Both Neurofibrillary tangles (NFT) and neuritic plaques (NP) are the primary neuropathologic markers of Alzheimer's disease (AD), although they are highly prevalent in normal brain aging [1–4].
Many reports have described that there are fewer differences in AD brain neuropathologic lesions between AD patients and control subjects aged 80 years and older, as compared with the considerable differences between younger persons with AD and controls [5, 6]. While there are dramatic differences in neuropathologic lesion counts between middle-aged AD cases and controls, the difference in lesion counts, while significant, is of lesser magnitude in older adult AD cases and controls.
Advanced age at death is associated with somewhat less severe dementia and fewer senile plaques and neurofibrillary tangles.
Presently there is not a consensus on whether NFT constitute a specific effect of the disease or result, in part, from a non-specific age related process.
In fact, some investigators  have suggested that, since the NFT are very prevalent in the brains of non-demented older adults, the presence of NFT in the brain is not, by itself, diagnostic of AD, and that NFT should be viewed as a later occurrence in the pathological progression of the disease.
Overall, the exact role of NFT to AD, aging, and dementia remains unclear. Even universally accepted neuropathological criteria for Alzheimer's disease differ on the diagnostic role of NFT.
The current approach of determining different cut-off points for NFT and NP density and regional distribution do not allow a 100% sensitivity and specificity in discriminating between AD brains and control subjects with normal cognitive function.
Recent studies further suggest that NFT have a stronger correlation to cognitive function than NP, not only in AD but also in normal aging and mild cognitive impairment [1, 3, 8]. The degree of cognitive impairment is a function of the distribution of NTF within the brain . In particular, the presence of high NFT density in the entorhinal and hippocampus neurons is strongly correlated to reduced cognitive performance in normal aging, whereas NFT formation in neocortical areas is associated with clinically overt AD [2–4, 9].
Neuropathologic studies [2–4, 9] have shown that the distribution of NFT in the human brain follows, in general, a predictable and hierarchical pattern whereas the distribution of NP varies among individuals. Neurofibrillary pathology is initially limited to the hippocampus and the entorhinal cortex [3, 9]. As the number of NFT increases in these areas, neurofibrillary pathology extends into the temporal cortex. Finally, tangles emerge and spread to the neocortical areas of the brain.
In a previous study  we have shown that Artificial Neural Networks analysis applied to demographic, clinical and genotype descriptors allowed a better prediction of the number of NFT in the neocortex and hippocampus than the number of NP in the same areas. These results indicate that a non-linear analysis of complex data is a valid approach in highlighting on the role of NP and NFT in the development of a degenerative process leading to AD. This supports the concept that the presence of NFT in aging may represent one of its earliest pathological substrates and play a significant role in the initial stages of memory impairment, confirming the findings [3, 9] by other authors.
An important way to challenge this hypothesis is to evaluate the predictive role of NFT and NP in two critical brain regions, i.e. neocortex and hippocampus, in distinguishing between normal subjects and those with AD.
The aim of this study is to discover the hidden and non-linear associations among Alzheimer's disease pathognomonic brain lesions and the clinical diagnosis of Alzheimer's disease in participants in the Nun Study.