Feasibility of Engineered Neural Networks for Neuro-Restoration After Cortical Stroke

美国有超过800万人患有慢性中风。由此造成的残疾导致公共卫生费用高昂，生活质量下降。由于没有办法令人满意地恢复中风后的功能，新的有效的再生方法是非常需要的。因此，提出了“工程神经网络”（ENN）的概念。ENN被设想包含来自人类成体干细胞的神经元，并被构造成具有精确的输入和反馈回路。这些连接将使ENN与其他大脑和身体区域整合，从而学习行为。最终，这种整合过程可以导致恩斯取代中风受损的大脑和任何相关功能。在实现这一目标之前，第一步是开发一个实验台培养的神经网络（CNN），并验证它可以被训练来执行任意的感觉任务和运动行为。这项研究的成功完成将证明CNN可以被训练来编码任意行为，并与其他大脑和身体区域进行交互。这将证明进一步的研究，以追求恩斯的发展和方法，植入这种系统到中风受损的大脑。 最终，这可能会以功能上有意义的方式恢复大脑资源，这反过来可能会导致中风康复的突破性再生治疗。这项研究还将：（i）促进生物医学工程专业学生和研究实习生的教育和终身学习;（ii）扩大代表性不足群体对神经工程的参与;（iii）提高科学素养。该项目将开发一种新的神经恢复概念“工程神经网络”（ENN），设想包含来自人类诱导多能干细胞（HIPSC）的神经元。ENN将具有由兴奋性和抑制性神经元形成的输入和反馈回路组成的精确结构，以促进中风后与其他大脑/身体区域的通信。通过将ENN与微电子器件连接，将提供一致且精确的兴奋性和抑制性输入模式以及错误驱动的反馈，以训练ENN与其他大脑/身体区域连接并学习任意的人类行为。最终，这可以建立ENN与剩余的中风后大脑的双向通信，从而取代中风受损的皮层和受损的功能。为了衡量这一概念的可行性，第一步是开发一个实验台培养神经网络（CNN），并验证它可以被训练来执行任意的感觉任务和运动行为。科学上，CNN平台可以提供一种研究神经编码和记忆检索基本概念的方法。从神经工程的角度来看，这项研究可能会通知干细胞衍生的神经元组织的最佳设计。如果成功的话，这项研究将证明CNN可以被训练来编码任意行为并与其他大脑和身体区域相互作用，并将证明进一步研究恩斯的发展以及将这种系统植入中风受损大脑的方法是合理的。最终，这项技术可能会以功能上有意义的方式恢复大脑资源，这反过来可能会导致开创性的中风康复再生治疗。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Over 8 million people in the US are living with chronic stroke. The resulting disabilities lead to significant public health costs and decreased quality of life. With no means to satisfactorily restore functions after stroke, new effective regenerative approaches are much needed. Therefore, a new concept of “engineered neural networks” (ENN) is proposed. The ENN is envisioned to contain neurons derived from human adult stem cells and be structured to have precise inputs and feedback loops. These connections will enable the ENN’s integration with other brain and body areas and thereby learn behaviors. Ultimately, this integration process can lead to ENNs replacing stroke-damaged brain and any associated functions. Before this goal can be achieved, the first step is to develop a benchtop testbed cultured neural network (CNN) and verify that it can be trained to perform an arbitrary sensory task and motor behavior. Successful completion of this study would demonstrate that CNNs can be trained to encode arbitrary behaviors and interact with other brain and body areas. This would justify further research to pursue the development of ENNs and methods to implant such systems into the stroke-damaged brain. Ultimately, this may restore brain resources in a functionally meaningful manner, which may in turn lead to ground-breaking regenerative treatments for stroke rehabilitation. This study will also: (i) promote education and lifelong learning in biomedical engineering students and research trainees; (ii) broaden the participation of underrepresented groups in neuroengineering; (iii) increase scientific literacy. This project will develop a novel neurorestorative concept of “engineered neural networks” (ENN) envisioned to contain neurons derived from human induced pluripotent stem cells (HIPSCs). The ENN will have a precise structure consisting of inputs and feedback loops, formed by excitatory and inhibitory neurons, to facilitate communication with other brain/body areas post-stroke. By interfacing the ENN with microelectronics, consistent and precise patterns of excitatory and inhibitory inputs and error-driven feedback will be delivered to train the ENN to interface with other brain/body areas and learn arbitrary human behaviors. Ultimately, this can establish bidirectional communication of the ENN with the remaining post-stroke brain, thereby replacing the stroke-damaged cortex and subserved functions. To gauge the feasibility of this concept, the first step is to develop a benchtop testbed cultured neural network (CNN) and verify that it can be trained to perform an arbitrary sensory task and motor behavior. Scientifically, the CNN platform can provide a means to study basic concepts of neural encoding and memory retrieval. From a neuroengineering perspective, this study may inform the optimal design of stem cell-derived neuronal tissue. If successful, this study would demonstrate that CNNs can be trained to encode arbitrary behaviors and interact with other brain and body areas and would justify further research to pursue the development of ENNs and methods to implant such systems into the stroke-damaged brain. Ultimately, this technology may restore brain resources in a functionally meaningful manner, which may, in turn, lead to ground-breaking regenerative treatments for stroke rehabilitation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.