With an increasing aging pyramid the number of people with cognitive dysfunctions, such as various types of dementia, has grown at a high rate. However, years before the clinical onset symptoms of dementia, patients exhibit serious deficits in their oral and written communication and visual short-term memory, signs that can be measured and serve as a complement to medical evidence to discriminate the performance of healthy (elderly) controls or even predict poor cognitive health in late life. The aim of the project (2016-2019) is to apply and explore automatic linguistic analysis to language samples produced by persons at various stages of cognitive decline in order to identify important linguistic markers that can be used as a complementary, early diagnostic, prognostic or screening tool. Language, or rather linguistic performance in this context, are various forms of spoken or written language production and comprehension, e.g. transcripts of audio-recorded utterances; accessible language-based interaction through the web or measures from an eye tracking device. A correct and timely diagnosis of neurodegenerative brain disorders, such as Alzheimer’s disease, and differentiation of various types of dementia is of great importance to clinicians. The project intends to perform research in the areas of Natural Language Processing (NLP) that will allow us to broaden opportunities for multidisciplinary research activities between researchers from humanities, computer sciences and medicine.