Delineation of a task-demand dependent rostrocaudal gradient in the salience network

显着网络中任务需求依赖的轴尾梯度的描绘

• 批准号: RGPIN-2017-05854
• 负责人: Woodward, Todd
• 金额: $ 2.33万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=631179
• 关键词: Delineation; task; demand; dependent; rostrocaudal

The salience network is characterized by co-activation of the dorsal anterior cingulate and the bilateral insula, and has been assigned fundamental cognitive processes, such as signalling that a task context is important, or switching between other large-scale networks to facilitate access to attention. The dACC and insula have been proposed to follow a roughly rostral/caudal division; therefore, the salience network should also follow a rostrocaudal gradient, and delineation of this, and its functional significance, is an important first step in beginning to understanding the cognitive functions associated with the vast array of functional brain networks involved in an array of cognitive tasks. We have observed such a task-demand dependent rostrocaudal gradient in the salience network in our published studies, such that coordinated salience network activity is most posterior when sensorimotor processing is required, intermediate when externally oriented attention is required, and most anterior when reasoning and inner speech cognitive operations are executed. This organization is congruent with evolutionary theories of brain organization, with more frontal cognitive processing corresponding to exclusively human cognitive processes like reasoning and inner speech. To date this theory of task-demand dependent rostrocaudal gradient in the salience network has been developed based on observations across experiments, across samples, and across data collection sites. The proposed 5 year plan involves demonstrating control over these different configurations of the salience network using within-subjects manipulations of modality of stimulus presentation (visual, verbal and auditory) and modality of data collection (fMRI and EEG) using variations of the N-back and Sternberg working memory task platforms. Displays in the verbal modality include series of letters, nonsense syllables and words, presented visually or auditorily. Stimulus displays in the non-verbal modality include designs, spatial configurations or motions presented visually, or tones or other non-verbal sounds presented auditorily, possibly also depicting motion or spatial configurations. All networks that co-activate with the various salience configuration are anticipated to be modality dependent. The effect of each variable, and combinations, on performance and the rostrocaudal gradient of the salience network, is an important first step in beginning to understanding the cognitive functions associated with the vast array of functional brain networks. This will be explored over 10 multimodal experiments proposed to extend over 5 years. This research is important to Canadians because a precise understanding of the function of brain networks is required for manipulation of those brain networks, through brain training and/or neuromodulation, to enhance cognitive functioning.

显着网络的特征是背侧前扣带回和双侧岛叶的共同激活，并被分配了基本的认知过程，例如发出任务上下文重要的信号，或在其他大规模网络之间切换以促进注意力的获得。 dACC 和岛叶被提议遵循大致的头侧/尾侧划分；因此，显着性网络也应该遵循轴尾梯度，对此的描述及其功能意义是开始理解与涉及一系列认知任务的大量功能性大脑网络相关的认知功能的重要的第一步。在我们发表的研究中，我们在显着性网络中观察到了这种任务需求依赖的轴尾梯度，因此当需要感觉运动处理时，协调的显着性网络活动是最靠后的，当需要外部定向注意力时，协调的显着性网络活动是中间的，当执行推理和内部言语认知操作时，协调的显着性网络活动是最靠前的。这种组织与大脑组织的进化理论一致，更多的额叶认知处理对应于人类独有的认知过程，如推理和内心言语。迄今为止，显着网络中任务需求相关的轴尾梯度理论是基于跨实验、跨样本和跨数据收集站点的观察而发展起来的。拟议的 5 年计划包括使用 N-back 和 Sternberg 工作记忆任务平台的变体，使用受试者内部对刺激呈现方式（视觉、言语和听觉）和数据收集方式（功能磁共振成像和脑电图）的操作来展示对显着性网络的这些不同配置的控制。言语形态的显示包括一系列字母、无意义的音节和单词，以视觉或听觉方式呈现。非语言形式的刺激显示包括视觉呈现的设计、空间配置或运动，或者听觉呈现的音调或其他非语言声音，也可能描绘运动或空间配置。预计与各种显着性配置共同激活的所有网络都依赖于模态。每个变量及其组合对显着性网络的表现和轴尾梯度的影响，是开始理解与大量功能性大脑网络相关的认知功能的重要的第一步。这将通过 10 多个多模式实验进行探索，预计将持续 5 年以上。这项研究对加拿大人来说很重要，因为通过大脑训练和/或神经调节来操纵这些大脑网络，以增强认知功能，需要精确了解大脑网络的功能。