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Multitasking practice eliminates modality-based interference by separating task representations in sensory brain regions.
Journal of Neuroscience ( IF 4.4 ) Pub Date : 2024-11-07 , DOI: 10.1523/jneurosci.0755-24.2024
Marie Mueckstein,Kai Görgen,Stephan Heinzel,Urs Granacher,Michael A Rapp,Christine Stelzel

The debate on the neural basis of multitasking costs evolves around neural overlap between concurrently performed tasks. Recent evidence suggests that training-related reductions in representational overlap in fronto-parietal brain regions predict multitasking improvements. Cognitive theories assume that overlap of task representations may lead to unintended information exchange between tasks (i.e., crosstalk). Modality-based crosstalk was suggested as a source for multitasking costs in multisensory settings. Robust findings of increased costs for certain modality mappings may be explained by crosstalk between the stimulus modality in one task and sensory action consequences in the concurrently performed task. Whether modality-based crosstalk emerges from representational overlap in general fronto-parietal multitasking regions or modality-specific regions is not known yet. In this functional neuroimaging study, we investigate neural overlap during multitasking performance in humans, focusing on modality compatibility by employing multivariate pattern analysis and modality-specific practice interventions in three groups (total N = 54, 24 females). We observed significant differences between modality compatible and modality incompatible single-task representations, specifically in the auditory cortex but not in fronto-parietal regions. Notably, improved auditory decoding accuracy related to modality incompatible tasks was predictive of performance gains in the corresponding dual task along with complete elimination of modality-specific dual-task costs. This predictive relationship was evident only in the group practicing modality incompatible mappings, suggesting that specific practice on task sets with modality overlap influenced both neural representations and subsequent multitasking performance. This study contributes to the integration of cognitive theory and neuroscience and the role of task representations in dual-task interference.Significance Statement In a society dominated by multitasking, understanding its neurocognitive basis and plasticity is crucial for key aspects of everyday tasks. We investigate the neural mechanisms behind multitasking limitations, offering insights for targeted cognitive interventions. The study builds upon established theories of cognitive multitasking and imaging research, addressing the concept of modality-based crosstalk - the unintended exchange of modality-based information between tasks. Through functional brain imaging and pattern analysis, we examined how neural task representations contribute to performance costs in dual tasks with varying degrees of modality overlap. Notably, our findings demonstrate a practice-related decrease in neural overlap which is associated with substantial multitasking improvements, specifically in the auditory cortex, emphasizing the contribution of sensory regions to flexible multidimensional task representations.

中文翻译:


多任务练习通过分离感觉大脑区域中的任务表示来消除基于模态的干扰。



关于多任务处理成本的神经基础的争论围绕着并发执行的任务之间的神经重叠而发展。最近的证据表明,额顶脑区域代表性重叠的训练相关减少预示着多任务处理的改善。认知理论假设任务表示的重叠可能导致任务之间意外的信息交换(即串扰)。基于模态的串扰被认为是多感官环境中多任务处理成本的来源。某些模态映射成本增加的稳健发现可以通过一项任务中的刺激模态和同时执行的任务中的感觉动作后果之间的串扰来解释。目前尚不清楚基于模态的串扰是从一般额顶多任务区域还是模态特异性区域的表征重叠中出现的。在这项功能神经影像学研究中,我们调查了人类多任务执行过程中的神经重叠,通过在三组 (总 N = 54,24 名女性) 中采用多变量模式分析和模式特异性实践干预来关注模式兼容性。我们观察到模态兼容和模态不兼容的单任务表征之间存在显着差异,特别是在听觉皮层,但在额顶叶区域没有。值得注意的是,与模态不兼容任务相关的听觉解码准确性的提高可以预测相应双任务的性能提升以及完全消除特定于模态的双任务成本。 这种预测关系仅在练习模态不兼容映射的组中很明显,这表明具有模态重叠的任务集的特定练习会影响神经表征和随后的多任务处理表现。这项研究有助于认知理论和神经科学的整合以及任务表征在双重任务干扰中的作用。意义声明 在一个以多任务处理为主的社会中,了解其神经认知基础和可塑性对于日常任务的关键方面至关重要。我们研究了多任务处理限制背后的神经机制,为有针对性的认知干预提供了见解。该研究建立在认知多任务处理和成像研究的既定理论之上,解决了基于模态的串扰的概念——任务之间基于模态的信息的意外交换。通过功能脑成像和模式分析,我们研究了神经任务表征如何在具有不同程度模态重叠的双重任务中导致性能成本。值得注意的是,我们的研究结果表明,与实践相关的神经重叠减少,这与实质性的多任务处理改善有关,特别是在听觉皮层中,强调了感觉区域对灵活的多维任务表示的贡献。
更新日期:2024-11-07
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