Jackson Jade B, Rich Anina N, Moerel Denise, Teichmann Lina, Duncan John, Woolgar Alex
MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.
Macquarie Performance and Expertise Research Centre, & School of Psychological Sciences, Macquarie University, Sydney, Australia.
Imaging Neurosci (Camb). 2025 Jun 16;3. doi: 10.1162/IMAG.a.29. eCollection 2025.
A defining feature of human cognition is our ability to respond flexibly to whatwe see and hear, changing how we respond depending on our current goals. Infact, we can rapidly associate almost any input stimulus with any arbitrarybehavioural response. This remarkable ability is thought to depend on afrontoparietal "multiple demand" circuit which is engaged by manytypes of cognitive demand and widely referred to as domain general. However, itis not clear how responses to multiple input modalities are structured withinthis system. Domain generality could be achieved by holding information in anabstract form that generalises over input modality, or in a modality-taggedform, which uses similar resources but produces unique codes to represent theinformation in each modality. We used a stimulus-response task, withconceptually identical rules in two sensory modalities (visual and auditory), todistinguish between these possibilities. Multivariate decoding of functionalmagnetic resonance imaging data showed that representations of visual andauditory rules recruited overlapping neural resources but were expressed inmodality-tagged non-generalisable neural codes. Our data suggest that thisfrontoparietal system may draw on the same or similar resources to solvemultiple tasks, but does not create modality-general representations of taskrules, even when those rules are conceptually identical between domains.
人类认知的一个决定性特征是我们能够灵活地对所见所闻做出反应,根据当前目标改变我们的反应方式。事实上,我们几乎可以将任何输入刺激与任意行为反应迅速关联起来。这种非凡的能力被认为依赖于一个额顶叶“多重需求”回路,该回路会被多种类型的认知需求激活,并且被广泛称为领域通用。然而,尚不清楚在这个系统中对多种输入模态的反应是如何构建的。领域通用性可以通过以一种抽象形式保存信息来实现,这种抽象形式可以跨输入模态进行泛化,或者以一种带有模态标签的形式来实现,这种形式使用类似的资源,但会生成独特的代码来表示每种模态中的信息。我们使用了一个刺激-反应任务,在两种感觉模态(视觉和听觉)中具有概念上相同的规则,以区分这些可能性。功能磁共振成像数据的多变量解码表明,视觉和听觉规则的表征招募了重叠的神经资源,但以带有模态标签的不可泛化的神经代码来表达。我们的数据表明,这个额顶叶系统可能利用相同或相似的资源来解决多个任务,但不会创建任务规则的模态通用表征,即使这些规则在不同领域之间在概念上是相同的。