From Brain Maps to Cognitive Ontologies: Informatics and the Search for Mental Structure.
From Brain Maps to Cognitive Ontologies: Informatics and the Search for Mental Structure.
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DOI：
10.1146/annurev-psych-122414-033729
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发表时间：
2016
影响因子：
24.8
通讯作者：
Yarkoni T
中科院分区：
文献类型：
--
作者：
Poldrack RA;Yarkoni T
认知神经科学的一个主要目标是描述大脑系统如何产生心理功能。在这里，我们审查越来越大的作用信息驱动的方法正在发挥这样的努力。我们开始通过回顾一些挑战，传统的神经影像学方法面临的试图描绘大脑认知映射，例如，在建立特定的假设协会的困难。接下来，我们将展示如何使用强调大规模分析的互补方法来克服这些限制，包括一次合成数百或数千项研究的元分析方法;潜变量方法，旨在以自下而上的方式从数据中提取结构;以及能够从大脑活动模式定量推断精神状态的预测建模方法。我们强调了未得到充分重视，但正式的认知本体论在帮助澄清，完善和测试理论的大脑和认知功能的关键作用。最后，我们结束了什么样的未来信息学的发展可能会举行认知神经科学的投机性讨论。
A major goal of cognitive neuroscience is to delineate how brain systems give rise to mental function. Here we review the increasingly large role informatics-driven approaches are playing in such efforts. We begin by reviewing a number of challenges conventional neuroimaging approaches face in trying to delineate brain-cognition mappings—for example, the difficulty in establishing the specificity of postulated associations. Next, we demonstrate how these limitations can potentially be overcome using complementary approaches that emphasize large-scale analysis—including meta-analytic methods that synthesize hundreds or thousands of studies at a time; latent-variable approaches that seek to extract structure from data in a bottom-up manner; and predictive modeling approaches capable of quantitatively inferring mental states from patterns of brain activity. We highlight the underappreciated but critical role for formal cognitive ontologies in helping to clarify, refine, and test theories of brain and cognitive function. Finally, we conclude with a speculative discussion of what future informatics developments may hold for cognitive neuroscience.