, Brett J.;Kitchen, Andy C.;Tran, Nhi T.;Habibollahi, Forough;Khajehnejad, Moein;Parker, Bradyn J.;Bhat, Anjali;Rollo, Ben;Razi, Adeel;Friston, Karl J.
将神经元集成到数字系统中可能会实现单独使用硅无法实现的性能。在这里，我们开发了 DishBrain，这是一个利用结构化环境中神经元固有的自适应计算的系统。来自人类或啮齿动物的体外神经网络通过高密度多电极阵列与计算机计算集成。通过电生理刺激和记录，文化被嵌入到模拟游戏世界中，模仿街机游戏“乒乓球”。通过自由能原理应用主动推理理论的含义，我们发现在控制条件下观察不到的实时游戏五分钟内明显的学习。进一步的实验证明了闭环结构化反馈在随着时间的推移引发学习方面的重要性。文化表现出以目标导向的方式自组织活动的能力，以响应有关其行为后果的稀疏感官信息，我们将其称为合成生物智能。未来的应用可能会提供对智能的细胞相关性的进一步见解。随着时间的推移，闭环反馈后性能或“学习”的改善 从人类和原代小鼠皮层神经元观察到的学习 有刺激但无反馈的系统显示没有学习 在实施过程中观察到神经电生理活动的动态变化 DishBrain 系统是第一个实时合成生物智能平台，它证明生物神经元可以以某种方式调整发射活动，表明在游戏世界中提供简单的电生理感觉输入和反馈时，生物神经元能够学习执行面向目标的任务。
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. Improvements in performance or “learning” over time following closed-loop feedback Learning observed from both human and primary mouse cortical neurons Systems with stimulus but no feedback show no learning Dynamic changes observed in neural electrophysiological activity during embodiment The DishBrain system is the first real-time synthetic biological intelligence platform that demonstrates that biological neurons can adjust firing activity in a way that suggests the ability to learn to perform goal-oriented tasks when provided with simple electrophysiological sensory input and feedback while embodied in a game-world.
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