ABSTRACT Primary progressive aphasia (PPA) is a clinical syndrome characterized by isolated, progressive loss of speech and language abilities. PPA occurs when neurodegeneration selectively targets the language networks in the brain. It is most often caused by molecular and pathological changes typical of Frontotemporal lobar degeneration (FTLD) or Alzheimer?s disease (AD). Over the past 12 years of this project, we have studied a cohort of 300 well-characterized PPA patients, and have obtained an unprecedented number of post-mortem samples. We have published more than 130 papers, and have made discoveries that were essential in characterizing the PPA clinical variants and in defining the main clinico-anatomical presentations: the nonfluent/agrammatic (nfvPPA), semantic (svPPA) and logopenic (lvPPA) variants, each associated with a different probability of underlying molecular causes. Despite this significant progress, many questions regarding cognitive presentation, clinical course and biological basis remain unanswered. In this project, we will apply novel neuroimaging and cognitive neuroscience techniques to study clinical symptoms, in-vivo tau deposition, longitudinal progression, and prediction of pathological and molecular changes in PPA. We propose a five-year cross-sectional and longitudinal study of the cognitive, anatomical and biological features of more than 200 newly recruited individuals with PPA. In particular, in Aim 1, we will study the differential contribution of white matter, gray matter, and functional changes in the brain to the development of PPA symptoms, and use new tasks to investigate semantic, grammatical, and orthographic functions. In Aim 2, we will apply the novel positron emission tomography [18F]AV1451 tau ligand to study how in-vivo molecular brain changes relate to clinical and cognitive factors in lvPPA and nfvPPA. Finally, in Aim 3, we will study PPA progression, and the validity of the network-spread theory of neurodegeneration, by relating longitudinal neuroimaging changes in patients to the healthy connective architecture. Furthermore, we will perform multivariate analyses on the combined clinical, neuroimaging, genetic, and pathological data, in the largest and most comprehensive PPA dataset ever examined to determine whether molecular diagnosis can be predicted in-vivo. This project will provide novel evidence on the neural basis of language, and provide crucial data for the diagnosis of neurodegenerative diseases in their early stages, when treatment can be most effective.