Sprache enthüllt visuospatiale Dysfunktion bei posteriorer kortikaler Atrophie: ein Ansatz zur natürlichen Sprachverarbeitung.

Sprache enthüllt visuospatiale Dysfunktion bei posteriorer kortikaler Atrophie: ein Ansatz zur natürlichen Sprachverarbeitung.

Posterior cortical atrophy (PCA) is a clinical syndrome characterized by visuospatial processing decline while other cognitive domains are relatively preserved at initial presentation. The syndrome involves common visuospatial symptoms like object and space perception impairment, simultanagnosia, and visual field defects. Neuroimaging shows atrophy, hypometabolism, and tau deposition in posterior brain regions. Since most cases of PCA are related to Alzheimer’s pathology, it is also known as the visual variant of AD. However, recent research indicates language abnormalities in PCA, especially in category fluency and confrontation naming. Language impairments may arise from visuospatial deficits due to the close relationship between visual and linguistic processing networks in the brain.

The study aimed to test the hypothesis that language performance in PCA patients would differ between a visually-dependent task (describing a picture) and a visually-independent task (describing a job). Speech samples from both tasks were analyzed for word frequency, word utterance latency, and the use of spatial relational words. Results showed that PCA patients had higher word frequency, slower speech due to object recognition difficulties, and fewer spatial relational words in the picture description task compared to healthy individuals. However, no significant differences were found in the job description task. Content unit analysis revealed that PCA patients had difficulty verbalizing certain elements within the picture, reflecting visuospatial processing deficits.

The study also developed a predictive model using specific language features to classify PCA patients and healthy individuals. The model showed high accuracy in distinguishing between the two groups using linguistic markers extracted from the picture description task. These findings suggest that language abnormalities in PCA may reflect underlying visuospatial deficits and highlight the potential of computational linguistic analysis for clinical evaluation and classification of PCA patients.