Neural Mechanisms for memory-guided visual behavior in humans

项目摘要 记忆使我们能够利用以前的经验来指导现在的行为。剧情的计算模型 记忆提出，回忆过去的事件涉及恢复大脑皮质活动的模式， 在事件发生时触发。虽然有相当多的证据表明早期感觉可以恢复 最近的证据表明，恢复也发生在较高水平的区域，如外顶叶 大脑皮层，这是记忆成功的强烈预测。然而，恢复在横向上的意义 顶叶皮质及其与感觉区域恢复的关系尚不清楚。了解如何 像外侧顶叶皮质这样的区域代表、转换和优先处理来自感觉区域的信息 对于建立分布式大脑网络如何支持健康和功能失调的记忆的完整模型至关重要。 解决这些认识上的差距将需要依赖于创新的功能磁共振成像的多学科方法 分析、计算建模以及整合来自神经成像和电生理学的证据。我的 到目前为止，论文工作使用了功能磁共振成像方法来验证这一假设，即外侧顶叶皮质代表 记忆提取过程中的感觉内容。这项工作已经产生了几个支持这一点的重要结果 并参与了新的功能磁共振成像方法的开发。在拟议的研究和培训中 程序，我将使用视觉编码的计算模型来区分相互竞争的假设 在记忆提取过程中，顶叶皮质的地形图是如何编码空间信息的。这段经历 将提供视觉神经科学和计算建模方面的培训，使我能够在 研究情景记忆的不同方法。在拟议的博士后培训阶段，我将获得 从人体收集的电生理测量的理论和方法培训。这个 功能磁共振成像和电生理测量的结合将使我能够测试关于 记忆信号随着时间的推移在不同的大脑区域传播，并产生统一的发现 在人类和非人类动物系统中进行的研究。这个研究项目有很大的潜力。 对支持记忆提取的大脑皮层机制产生新的理解，以连接发现 跨测量技术，并为衰老和疾病相关记忆的治疗提供信息 精神错乱。我相信，这个研究项目提供的培训将使我能够发展 不同的理论和方法专业知识需要对一套核心的 系统和认知神经科学中的问题。

Project Summary Memory allows us to use previous experience to guide current behavior. Computational models of episodic memory propose that recalling an event from the past involves reinstating patterns of cortical activity that were evoked when the event occurred. While there is considerable evidence for reinstatement within early sensory areas, recent evidence suggests that reinstatement also occurs in higher-level regions, such as lateral parietal cortex, that are strongly predictive of memory success. However, the significance of reinstatement in lateral parietal cortex and its relation to reinstatement in sensory areas is not well understood. Understanding how areas like lateral parietal cortex represent, transform, and prioritize information from sensory areas will be critical to building a full model of how distributed brain networks support healthy and dysfunctional memory. Addressing these gaps in understanding will require a multidisciplinary approach that relies on innovative fMRI analyses, computational modeling, and integrating evidence from neuroimaging and electrophysiology. My dissertation work so far has used fMRI approaches to test the hypothesis that lateral parietal cortex represents sensory content during memory retrieval. This work has produced several significant results in favor of this hypothesis and has involved the development of new fMRI methods. In the proposed research and training program, I will use computational models of visual encoding to discriminate between competing hypotheses of how topographic maps in parietal cortex encode spatial information during memory retrieval. This experience will provide training in visual neuroscience and computational modeling, allowing me to develop expertise with diverse approaches to studying episodic memory. In the proposed postdoctoral training phase, I will gain theoretical and methodological training in electrophysiological measurements collected from humans. The combination of fMRI and electrophysiology measurements will allow me to test novel hypotheses about how memory signals propagate through time across distinct brain regions, and to generate findings that unify research performed in human and non-human animal systems. This research program has significant potential to generate novel understanding of the cortical mechanisms that support memory retrieval, to bridge findings across measurements techniques, and to inform the treatment of aging- and disease-related memory disorders. I am confident that the training provided by this research program will allow me to develop the diverse theoretical and methodological expertise needed to conduct independent research on a core set of questions in systems and cognitive neuroscience.