Verbal and Non-Verbal Control Settings in Action Control Configuring the Cognitive System for Present and Future Task Performance

认知控制确保我们成功实现目标。行动控制模型假设自动以及受控的过程，以确保成功完成目标导向的行动。这两种行为控制模式在语言和联想学习的使用上有所不同。在实际的任务表现的控制过程中的差异参与，在这个项目中，即口头和非口头的，被认为是导致差异学习和专业知识的两个控制设置下调查。语言控制设置是依赖于语言的控制设置，包括自我指令和相当抽象的符号表示等过程。相比之下，非语言控制设置利用以前学习的协会，并导致情节记忆痕迹的形成。认知控制过程及其对情境约束的灵活适应已经使用任务转换范式进行了研究。在任务转换情境中，人们至少遇到两个任务，并被要求在它们之间交替，这是由其他任务旁边的有效任务提示所指示的，例如Stroop任务。在第一系列的实验中，我们将调查如何情境特征，如任务，线索和刺激导致参与者采用一个或另一个控制设置在当前的情况。此外，我们感兴趣的是不同的控制设置如何导致差异学习，以实现专业知识/技能。我们预计，语言控制设置会导致更快的学习，但在目标改变的情况下，灵活性也会降低。另一方面，非语言控制设置需要更长的时间才能实现自动化，但可能会导致更大的一致性效应，利用看似无关的信息。 在第二个系列的实验中，我们计划使用事件相关电位（ERP）来识别语言和非语言控制设置的神经基础。此外，还将考察线索与任务之间的语义相关性对任务绩效的影响。在系列3中，我们将研究智力、工作记忆容量和自我导向言语的个体差异如何影响语言和非语言控制设置的选择。本系列将研究控制设置的选择，以解决认知任务（即，Stroop或Flanker）作为上下文触发器旁边的个体差异。在最后一个系列中，我们将通过测试双语和单语参与者来调查终身培训的影响。我们假设，不断需要管理两种语言导致双语者不断地采用口头控制模式，因此双语的一个合格条件可能是由于口头控制设置的主导地位，在适应控制设置的灵活性降低。综上所述，我们提出了四个系列的实验，以扩大我们对认知控制的灵活性及其调节条件和所实现的技能形成的理解。

Cognitive control ensures our successful achievement of goals. Models of action control assume automatic as well as controlled processes to ensure successful completion of goal-directed actions. These two modes of action control differ in the use of language and associative learning. Next to differential involvement of control processes in actual task performance, the two control settings under investigation in this project, namely verbal and non-verbal ones, are assumed to lead to differential learning and expertise. Verbal control settings are control settings relying on language, comprising processes such as self-instruction and rather abstract, symbolic representations. In contrast, non-verbal control settings make use of formerly learnt associations and lead to the formation of episodic memory traces. Cognitive control processes and their flexible adaption to situational constraints have been studied using the task-switching paradigm, for example. In a task-switching situation, people encounter at least two tasks and are asked to alternate between them as indicated by valid task cue next to other tasks, such as the Stroop task. In a first series of experiments, we will investigate how situational characteristics such as task, cues and stimuli lead participants to adopt one or the other control setting in a current situation. Moreover, we are interested in how different control settings lead to differential learning to achieve expertise/skills. We expect that verbal control settings lead to faster learning, but also less flexibility in case of a goal change. Non-verbal control settings, on the other hand will take longer to achieve automatization, yet might lead to larger congruency effects exploiting seemingly irrelevant information. In a second series of experiments, we plan to identify the neural underpinnings of verbal and non-verbal control settings using event-related potentials (ERPs). Furthermore, the impact of semantic relatedness between cues and tasks on task performance will investigated. In series 3, we will investigate how individual differences in intelligence, working memory capacity and self-directed speech affect the choice of verbal and non-verbal control settings. This series will investigate the choice of control settings to solve cognitive tasks (i.e., Stroop or Flanker) as an individual difference next to contextual triggers. In the final series we will investigate the impact of lifelong training by testing bilingual and monolingual participants. We assume that the constant need to manage two languages leads bilinguals to adopt the verbal control mode constantly and therefore one qualifying condition of bilingualism might be a reduced flexibility in the adaption of control settings because of the dominance of verbal control settings. In sum, we suggest four series of experiments to broaden our understanding of the flexibility of cognitive control and its modulating conditions and the achieved skill formation.