Rotation 1: The Computational Mechanism of Visual Working Memory Retrieval

BBSRC战略主题：综合理解健康的生物科学视觉感知是指大脑组织和解释视觉信息的过程系统。在有效编码假设下，用于视觉特征（如颜色和方向）绑定的神经系统应该根据环境中模式的频率（即自然统计）进行有效配置和优化。第一个研究方向将集中在系统地探索由被操纵的自然统计引起的特征绑定动态（例如，将颜色与方向耦合）。此外，还将研究与自然统计分布变化有关的单个特征空间。为了实现这些目标，扩展现实与双目视频传输将与传统的心理物理方法一起使用。第二项研究将集中在视觉工作记忆（VWM），这是一种灵活的神经系统，能够在短时间内存储和检索视觉信息的内部表征。绑定动态将在线索回忆范式中进行研究，参与者对一组具有唯一特征值（例如，颜色和方向）的对象进行编码。在短暂的间隔后，目标物品由其特征之一（例如颜色）提示，并且必须报告另一个特征（例如位置）。因此，检索过程可以大致分为线索到项目匹配和报告特征读出。这些阶段将与跨特征空间的试验级动态有关，例如，测试与响应错误相关的VWM检索和检索时间组件的潜在并行性质。重要的是，以前的计算工作通过累积到边界的原则将VWM检索与视觉决策进行了类比，其中感官信息不断地集成到决策边界。利用线索回忆任务，本项目将进一步研究在知觉决策方面的潜在相似性，如时间压力和任务难度的影响。此外，试验级动态将通过思维的变化进行检查，代表自适应实时决策更新。后续实验将把主要发现扩展到改变特征特征和维度，从VWM检索的角度瞄准结合动力学。最后的实验将努力识别跨试验和特征域的动态，例如，通过操纵刺激特征的自然统计来测试VWM检索中线索特征优势的潜在变化。为了扩展行为分析，结合动力学机制和VWM检索将使用累积到绑定和种群编码框架内的计算模型进行研究。总的来说，为了提高我们对视觉大脑特征绑定和检索动态的理解，该项目将采用多范式方法进行严格的实验操作，重点关注视觉感知和VWM。虽然视觉感知通常被认为是编码阶段，只是在VWM存储之前，但这些认知和神经功能可能会动态地相互作用，甚至通过最基本的任务进行导航。这项工作将首先尝试绘制每个学院的关键动态图，随后测试它们的相互动态，并将其合成为可测试的计算模型。至关重要的是，这些基本原则可能为诊断措施的发展提供基础，这些措施足够敏感，可以检测新出现的特征结合缺陷，例如在阿尔茨海默病的早期阶段。

BBSRC strategic theme: Biosciences for an integrated understanding of healthVisual perception refers to the system of processes by which the brain organises and interprets visual information. Under the efficient coding hypothesis, the neural system for binding of visual features (e.g., colour and orientation) should be efficiently configured and optimised according to frequencies of patterns in the environment (i.e., natural statistics). The first research line will centre on systematic explorations of feature binding dynamics induced by manipulated natural statistics (e.g., coupling colours with orientations). Moreover, individual feature spaces will be also investigated in relation to altered natural statistics distributions. For these objectives, extended reality with binocular video passthrough will be used alongside traditional psychophysical methods. The second research line will focus on visual working memory (VWM), a flexible neural system enabling to store and retrieve internal representations of visual information over short time. The binding dynamics will be studied within the cued recall paradigm where participants encode a set of objects with unique feature values (e.g., colours and orientations). After a brief interval, the target item is cued by one of its features (e.g., colour) and another one must be reported (e.g., location). As such, the retrieval process can be broadly divided into cue-to-item matching and report feature readout. These stages will be explored in relation to trial-level dynamics across feature spaces, for example, testing the potential parallel nature of VWM retrieval and retrieval time components in relation to response errors. Importantly, previous computational work drew a parallel between VWM retrieval and visual decision making through the accumulation-to-bound principle where sensory information is continuously integrated towards decision bounds. Using the cued recall task, this project will further investigate the potential similarities building on robust findings in perceptual decision making, such as the effects of time pressure and task difficulty. Additionally, the trial-level dynamics will be examined through changes of mind, representing adaptive real-time decision updating. Follow-up experiments will extend the main findings to altered feature characteristics and dimensionality, targeting binding dynamics from the VWM retrieval perspective. The final experiments will strive to identify dynamics across trials and feature domains, for example, testing potential shifts in cue feature dominance within VWM retrieval by manipulating natural statistics of stimuli features. To extend behavioural analyses, the binding dynamics mechanism and VWM retrieval will be investigated using computational models within the accumulation-to-bound and population coding frameworks. In general, to advance our understanding of the dynamics of feature binding and retrieval in the visual brain, the project will utilise rigorous experimental manipulations in a multi-paradigm approach, focused on both visual perception and VWM. Whereas visual perception is typically framed as the encoding stage only preceding VWM storage, these cognitive and neural faculties might dynamically interact to navigate even through the most basic tasks. This work will initially attempt to map the key dynamics in each faculty to subsequently test their mutual dynamics, synthesised into testable computational models. Crucially, these fundamental principles may provide foundations for developments of diagnostic measures, sufficiently sensitive to detect emerging feature binding deficits, for example, in early stages of Alzheimer's disease.