Investigating Symbolic Computation in the Brain: Neural Mechanisms of Compositionality

项目总结/摘要 动物表现出一系列非凡的创造性、适应性和灵活性行为。鸟类和灵长类动物 新的材料来建造巢穴和工具;老鼠有效地构建导航捷径，人类概括 一种语言的知识，以有效地说另一种语言。这种动态地创造新奇行为的能力， 或几次试验往往取决于成分规划，或产生有限的新组合的能力， 以目标为导向的简单元素的数量。尽管它对于理解 认知及其障碍，组合性的神经机制仍然未知，因为缺乏 实验框架，用于研究组合规划。为了满足这一迫切需要， 方法，这个建议将阐明神经机制，在一个新的绘画任务，我已经制定了在 在弗赖瓦尔德实验室，猕猴可以画出以前从未见过的视觉图形的复制品。受试者行为 在构建先前学习的新组合的能力中表现出组合性的关键特征 元素来绘制新图像。我将研究合成动作的神经和计算机制 计划通过整合这一行为任务的其他两个创新：（1）大规模记录在12个正面 皮质区域，每个区域都与认知有关，但从未同时记录，这将使我能够发现 它们的不同功能如何联合收割机来支持认知（目标1），以及（2）一个综合分析框架 建立和比较神经网络（目标2）和符号（目标3）计算模型的组成 利用行为和神经数据进行规划。我将检验主要假设，即组合性取决于 在分层组织的额叶皮层区域执行符号认知算法的神经动力学。 这些研究有望在神经基质和动力学方面发现 组合行动计划此外，由于这些研究的交叉方法-测试神经 网络（目标2）和符号（目标3）建模框架在相同的数据-他们可以统一这两个 有影响力的认知方法，这将是神经科学的基础性进展， 智能相应地，本研究将有助于理解认知障碍，包括额叶 规划障碍，以及建立大脑-机器接口，从皮层活动中解码认知计划。 这个奖项也将为我提供重要的培训，为我过渡到独立做好准备。我会训练 在计算建模-建设，实证测试，并解释这些模型-这将支持我的 使用模型来生成和测试新的神经回路和计算假设。我将获得重要的 在实验室管理和领导，科学沟通，和拨款写作的职业发展技能， 这将支持我建立一个独立的神经基质研究计划的长期目标， 智力和创造性行为的基础。

PROJECT SUMMARY/ABSTRACT Animals exhibit a remarkable array of creative, adaptive, and flexible behaviors. Birds and primates repurpose new materials to build nests and tools; rats efficiently construct navigational shortcuts, and humans generalize knowledge of one language to efficiently speak another. This ability to dynamically create novel behavior in one or a few trials often depends on compositional planning, or the ability to generate new combinations of a finite number of simple elements in a goal-directed manner. Despite its central importance for understanding cognition and its disorders, the neural mechanisms of compositionality remain unknown as there is a dearth of experimental frameworks for studying compositional planning. To address this critical need for new approaches, this proposal will elucidate neural mechanisms in a novel drawing task that I have developed in the Freiwald lab, in which macaques draw copies of never-before-seen visual figures. Subjects’ behavior exhibits a key signature of compositionality in the ability to construct novel combinations of previously learned elements to draw new images. I will investigate neural and computational mechanisms for compositional action planning by integrating this behavioral task two other innovations: (1) large-scale recordings in 12 frontal cortical areas, each implicated in cognition but never recorded simultaneously, which will allow me to discover how their distinct functions combine to support cognition (Aim 1), and (2) an integrative analysis framework building and comparing neural network (Aim 2) and symbolic (Aim 3) computational models of compositional planning with behavioral and neural data. I will test the main hypothesis that compositionality depends on neural dynamics implementing symbolic cognitive algorithms in hierarchically organized frontal cortical areas. These studies are expected to discover the first mechanisms, in neural substrates and dynamics, of compositional action planning. Further, because of these studies’ intersectional approach - testing neural network (Aim 2) and symbolic (Aim 3) modeling frameworks on the same data - they may unify these two influential approaches to cognition, which would be a foundational advance for the neuroscience of intelligence. Correspondingly, this study will contribute to understanding cognitive disorders, including frontal planning disorders, and to building brain-machine interfaces that decode cognitive plans from cortical activity. This award will also provide me with crucial training to prepare me for transitioning to independence. I will train in computational modeling - building, empirically testing, and interpreting these models - which will support my use of models to generate and test novel neural circuit and computational hypotheses. I will gain important career development skills in lab management and leadership, scientific communication, and grant writing, which will support my long term goal of establishing an independent research program on the neural substrates of intelligence and creative behavior.