Difficulty retrieving information (e.g., words) from memory is prevalent in neurogenic communication disorders (e.g., aphasia and dementia). Theoretical modeling of retrieval failures often relies on clinical data, despite methodological limitations (e.g., locus of retrieval failure, heterogeneity of individuals, and progression of disorder/disease). Techniques from network science are naturally capable of handling these limitations. This paper reviews recent work using a multiplex lexical network to account for word retrieval failures and highlights how network science can address the limitations of clinical data. Critically, any model we employ could impact clinical practice and patient lives, harkening the need for theoretically well-informed network models.

中文翻译：

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将临床数据纳入检索失败网络模型的方法学考虑

从记忆中提取信息（例如单词）的困难在神经源性交流障碍（例如失语症和痴呆症）中很普遍。检索失败的理论模型通常依赖于临床数据，尽管有方法学上的限制（例如，检索失败的位置、个体的异质性和疾病/疾病的进展）。来自网络科学的技术自然能够处理这些限制。本文回顾了最近使用多重词汇网络来解释单词检索失败的工作，并强调了网络科学如何解决临床数据的局限性。至关重要的是，我们采用的任何模型都可能影响临床实践和患者生活，从而需要理论上信息丰富的网络模型。