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当前的行为。情景性的计算模型 记忆提出，回忆过去的事件涉及恢复皮层活动的模式， 在事件发生时被唤醒。虽然有相当多的证据表明，在早期感觉恢复 区域，最近的证据表明，恢复也发生在更高级别的区域，如侧顶叶， 大脑皮层，这是强烈的记忆成功的预测。然而，在横向恢复的意义 顶叶皮层及其与感觉区恢复的关系尚不清楚。了解如何 像侧顶叶皮层这样的区域代表、转换和优先处理来自感觉区域的信息， 这对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。 解决这些理解上的差距需要依靠创新的功能磁共振成像的多学科方法 分析，计算建模，并整合来自神经成像和电生理学的证据。我 到目前为止，论文工作已经使用功能磁共振成像方法来测试外侧顶叶皮层代表 记忆提取过程中的感觉内容这项工作已经产生了几个重要的结果，有利于这一点 这一假说，并涉及新的功能磁共振成像方法的发展。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竞争的假设， 顶叶皮层地形图在记忆提取过程中如何编码空间信息。这段经历 将提供视觉神经科学和计算建模方面的培训，使我能够发展专业知识， 研究情景记忆的不同方法。在拟进行的博士后培养阶段， 从人体收集的电生理测量的理论和方法培训。的 结合功能磁共振成像和电生理学测量将允许我测试新的假设， 记忆信号通过时间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。这项研究计划具有巨大的潜力 对支持记忆提取的皮层机制产生新的理解， 跨测量技术，并告知治疗衰老和疾病相关的记忆 紊乱我相信，这项研究计划提供的培训将使我能够发展 需要多样化的理论和方法专业知识，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.