Semantic Memory Organization in Japanese Patients With Schizophrenia Examined With Category Fluency - Sumiyoshi, Chika; Fujino, Haruo; Sumiyoshi, Tomiki; Yasuda, Yuka; Yamamori, Hidenaga; Fujimoto, Michiko; Hashimoto, Ryota (Frontiers in Psychiatry, 2018)
Background Disorganization of semantic memory in patients with schizophrenia has been studied by referring to their category fluency performance. Recently, data-mining techniques such as singular value decomposition (SVD) analysis have been reported to be effective in elucidating the latent semantic memory structure in patients with schizophrenia. The aim of this study is to investigate semantic memory organization in patients with schizophrenia by introducing a novel method based on data-mining approach. Method Category fluency data were collected from 181 patients with schizophrenia and 335 healthy controls at the Department of Psychiatry, Osaka University. The 20 most frequently reported animals were chosen for SVD analysis. In the two-dimensional (2D) solution, item vectors (i.e., animal names) were plotted in the 2D space of each group. In the six-dimensional (6D) solution, inter-item similarities (i.e., cosines) were calculated among items. Cosine charts were also created for the six most frequent items to show the similarities to other animal items. Results In 2D spatial representation, the 6 most frequent items were grouped in same clusters (i.e., dog, cat as pet cluster, lion, tiger as wild/carnivorous cluster, and elephant, giraffe as wild/herbivorous cluster) between patients and healthy adults. As for 6D spatial cosines, the correlations (Pearson’s r) between 17 items commonly generated in the two groups were moderately high. However, cosine charts created for the 3 pairs from the 6 most frequent animals (dog-cat, lion-tiger, elephant-giraffe) showed that pairwise similarities between other animals were less salient in patients with schizophrenia. Discussion Semantic memory organization in patients with schizophrenia, revealed by SVD analysis, did not appear to be seriously disorganized in the 2D space representation, maintaining a similar clustering structure to that in healthy controls for common animals. However, the coherence of those animals was less salient in 6D space, lacking pair-wise similarities to other members of the animal category. These results suggested there were subtle but structural differences between the two groups. A data-mining approach like SVD analysis seems to be effective in evaluating semantic memory in patients with schizophrenia, providing both a visual representation and an objective measure of the structural differences compared to healthy adults.