<p indent=0mm>In the everyday life, internal goals guide us to focus on task-relevant information but inhibit task-irrelevant information that however could not be completely filtered out. Here, cognitive control is required to drive the attention in accordance with internal goals. As an important phenomenon in the field of cognitive control, conflict adaptation refers to the adaptability of cognitive control in goal-guided behaviors, which is of great significance for individuals to adapt to ever-changing environments. In the lab, conflict adaptation is indexed by a reduced conflict after conflict trials (i.e., Trial <italic>n</italic>–1 is incongruent stimulus) compared with after non-conflict trials (i.e., Trial <italic>n</italic>–1 is congruent stimulus). In order to explain this important effect, researchers have proposed a number of accounts, which could be classified into two kinds of perspectives: Attention-based control accounts and memory-based learning accounts. The former includes the well-known conflict monitoring theory, the activation-suppression theory, the negative affective theory, and the expectancy theory. Whereas, the feature-integration theory, the contingency learning hypothesis, and the temporal learning hypothesis belong to the latter. In short, the control accounts emphasize that attentional resources adjustment leads to conflict adaptation through allocating more resources to the target dimension while allocating fewer resources to the distractor dimension. On the other hand, the learning accounts propose that the binding and unbinding of memories between stimulus and responses result in conflict adaptation. Due to their different research focuses, however, the previous studies have discussed the two accounts separately, which is not conducive to the investigation and understanding of the full profiles of conflict adaptation. From our perspective, conflict adaptation in essence is a goal-directed adjustment process. Meanwhile, it is also a phenomenon of learning. Accordingly, in the present comprehensive review, we proposed a hypothesis of the binding guided by attention, which combines the control accounts and the learning accounts. Specifically, conflict adaptation does not only need to guide the allocation of attention resources through task demand, but also needs to enhance the memory representation of “stimulus-response” mapping through binding learning. The integration of the two processes should ultimately promote the occurrence of conflict adaptation. In fact, our hypothesis explains conflict adaptation by combining the Biased Competition model with the Parallel Distributed Processing model. Firstly, the Biased Competition model posits that top-down selective attention enhances neuronal activities that respond to target features and inhibits response-selective neuronal activities of distractor features. Thus, the competition between neurons is biased towards target characteristics. Secondly, the Parallel Distributed Processing model postulates that different stimulus dimensions (e.g., colors and spatial locations) are processed in parallel in different channels that however can activate the same response system, and selective attention can change the processing priority of different stimulus dimensions. To conclude, by integrating the control accounts and the learning accounts, the current hypothesis provides a comprehensive and interpretable mechanism to address conflict adaptation. To be more specific, this hypothesis proposes that conflict adaptation is ultimately generated through binding learning (i.e., the Hebbian learning) with the Parallel Distributed Processing model as the underlying mechanism. More importantly, the binding learning must be guided by the top-down attention-based control mechanism, which is achieved through the Biased Competition model. In summary, the attention-guided binding learning hypothesis provides an integrated reference frame for an in-depth understanding of the internal mechanism of conflict adaptation.
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