Micromechanical Engineering of Connectivity in Living Neural Networks

为了促进生物信息处理理论的发展，有一个允许神经网络中连接的先验规范的系统将是有用的。 通过定义神经网络中的连通性，该系统将允许任意神经元架构的快速原型。 理想情况下，这样的系统不仅能够重现体内结构，而且能够以用户定义的方式创建新的神经结构。 这样的用户定义的网络将允许更严格的测试神经系统中的生物信息处理的理论，并可能导致识别新的信息处理范式。 在这个项目中，以下问题将被解决：a）确定成功的神经突起诱导下施加的力量的决定因素。B）比较工程网络的行为模型网络的行为，以评估神经元的信息处理是线性还是非线性的。c）发展的方法，以扩大规模，允许形成多个连接。

To facilitate the development of theories for biological information processing, it would be useful to have a system that permits a priori specification of the connection in a neural network. By defining the connectivity in a neural network, the system will allow rapid prototyping of arbitrary neuronal architectures. Ideally, such a system would be able to not only recapitulate in vivo structure, but also be able to create novel neural structures in a user-defined manner. Such user-defined networks will then allow more rigorous testing of theories for biological information processing in the nervous system and will potential result in the identification of novel information processing paradigms in general. In this project, the following issues will be addressed:a) Identify the determinants of successful neurite elicitation under applied force.b) Compare engineered network behavior to model network behavior to assess whether neuronal information processing is linear or nonlinear.c) Develop approaches to scale-up that allow multiple connections to be formed.