Sensory-Biased Working Memory & Attention Networks in the Human Brain

感觉偏向的工作记忆

• 批准号: 1829394
• 负责人: David Somers
• 金额: $ 59.11万
• 依托单位: Trustees of Boston University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1829394&HistoricalAwards=false
• 关键词: Sensory; Biased; Working; Memory; &amp

AbstractHumans experience the world via multiple sensory modalities -- we see, we hear, and we touch. Each sensory modality has unique strengths and weaknesses in its ability to represent the world around us. Our minds are able to flexibly recruit visual or auditory brain structures when their strengths correspond to the task at hand. In addition, our experience at any moment depends both on sensory input and on working memory and attention mechanisms in the brain. These mechanisms have very limited capacities, which in turn limit cognition. The overarching goal of this project is to examine the human brain mechanisms that support attention and working memory in vision, hearing, and touch. The research team will perform functional MRI experiments to study the brain activity of healthy adults while they perform demanding sensory working memory tasks. Preliminary studies by the research group suggest that there are extensive brain networks, extending into the frontal lobes of the cerebral cortex, that are specialized for each sensory modality, as well as a shared network that supports and unifies these three senses. The current research program will examine individual differences in working memory performance and brain network organization. It will also develop advanced computational models that can predict the functional organization of an individual's brain from their unique pattern or 'fingerprint' of brain connectivity. The project will facilitate other research efforts through the dissemination of new models and computational tools, and will recruit and train young scientists, including members of groups that are under-represented in STEM, in cognitive neuroscience research.This proposal has 4 primary intellectual goals: (1) identify the fine-scale organization of tactile, visual, auditory, and modality-independent attention & working memory (WM) regions within human cerebral cortex; (2) reveal the specificity of coding of WM information across cortical regions for each modality; (3) detail the network organization of attention & WM circuits; and (4) test hypotheses about content-specific WM mechanisms and cross-modality WM coding. Individual subject fMRI analyses permit fine-scale observation of distinct functional regions. Drawing on subject-specific maps of cortical organization, the research group will re-examine the highly debated question of which brain structures support stimulus-specific working memory for each modality. It will investigate the specificity of sensory modality biased regions by examining functional networks in the resting-state within individual participants. The research team will leverage its findings to probe these networks in 1200 subjects from the Human Connectome Project dataset. The research group will also test and validate a machine-learning approach, Connectome Fingerprinting, for predicting the location of modality-specific working memory regions in individual brains from their unique functional connectome. Vision excels in coding spatial information, but codes timing less reliably; conversely, the auditory system performs high-fidelity temporal coding but coarse spatial coding. The research team has observed cross-modal recoding of WM information into cortical structures that prefer the 'appropriate modality' - auditory spatial WM recruits visual-biased regions and visual temporal WM recruits auditory-biased regions. To probe content-specific WM mechanisms, the researchers will examine interactions between sensory modality WM and space/time WM. The research group hypothesizes that visual and spatial WM stores are distinct, but that auditory and timing WM stores are shared. Collectively, these studies will elucidate the human brain networks and mechanisms that support sensory working memory.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.

Abstracthumans通过多种感官方式体验世界 - 我们看到，我们听到并触摸。每种感觉方式都具有代表我们周围世界的能力的独特优势和缺点。当我们的长度与手头的任务相对应时，我们的思想能够灵活招募视觉或听觉大脑结构。此外，我们的经验在任何时候都取决于感官输入，以及大脑中的工作记忆和注意力机制。这些机制具有非常有限的能力，从而限制了认知。该项目的总体目标是检查支持视力，听力和触摸中注意力和工作记忆的人脑机制。研究小组将执行功能性MRI实验，以研究健康成年人的大脑活动，同时他们执行苛刻的感觉工作记忆任务。研究小组的初步研究表明，存在广泛的大脑网络，扩展到大脑皮层的额叶，这些脑网络专门针对每种感觉方式，以及支持并统一这三种感官的共享网络。当前的研究计划将检查工作记忆性能和大脑网络组织的个体差异。它还将开发高级计算模型，这些模型可以通过其独特的模式或大脑连接性的“指纹”来预测个人大脑的功能组织。该项目将通过传播新的模型和计算工具来促进其他研究工作，并将招募和培训年轻科学家，包括在STEM中代表不足的团体成员，在认知神经科学研究中。 （1）确定人类大脑皮层内的触觉，视觉，听觉和模态的触觉，视觉，听觉和模态性记忆（WM）区域的精细组织； （2）揭示了每种模态跨皮质区域的WM信息编码的特异性； （3）详细介绍关注和WM电路的网络组织； （4）测试有关特定于内容的WM机制和交叉模式WM编码的假设。个体受试者fMRI分析允许对不同功能区域进行精细观察。利用皮质组织的特定主题图，研究小组将重新检查一个高度争议的问题，即哪种大脑结构支持刺激特异性的工作记忆。它将通过检查单个参与者中静息状态的功能网络来研究感觉方式有偏见区域的特异性。研究团队将利用其发现来探究来自人类Connectome项目数据集的1200名受试者的这些网络。研究小组还将测试和验证一种机器学习方法，即Connectome指纹识别，以预测单个大脑中特定于模态的工作记忆区域的位置，从其独特的功能连接组中。视觉在编码空间信息方面表现出色，但是编码时间的定时不太可靠；相反，听觉系统执行高保真时间的时间编码，但粗糙的空间编码。研究团队已经观察到WM信息的跨模式重新编码为偏爱“适当的模态”的皮质结构 - 听觉空间WM招募了视觉偏见的区域和视觉时间WM WM招募听觉偏见的区域。为了探测特定于内容的WM机制，研究人员将检查感觉方式WM与空间/时间WM之间的相互作用。研究小组假设视觉和空间WM商店是不同的，但是共享听觉和时机WM商店。总的来说，这些研究将阐明支持感官工作记忆的人类脑网络和机制。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响审查标准通过评估来支持的。

项目成果

Visual-biased frontal structures are preferentially connected to multisensory working memory regions.

视觉偏向的额叶结构优先连接到多感觉工作记忆区域。

• DOI: 10.1167/19.10.245c
• 发表时间: 2019
• 期刊: Journal of Vision
• 影响因子: 1.8
• 作者: Noyce, Abigail;Lefco, Ray W.;Brissenden, James A.;Tobyne, Sean M.;Shinn-Cunningham, Barbara G.;Somers, David C.
• 通讯作者: Somers, David C.

Extended Frontal Networks for Visual and Auditory Working Memory

视觉和听觉工作记忆的扩展额叶网络

• DOI: 10.1093/cercor/bhab249
• 发表时间: 2021
• 期刊: Cerebral Cortex
• 影响因子: 3.7
• 作者: Noyce, Abigail L;Lefco, Ray W;Brissenden, James A;Tobyne, Sean M;Shinn-Cunningham, Barbara G;Somers, David C
• 通讯作者: Somers, David C