Heterogeneity in Posterior Cortical Atrophy: a multimodal investigation

Posterior Cortical Atrophy (PCA) is a rare neurodegenerative syndrome, most commonly associated with Alzheimer’s disease (AD) pathology. It is characterized by progressive visuospatial and visuoperceptual impairments, often accompanied by additional higher-order visual and cognitive deficits. Despite its clinical significance, the heterogeneity of PCA in terms of phenotype, underlying mechanisms, and potential treatment strategies is still not fully understood. This thesis aimed to investigate such heterogeneity through a multimodal approach integrating metabolic imaging, neuropsychological assessment, meta-analytic structural mapping, and computational modeling of noninvasive brain stimulation. Following a general introduction to PCA (Chapter 1 - General introduction: Posterior Cortical Atrophy (PCA), four empirical studies are presented. The first study (Chapter 2 - Metabolic variants of PCA: a data-driven approach for amyloid-related hypometabolism) applied hierarchical clustering to FDG-PET data from 55 patients, controlling for amyloid-related hypometabolism. This analysis delineated three main metabolic variants: right occipito-parietal, occipital (left or right), and dominant parietal. Each variant was associated with partially distinctive cognitive features, namely simultanagnosia, early visuoperceptual deficits, or Gerstmann’s syndrome. These findings suggest that the phenotypic diversity of PCA may reflect reproducible anatomo-clinical patterns. The second study (Chapter 3 - Single-word reading in PCA: a behavioral and FDG-PET study) focused on single-word reading and used a classification framework grounded in dual-route model of reading. Dyslexia was identified in around 45% of PCA patients, predominantly of peripheral type. Performance was disproportionately affected for nonwords and function words, consistent with piecemeal decoding and reduced top–down semantic facilitation. FDG-PET analyses revealed a right-lateralized pattern of hypometabolism in dyslexic cases, contrasting with a left-sided involvement in non-dyslexic patients, indicating that different posterior circuits may underlie distinct reading profiles. The third study (Chapter 4 - Gray matter atrophy and structural connectivity in PCA: a voxel-based meta-analysis) conducted a large coordinate-based voxel-based morphometry meta-analysis of PCA (likely the most extensive to date, to the best of our knowledge) pooling 18 studies (19 independent samples: total N = 916). Consistent gray matter atrophy was identified in the occipito-parietal junction, precuneus, and inferior temporal cortex, with a stronger right-hemisphere contribution and involvement of both dorsal and ventral visual streams. Structural connectivity analyses showed that these loci are embedded within long-range association tracts, reinforcing a network-based view of PCA. The fourth study (Chapter 5 - Brain stimulation modeling in PCA: from meta-analysis to optimized protocols) employed finite element modeling in SimNIBS to design optimized transcranial electrical stimulation (tES) protocols targeting meta-analytic loci of atrophy. Despite atrophy and anatomical complexity, the optimized montages achieved physiologically meaningful field strengths with favorable orientations, supporting the feasibility of model-driven neuromodulation in PCA. Taken together, these four studies indicate that PCA is not a unitary entity but rather encompasses multiple anatomo-clinical variants. By integrating metabolic, cognitive, structural, and interventional perspectives, this thesis contributes to a more refined understanding of PCA heterogeneity and suggests possible avenues for tailored diagnostic and translational approaches.