Computational Mechanisms of Information-Seeking in Anxiety.

Ko-Ping Chou, Ryan Smith
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Abstract

The drive to seek information through exploratory behavior is widespread in both humans and other animals. This can be adaptive in reducing uncertainty about the best course of action within novel or changing environments. However, exploratory behaviors can also become maladaptive if subjective uncertainty levels remain too high or too low, as may happen in states of elevated anxiety. In this article, we review recent studies investigating the influence of anxiety on information-seeking behavior. We focus primarily on studies using cognitive computational models and associated behavioral tasks designed to test specific exploratory strategies, which could each be affected by anxiety in distinct ways. Results of current studies remain mixed and highlight the importance of distinguishing potential effects of task, state vs. trait anxiety, somatic vs. cognitive anxiety, and clinical vs. sub-clinical anxiety. There are also a range of different information-seeking strategies that are necessary to consider. At present, many findings could be taken to support a picture in which cognitive anxiety, and/or trait anxiety more broadly, may increase information-seeking, while somatic and/or state anxiety could have opposing effects. However, a number of previous results also appear inconsistent or task-dependent. Future studies are needed to resolve these apparent inconsistencies and more directly disentangle effects of different dimensions of anxiety on the adaptive and maladaptive use of information-seeking.

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Current topics in behavioral neurosciences
Current topics in behavioral neurosciences Neuroscience-Behavioral Neuroscience
CiteScore
4.80
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0.00%
发文量
103
期刊最新文献
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