The Neural Mechanisms Underlying Categorical Decision Making

项目摘要/摘要 当我们面对关于我们世界的不清楚或模糊的信息时，我们严重依赖记忆来 填写缺失的数据，并最终指导行为。例如，如果你遇到一只巨大的四条腿的动物 当你在森林中徒步旅行时，和它的幼崽在一起，你随后的行动不仅取决于识别它，而且 一旦你记住熊是危险的，你就会做出适当的反应。大脑中的机制是什么 负责识别、识别和分类对象，所有这些都可能发生在数百个 毫秒？这个问题与作为接口的语义记忆系统内在地联系在一起 在输入的感官信息和我们先前存在的词语、图像的意义知识之间， 概念及其关联。拟议研究的主要目标是更好地了解 语义范畴如何在人脑中发生的时间动力学。 研究语义分类的一种方法是将其框定为发生在大脑中的决定。 对几个物种(例如，老鼠、猴子和人类)的决策研究表明， 决策需要特定的计算，在此过程中积累证据，直到特定的阈值 已会面，表明已做出决定。这一框架(漂移扩散模型，DDMS)有助于 根据任务的不同，发现大脑中的几个决策信号，这导致研究人员 我认为DDMS可能是一种脑部通病机制。如果这是真的，DDMS应该能够解释活动 在物体识别任务期间的人类腹侧视觉流中。这项研究的第一个目的是确定 人类腹侧视觉流中的什么位置最能用决策信号描述。主 假设在语义分类任务中，决策信号应该出现在前部 颞叶(ATL)，近几十年来一直被认为是大脑的语义中枢。 这项研究的第二个目的是研究大脑如何对视觉进行分类(例如，模糊、遮挡) 刺激物。在行为层面上，当图像较少时，人类需要更多时间来执行对象识别 安全。一种可能的解释神经机制将涉及与明确的相同的神经过程 视觉识别只是发生得更慢。一个相反的假说是，额外的大脑区域必须是 被招募来解决歧义。例如，经由内侧颞叶(MTL)访问存储的存储器可以 被征召来唤起以前的经验。另一种选择依赖于更大程度的认知控制 来自前额叶皮质(PFC)。这项研究项目将利用 人类的颅内记录。这项研究可以解释认知系统和大脑网络 通常在影响记忆的疾病中受损，包括阿尔茨海默病和语义性痴呆症。

PROJECT SUMMARY/ABSTRACT When we are confronted with unclear or vague information about our world, we rely heavily on memory to fill in missing data and ultimately guide behaviors. For example, if you encounter a massive four-legged animal alongside its cub while hiking in a forest, your subsequent actions rely not merely on identifying the animal, but reacting appropriately once you remember that bears are dangerous. What mechanisms in the brain are responsible for recognizing, identifying, and categorizing objects, all of which can occur within hundreds of milliseconds? This question is inherently linked to the semantic memory system, which acts as the interface between incoming sensory information and our preexisting knowledge of the meaning of words, images, concepts, and their associations. The primary goal of the proposed research is to better understand the temporal dynamics of how semantic categorization occurs in the human brain. One method to study semantic categorization is by framing it as a decision that occurs in the brain. Research on decision-making across several species (e.g., mice, monkeys, and humans) has shown that decision-making requires a specific computation where evidence is accumulated until a particular threshold is met, indicating a decision has been reached. This framework (drift-diffusion models, DDMs) has helped to uncover several decision-making signals across the brain depending on the task, leading researchers to believe DDMs could be a brain-general mechanism. For this to be true, DDMs should be able to explain activity in the human ventral visual stream during object recognition tasks. The first aim of this study is to identify where in the human ventral visual stream can best be described by decision-making signals. The main hypothesis is that during a semantic categorization task, decision-making signals should occur in the anterior temporal lobe (ATL), which has been implicated in recent decades as the brain’s semantic hub. The second aim of this study is to examine how the brain categorizes (e.g., blurred, occluded) visual stimuli. On a behavioral level, humans require more time to perform object recognition when images are less clear. One possible explanatory neural mechanism would involve the same neural processes as unambiguous visual recognition that just occurs more slowly. A contrasting hypothesis is that additional brain areas must be recruited to solve ambiguity. For instance, accessing stored memories via the medial temporal lobe (MTL) may be enlisted to call upon previous experiences. Another option relies on a greater degree of cognitive control from the prefrontal cortex (PFC). This research project will leverage the spatiotemporal precision offered by intracranial recordings in humans. This study can illuminate cognitive systems and brain networks that are often damaged in diseases affecting memory, including Alzheimer’s Disease and Semantic Dementia.