Flexible encoding of multiple task dimensions in human cerebral cortex

Benjamin J. Tamber-Rosenau, Allen T. Newton, René Marois
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Abstract

Cognitive models have proposed that behavioral tasks can be categorized along at least three dimensions: the sensory-motor modality of the information, its representational format (e.g., location vs. identity), and the cognitive processes that transform it (e.g., response selection). Moreover, we can quickly and flexibly encode, represent, or manipulate information along any of these dimensions. How is this flexibility in encoding such information implemented in the cerebral cortex?To address this question, we devised a series of functional magnetic resonance imaging (fMRI) experiments in each of which participants performed two distinct tasks that differed along one of the three dimensions.Using multivariate pattern analysis of the fMRI data, we were able to decode between tasks along at least one task dimension within each of the cortical regions activated by these tasks. Moreover, the multiple demand network, a system of brain regions previously associated with flexible task encoding, was largely composed of closely juxtaposed sets of voxels that were specialized along each of the three tested task dimensions.These results suggest that flexible task encoding is primarily achieved by the juxtaposition of specialized representations processing each task dimension in the multiple demand network.
人类大脑皮层对多个任务维度的灵活编码
认知模型提出,行为任务至少可以从三个维度进行分类:信息的感觉运动模式、信息的表征形式(如位置与身份)以及转换信息的认知过程(如反应选择)。此外,我们还可以快速灵活地对信息进行编码、表征或处理。为了解决这个问题,我们设计了一系列功能性磁共振成像(fMRI)实验,在每项实验中,参与者都执行了两个不同的任务,这两个任务在三个维度中的一个维度上存在差异。通过对fMRI数据进行多元模式分析,我们能够在这些任务激活的每个皮层区域内,沿着至少一个任务维度对不同任务进行解码。这些结果表明,灵活的任务编码主要是通过在多重需求网络中并置处理每个任务维度的专门表征来实现的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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