Identifying the neurostructural determinants of minimal cognition using embodied 3D bioengineered brain models

使用具体的 3D 生物工程大脑模型识别最小认知的神经结构决定因素

• 批准号: RGPIN-2022-04162
• 负责人: Rouleau, Nicolas
• 金额: $ 2.77万
• 依托单位: Algoma University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=764131
• 关键词: Identifying; neurostructural; determinants; minimal; cognition

Cognitive functions are among the most mechanistically complex yet defining features of the human species. In pursuit of neural mechanisms underlying cognition, early investigators correlated neural damage with loss-of-function and stimulated the brains of both humans and non-human animals to map structure-function relationships. These early methods eventually gave way to the contemporary use of animal models to study fine-scale neural circuits associated with animal cognition. Unfortunately, animal models are low-throughput and lack key elements of human physiology. To address these pitfalls, cognitive scientists have started to explore the possibility of measuring cognition in single cells and tissues with notable success. Simple response patterns among the smallest building blocks of life may represent expressions of "minimal cognition" - precursors to complex, high-order cognitive functions. Similarly, the increasingly prevalent view that cognition is fundamentally "embodied" or inextricably linked to brain-body interfaces suggests that sensory-motor feedback loops may be fundamental to intelligence, learning, and decision-making. Therefore, a comprehensive understanding of cognition may require an assessment of its most rudimentary forms as information-processing within embodied tissues. To that end, advances in biomaterials and three-dimensional (3D) neural tissue culture techniques have made it possible to biologically engineer 3D brain tissues in vitro with customizable cytoarchitectures. These bioengineered brain models (BBMs) can be made with both human and non-human tissues, thus overcoming many of the limitations of traditional monolayer cell culture and the inflexibility of genetically-determined animal and organoid brain structure. I have developed a highly tractable and customizable 3D-BBM derived from human induced pluripotent stem cells (iPSC) embedded in silk scaffolds that can be stably cultured for years, displays habituation-like learning responses, and synaptic plasticity. In a recent high-impact review, I predicted that if the 3D-BBM were embodied such that it could output to a motor effector (e.g., muscles, mobile robots) with feedback, displays of minimal cognition would be achievable. The proposed 5-year NSERC DG research program will build on these significant advances in the fields of bioengineering and neurorobotics by integrating 3D-BBMs with computer interfaces to record deep tissue electrophysiological dynamics, achieve embodiment, program response patterns, and display minimal cognitive functions. The main outcomes include transformative in vitro tools for neurocognitive research and the identification of causal mechanisms of minimal cognitive function. The results of the proposed research will also fuel the training of 33 HQP as well as instruct and inform the design of new artificial and hybrid intelligences with commercial and industrial applications.

认知功能是人类物种中机械上最复杂但又是最具定义的特征之一。为了探索认知背后的神经机制，早期的研究人员将神经损伤与功能丧失联系起来，并刺激人类和非人类动物的大脑绘制结构-功能关系图。这些早期的方法最终被现代使用的动物模型所取代，以研究与动物认知相关的精细神经回路。不幸的是，动物模型是低吞吐量的，并且缺乏人类生理学的关键要素。为了解决这些缺陷，认知科学家已经开始探索在单个细胞和组织中测量认知的可能性，并取得了显著的成功。最小的生命构件之间的简单反应模式可能代表了“最小认知”的表达--复杂的、高级认知功能的前驱。同样，越来越流行的观点认为，认知从根本上是“体现的”或与脑-体接口密不可分地联系在一起，这表明感觉-运动反馈环可能是智力、学习和决策的基础。因此，对认知的全面理解可能需要对其最基本的形式进行评估，作为具体组织中的信息处理。为此，生物材料和三维(3D)神经组织培养技术的进步使利用可定制的细胞结构在体外对3D脑组织进行生物工程成为可能。这些生物工程脑模型(BBM)既可以用人类组织也可以用非人类组织制作，从而克服了传统单层细胞培养的许多局限性，以及遗传决定的动物和有机脑组织结构的不灵活性。我已经开发出一种高度易处理和可定制的3D-BBM，它来自嵌入丝质支架中的人类诱导多能干细胞(IPSC)，可以稳定培养多年，表现出习惯化的学习反应和突触可塑性。在最近的一次高影响力的评论中，我预测，如果3D-BBM被实现，它可以输出到带有反馈的运动执行器(例如肌肉、移动机器人)，就可以实现最低限度的认知展示。拟议的为期5年的NSERC DG研究计划将建立在生物工程和神经机器人领域的这些重大进展的基础上，通过将3D-BBM与计算机接口集成，以记录深层组织电生理动力学，实现具体化，编程响应模式，并显示最低认知功能。主要成果包括用于神经认知研究的变革性体外工具和识别最低认知功能的因果机制。拟议的研究结果还将推动对33名HQP的培训，并指导和指导具有商业和工业应用的新的人工智能和混合智能的设计。