Novel advances in the characterization of dementia subtypes: from multi‐feature classification to whole brain computational models

Brain functional connectivity analyses derived from electroencephalography (EEG) provides relevant information for classification of dementia subtypes. The predictive strength of classification tools can be benefit from integrative, multi‐feature analysis of EEG which result in composite metric of functional connectivity. Additionally, significant improvement can be obtained when connectivity analyses consider the dependence between groups of regions as a whole system (high order interactions), instead of conceiving the network as a collection of pairwise interactions.