Correction to "Determining the optimal environmental information for training computational models of lexical semantics and lexical organization" by Johns (2024).

Reports an error in "Determining the optimal environmental information for training computational models of lexical semantics and lexical organization" by Brendan T. Johns (, 2024[Sep], Vol 78[3], 163-173; see record 2025-18520-001). In the article, the bar graph for Figure 4 is not the correct graph. The correct graph is provided in the erratum. (The following abstract of the original article appeared in record 2025-18520-001.) Experiential theories of cognition propose that the external environment shapes cognitive processing, shifting emphasis from internal mechanisms to the learning of environmental structure. Computational modelling, particularly distributional models of lexical semantics (e.g., Landauer & Dumais, 1997) and models of lexical organization (e.g., Johns, 2021a), exemplifies this, highlights the influence of language experience on cognitive representations. While these models have been successful, comparatively less attention has been paid to the training materials used to train these models. Recent research has explored the role of social/communicatively oriented training materials on models of lexical semantics and organization (Johns, 2021a, 2021b, 2023, 2024), introducing discourse- and user-centred text training materials. However, determining the optimal training materials for these two model types remains an open question. This article addresses this problem by using experiential optimization (Johns, Jones, & Mewhort, 2019), which selects the materials that maximize model performance. This study will use experiential optimization to compare user-based and discourse-based corpora in optimizing models of lexical organization and semantics, offering insight into pathways towards integrating cognitive models in these areas. (PsycInfo Database Record (c) 2025 APA, all rights reserved).