Bolt Taylor, Nomi Jason S, Yeo B T Thomas, Uddin Lucina Q
Department of Psychology, University of Miami, Coral Gables, Florida 33124,
Department of Psychology, University of Miami, Coral Gables, Florida 33124.
J Neurosci. 2017 Jul 26;37(30):7263-7277. doi: 10.1523/JNEUROSCI.0323-17.2017. Epub 2017 Jun 20.
Decades of cognitive neuroscience research have revealed two basic facts regarding task-driven brain activation patterns. First, distinct patterns of activation occur in response to different task demands. Second, a superordinate, dichotomous pattern of activation/deactivation, is common across a variety of task demands. We explore the possibility that a hierarchical model incorporates these two observed brain activation phenomena into a unifying framework. We apply a latent variable approach, exploratory bifactor analysis, to a large set of human (both sexes) brain activation maps ( = 108) encompassing cognition, perception, action, and emotion behavioral domains, to determine the potential existence of a nested structure of factors that underlie a variety of commonly observed activation patterns. We find that a general factor, associated with a superordinate brain activation/deactivation pattern, explained the majority of the variance (52.37%) in brain activation patterns. The bifactor analysis also revealed several subfactors that explained an additional 31.02% of variance in brain activation patterns, associated with different manifestations of the superordinate brain activation/deactivation pattern, each emphasizing different contexts in which the task demands occurred. Importantly, this nested factor structure provided better overall fit to the data compared with a non-nested factor structure model. These results point to a domain-general psychological process, representing a "focused awareness" process or "attentional episode" that is variously manifested according to the sensory modality of the stimulus and degree of cognitive processing. This novel model provides the basis for constructing a biologically informed, data-driven taxonomy of psychological processes. A crucial step in identifying how the brain supports various psychological processes is a well-defined categorization or taxonomy of psychological processes and their interrelationships. We hypothesized that a nested structure of cognitive function, in terms of a canonical domain-general cognitive process, and various subfactors representing different manifestations of the canonical process, is a fundamental organization of human cognition, and we tested this hypothesis using fMRI task-activation patterns. Using a data-driven latent-variable approach, we demonstrate that a nested factor structure underlies a large sample of brain activation patterns across a variety of task domains.
几十年来的认知神经科学研究揭示了关于任务驱动型大脑激活模式的两个基本事实。第一，不同的激活模式会因不同的任务需求而出现。第二，一种上级的、二分的激活/去激活模式在各种任务需求中普遍存在。我们探讨了一种层次模型将这两种观察到的大脑激活现象纳入一个统一框架的可能性。我们将一种潜在变量方法，即探索性双因素分析，应用于一大组涵盖认知、感知、行动和情感行为领域的人类（男女皆有）大脑激活图（ = 108），以确定在各种常见激活模式背后潜在存在的嵌套因素结构。我们发现，一个与上级大脑激活/去激活模式相关的一般因素解释了大脑激活模式中大部分的方差（52.37%）。双因素分析还揭示了几个子因素，它们解释了大脑激活模式中方差的另外31.02%，这些子因素与上级大脑激活/去激活模式的不同表现相关，每个子因素都强调了任务需求出现的不同背景。重要的是，与非嵌套因素结构模型相比，这种嵌套因素结构对数据的整体拟合度更好。这些结果指向一个领域通用的心理过程，它代表一种“聚焦意识”过程或“注意力事件”，会根据刺激的感觉模态和认知处理程度以不同方式表现出来。这个新模型为构建一个基于生物学且数据驱动的心理过程分类法提供了基础。确定大脑如何支持各种心理过程的关键一步是对心理过程及其相互关系进行明确的分类或分类法。我们假设，就一个典型的领域通用认知过程而言，认知功能的嵌套结构以及代表该典型过程不同表现的各种子因素是人类认知的基本组织，并且我们使用功能磁共振成像任务激活模式来检验这个假设。通过一种数据驱动的潜在变量方法，我们证明了嵌套因素结构是各种任务领域中大量大脑激活模式的基础。
