Much of the attention on diet and Alzheimer's disease (AD) or cognition among the elderly has focused on the role of single nutrients or foods, while available information on dietary pattern (DP) analysis, which better reflects the complexity of the diet, is sparse. In this review, we describe different patterning approaches and present studies performed to date that have assessed the associations between DPs and risk of AD or cognitive function in the elderly. Three patterning approaches have been most commonly used: (i) hypothesis-based that use dietary quality indexes or scores (e.g. Mediterranean pattern), (ii) data-driven that use factor or cluster analysis to derive DPs, (iii) reduced rank regression which combines characteristics of the former two approaches. Despite differences existing among the approaches, DPs characterized by higher intake of fruits, vegetables, fish, nuts and legumes, and lower intake of meats, high fat dairy, and sweets seemed to be associated with lower odds of cognitive deficits or reduced risk of AD. Overall, the inherent advantages as well as the existing evidence of DP analyses strongly suggest that this approach may be valuable in AD and aging research. Further studies are warranted, though, to confirm the findings in different population settings, to address some methodological issues, and possibly utilize the information for future clinical trial design.