NCS-FO: Uncovering Dynamics of Neural Activity of Subjective Estimation of Time

我们在日常生活中不断地估算时间。事实上，这些信息被用来构建我们感知、记忆和对世界的一般理解的许多方面。研究表明，我们对时间的个人体验是不一致的，可能受到各种内部和外部因素的影响。虽然脑成像技术有助于提高我们对大脑如何估计时间的认识，但我们对时间感知和估计的神经机制知之甚少。这个跨学科项目汇集了来自信号处理、神经成像和心理学的专业知识，以开发一种创新的数据驱动计算工具，当与脑成像和行为测量相结合时，可以识别导致我们如何体验时间差异的特定大脑过程。所获得的知识也可能对神经和精神疾病有影响，如帕金森病、精神分裂症和注意力缺陷/多动障碍（ADHD），这些疾病的时间感知变化很常见。研究人员还致力于使他们开发的信号处理工具广泛可用，并开展广泛的外展和网络研讨会，以提高对研究的认识和利用。这项研究旨在揭示导致我们主观时间感变化的特定神经机制，这一点目前还没有得到很好的理解。通过利用矩阵分解，该项目提供了一种创新的数据驱动计算工具，专门用于识别两个神经数据集之间的差异（包括空间和时间）。这种新方法偏离了大多数传统分析，传统分析对潜在神经过程的本质（例如，时间或空间邻接性）做出了更强的假设。因此，这里开发的技术可能会对各种各样的行为及其神经关联提供新的见解。该项目希望发展这项技术，并将其应用于个人主观时间估计变化的神经机制，同时操纵三个因素（记忆、感觉处理和唤醒）。所提出的计算工具可以定位产生观察到的差异的特定神经活动，并识别这些活动何时发生。了解时间感知及其估计变异的神经机制对推进神经科学基础研究和时间估计理论具有重要意义。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

We are constantly estimating time in our everyday lives. Indeed, this information is used to frame many aspects of our perception, memory, and general understanding of the world. Research suggests that our personal experience of time is not consistent and can be influenced by various internal and external factors. While brain imaging techniques have contributed to advancing our knowledge of how the brain estimates time, little is known about the neural mechanisms that underlie time perception and estimation. This interdisciplinary project brings together expertise from signal processing, neuroimaging and psychology, to develop an innovative data-driven computational tool, that when combined with brain imaging and behavioral measurements, can identify specific brain processes that cause differences in how we experience time. The knowledge gained may also have implications for neurological and psychiatric disorders such as Parkinson’s disease, schizophrenia, and attention-deficit/hyperactivity disorder (ADHD), for which changes in time perception are common. The researchers also aim to make the signal processing tools they develop broadly available and conduct extensive outreach and webinars to increase awareness and utilization of the research.The proposed research aims to uncover the specific neural mechanisms that contribute to variations in our subjective sense of time, which are currently not well understood. By utilizing matrix factorization, the project offers an innovative data-driven computational tool, specifically developed for identifying the differences (both spatially and temporally) between two neural datasets. This new approach deviates from most conventional analyses, which make stronger assumptions about the nature of the underlying neural processes (e.g., temporal or spatial adjacency). Thus, the technique developed here may offer new insights across a wide variety of behaviors and their neural correlates. The project hopes to develop this technique and utilize it in the context of the neural mechanisms underlying changes in an individual’s subjective estimation of time while three factors are manipulated (memory, sensory processing, and arousal). The proposed computational tool can localize specific neural activities that give rise to the observed differences, as well as identify when these activities occur. Understanding of the neural mechanisms that contribute to the variability in time perception and its estimation holds great significance in advancing basic neuroscience research and theories about time estimation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.