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Domain-specific cognitive flexibility: Shift-readiness adaptations for task- and attention-switching are non-transferrable

任务切换 认知灵活性 任务(项目管理) 认知心理学 认知 灵活性(工程) 心理学 计算机科学 域特异性 领域(数学分析) 人机交互 沟通 神经科学 数学分析 管理 经济 统计 数学
作者
Audrey Siqi-Liu,Cai S. Longman,Tobias Egner
出处
期刊:Quarterly Journal of Experimental Psychology [SAGE Publishing]
卷期号:: 17470218251352839-17470218251352839
标识
DOI:10.1177/17470218251352839
摘要

Adaptive behavior in the real world involves navigating competing goals in a constantly changing environment. Doing so requires cognitive flexibility across multiple domains, including flexibility for switching between tasks, that is, activating the appropriate rules for stimulus-response associations, and flexibility for shifting attention between different sources of sensory inputs. Previous work in task switching and attention shifting has separately shown that people are capable of strategically modulating both types of flexibility based on the current demands. That is, people become better at switching between tasks (e.g., digit magnitude vs. parity tasks) when switches are frequently cued and better at shifting attention between different stimulus locations when shifts are frequently cued. Across five experiments in the current study, we investigated the possibility of cognitive flexibility transfer between the domains of task switching and attention shifting when the frequency of switches/shifts is orthogonally manipulated within the same context. We implemented a novel paradigm that involved concurrent cued task switching and attention shifting. We varied either the proportion of task switches or attention shifts across blocks of trials, while keeping the proportion of the other constant. If flexibility adaptations in biased contexts transferred across domains, switch/shift frequency manipulations in one domain should affect flexibility across both domains. Instead, in Experiments 1 to 3, we found that performance costs of attention shifts remained constant across task-switch biased contexts despite adjustments in task-switch costs; likewise, in Experiments 4 to 5, we found that costs of switching between tasks remained constant across blocks that varied in attention-shift frequency despite adaptations in attention-shift costs. These results suggest that probabilistic learning and adjustments of attention-shifts and task switches to meet contextual demands occur independently.
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