Resolving the neural dynamics of visual and auditory scene processing in the human brain: a methodological approach
Resolving the neural dynamics of visual and auditory scene processing in the human brain: a methodological approach
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DOI：
10.1098/rstb.2016.0108
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发表时间：
2017-02-19
影响因子：
6.3
通讯作者：
Teng, Santani
中科院分区：
文献类型：
--
作者：
Cichy, Radoslaw Martin;Teng, Santani
在自然环境中，视觉和听觉刺激会在几分之一秒内引起大量大脑区域的反应，从而产生多模态场景及其属性的表示。视觉和听觉信息处理过程中快速而复杂的神经动力学对人类认知神经科学提出了重大挑战。非侵入性测量的大脑信号固有地是嘈杂的，神经表示的格式是未知的，并且表示之间的转换是复杂的并且通常是非线性的。此外，没有单一的非侵入性脑测量技术提供时空整合视图。在这篇观点文章中，我们认为，可以通过基于最近方法发展的三大支柱的协调努力取得进展：（i）敏感的分析技术，如解码和交叉分类，（ii）使用深度神经网络等模型的复杂计算建模，以及（iii）跨成像方法的集成（脑磁图/脑电描记术、功能磁共振成像）和模型，例如使用代表性相似性分析。我们展示了两个最近的努力，已经在这种精神进行，并提供新的视觉和听觉场景分析的结果。最后，我们讨论了这种观点的局限性，并为未来的研究勾画了一个具体的路线图。
In natural environments, visual and auditory stimulation elicit responses across a large set of brain regions in a fraction of a second, yielding representations of the multimodal scene and its properties. The rapid and complex neural dynamics underlying visual and auditory information processing pose major challenges to human cognitive neuroscience. Brain signals measured non-invasively are inherently noisy, the format of neural representations is unknown, and transformations between representations are complex and often nonlinear. Further, no single non-invasive brain measurement technique provides a spatio-temporally integrated view. In this opinion piece, we argue that progress can be made by a concerted effort based on three pillars of recent methodological development: (i) sensitive analysis techniques such as decoding and cross-classification, (ii) complex computational modelling using models such as deep neural networks, and (iii) integration across imaging methods (magnetoencephalography/electroencephalography, functional magnetic resonance imaging) andmodels, e.g. using representational similarity analysis. We showcase two recent efforts that have been undertaken in this spirit and provide novel results about visual and auditory scene analysis. Finally, we discuss the limits of this perspective and sketch a concrete roadmap for future research.This article is part of the themed issue 'Auditory and visual scene analysis'.