Developing systems to model AD is challenging due to the extreme complexity of microscopic neuroanatomy and uncertainty regarding key pathogenic steps. AD is primarily characterized by the extracellular deposition of misfolded amyloid-β (Aβ) peptide-containing neuritic plaques and the intracellular formation of neurofibrillary tangles (NFTs), accompanied by neuroinflammation and massive neuronal cell and synapse loss at specific brain regions [1–3]. β-Secretase (BACE1) and γ-secretase are two enzymes that cleave amyloid precursor protein (APP) to generate Aβ. The closest relationship between the Aβ plaques and cognition is found during the early stages of the disease, and this correlation decreases as NFT production and neurodegeneration progress [4–6]. Furthermore, the intensity of cognitive decline seems to correlate with the density of the neuritic plaques [7–9]. As the disease advances to later stages, the relationship between Aβ plaques and cognitive decline becomes weaker [5, 6]. A number of studies have reached similar conclusions concerning the relationship between neocortical NFTs and cognitive impairment. During the initial phase of the syndrome, NFTs are restricted to the entorhinal cortex, progressively spreading to the limbic and medial temporal lobe
