Semantic memory networks in neurodegenerative diseases - Dra Elena Abad
Recent studies indicate that optimal access to conceptual memory involves a complex network architecture of related concepts. Under that scenario, conceptual network models help us understand better how associative memory works in the retrieval of semantic information. In this work we analyzed verbal fluency time series of natural categories of animals by co-occurrence statistics (Goñi et al. 2011). Data groups were collected from patients suffering from multiple sclerosis and Alzheimer’s disease and compared to controls. By using statistical methods, we assessed the resulting conceptual networks and inferred specific differences between the neurodegenerative conditions, with respect to healthy subjects. Our results hint at the potential of this type of analysis as a functional biomarker of neurological diseases, but it is a work in progress, more systematic collection of different data tests could be very useful to help us to identify affected cognitive processes underlying.
Place: CELLEX sala A11