A network model of retrieval failures: Moving forward with incorporating clinical data
Year: 2021
Type: preprint
Abstract: Understanding retrieval failures requires a cognitive model that considers not just impaired processes, but also the role of structure. The development of a network model of retrieval failures requires the inclusion of clinical data, but there remain methodological issues in using and interpreting such data: locus of retrieval failure, heterogeneity of individuals, and progression of disorder/disease. Techniques from network science may prove useful in addressing these issues, while capturing the complexity of language disorders. Critically, any network model we employ could have downstream impact on clinical practice, which ultimately impacts patient lives, harkening the need for theoretically well-informed network models.
Author: Nichol Castro
Institution: University at Buffalo, State University of New York
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W3165268716