CAREER: Testing a unified theory of perception and memory in the medial temporal lobe

记忆对我们的日常生活至关重要，它使我们能够认出熟人的脸，记得我们把车停在哪里，或者生动地回忆起上周发生的一件事。然而，它是脆弱的：记忆能力会随着年龄的增长而显著下降，在大脑内侧颞叶受损的人中，记忆能力的下降甚至更明显。直到最近，记忆理论还假定内侧颞叶仅专用于记忆功能。然而，最近的证据表明，这些大脑区域对其他认知任务很重要，包括想象未来和在视觉上区分两个高度相似的物体。因此，当前知识中的一个关键空白是一种理论，即记忆如何与高级视觉感知相互作用，以及为什么这两种认知功能都依赖于内侧颞叶。在NSF职业奖的支持下，Rosie Cowell博士将发展这样的理论，并用实证研究来验证它。通过将这一理论应用于脑损伤引起的健忘症和正常衰老引起的更中度的记忆丧失，该项目将调查这两种形式的记忆丧失是否可以用相同的机制来解释。此外，该项目将通过以下方式更广泛地造福社会：(1)提供独特的综合研究培训制度，研究生在理论建设和假设检验方面获得直接经验；(2)通过为代表不足群体的高中的女学生举办动手科学研讨会，以及通过在马萨诸塞州当地社区的公共宣传，扩大对STEM领域的参与。为了发展记忆和高级知觉的统一理论，拟议的研究将使用行为研究、功能磁共振成像(FMRI)和计算建模。这项研究将考察知觉干扰对两个认知受损人群记忆的影响：内侧颞叶(MTL)受损的个体和健康的老年人。这一建议的中心假设是，MTL包含了对对象和事件的联合表征，这对记忆和感知都是关键的。连词对感知至关重要，因为它们可以区分两个相似的物体或事件，对记忆也至关重要，因为它们屏蔽了持续不断的感知干扰，否则会导致戏剧性地忘记对象或事件。假设MTL损伤和正常衰老都损害了连接表征，迫使一个人依赖于保留在感觉皮质中的碎片化的、基于特征的表征。基于特征的表征不足以区分相似的项目(导致知觉障碍)，并且非常容易受到知觉干扰(导致记忆问题)。计划中的研究有望揭示，当任务解决方案需要复杂的、连接的刺激表征时，MTL结构对任何认知任务都有贡献，无论是助记还是知觉。这种理解认知的表征方法将通过开发一种形式的、神经计算上可信的模型来充分利用，该模型将神经表征与认知表现联系起来，并具有明确的机制。

Memory is critical to our everyday existence, enabling us to recognize an acquaintance's face, remember where we have parked our car, or recall an event from last week in vivid detail. And yet, it is fragile: memory performance can decline noticeably with age and deteriorates even more dramatically in individuals with damage to the medial temporal lobes of the brain. Until recently, theories of memory assumed that the medial temporal lobes are dedicated solely to memory function. However, recent evidence suggests that these brain regions are important for other cognitive tasks, including imagining the future and visually discriminating between two highly similar objects. Therefore, a critical gap in current knowledge is a theory of how memory interacts with high-level visual perception and why both of these cognitive functions depend upon the medial temporal lobes. With the support of this NSF CAREER award, Dr. Rosie Cowell will develop such a theory and test it with empirical studies. By applying the theory to both amnesia caused by brain damage and the more moderate memory loss caused by normal aging, this project will investigate whether these two forms of memory loss can be explained by the same mechanisms. In addition, the project will benefit society more broadly by (1) providing a uniquely integrated research training regime in which graduate students receive direct experience with both theory-building and hypothesis-testing, and (2) broadening participation in STEM fields via hands-on science workshops for female students from high-schools that serve under-represented groups, and via public outreach in the local Massachusetts community.To develop a unifying theory of memory and high-level perception, the proposed research will employ behavioral studies, functional magnetic resonance imaging (fMRI) and computational modeling. The studies will examine the effect of perceptual interference on memory in two cognitively-impaired populations: individuals with medial temporal lobe (MTL) damage and heathy, older adults. The central hypothesis of this proposal is that the MTL houses conjunctive representations of objects and events that are critical for both memory and perception. The conjunctions are critical for perception because they allow differentiation between two similar objects or events, and critical for memory because they shield against a constant stream of perceptual interference that would otherwise cause dramatic forgetting of an object or event. It is assumed that both MTL damage and normal aging compromise the conjunctive representations, forcing a person to rely upon the fragmental, feature-based representations that remain in sensory cortex. Feature-based representations are inadequate for differentiating similar items (leading to perceptual impairments) and highly susceptible to perceptual interference (leading to memory problems). The planned studies are expected to reveal that MTL structures contribute to any cognitive task, mnemonic or perceptual, whenever the task solution requires complex, conjunctive representations of stimuli. This representational approach to understanding cognition will be fully exploited by developing a formal, neuro-computationally plausible model that links neural representations to cognitive performance with an explicit mechanism.