Review Figure 3

<b>Figure 3: </b>Summary of co-keyword analysis completed across the Full Corpus, and both Decades. Keyword co-occurrence matrices are visualized using graph theory methods, and modularity analytics applied to identify self-clustering networks (<b>Panel A)</b>. To aid accessibility, these modules are visualized as colored concentric rings, each reflecting a module’s singular rank and theme (<b>Psychological: Blue; Physiological: Red,[1] Panel B)</b>. Node size reflects normalized Eigenvector centrality, with prominent internal nodes labeled (see <b>Supplementary Section 1</b> for full prominent node listing). Modular internal and external connectivity metrics were extracted, normalized and visualized relative to normalized corpus median values via a strategic diagram (<b>Panel C</b>). Providing a summary of internal connectivity along the Y-axis, this provides a measure of the cohesiveness of a thematic trend – with highly developed and interconnected themes reflected in higher levels of internal connectivity. Summative metrics on the X-axis provide an overview of external connectivity, demonstrating the central dominance of a theme to the research domain. The range of corpus internal and external connections display significant growth between Decade 1 and Decade 2, in line with research proliferation (see <b>Figure 2</b>), coupled with simultaneous constriction in modularity, perhaps indicative of the development of cohesive research themes (<b>Figure 2 Panel D</b>)—see <b>Supplementary Table 4</b>. For yearly (1994, 2006, 2015) assessment see <b>Supplementary Figure 3</b>. <br>