Abnormal accumulation of amyloid β (Aβ), α-synuclein (α-syn), and microtubule-associated protein tau (tau) have been implicated in neurodegenerative diseases including Alzheimer’s disease (AD), Parkinson’s disease (PD), and Pick’s disease (PiD). The mechanisms through which aggregated versions of α-syn, Aβ, and tau may lead to neurodegeneration are not entirely clear, however, there is emerging evidence that neuronal calcium dysregulation is at play. Two-photon microscopy is a powerful tool that can be used to measure in vivo alterations of calcium transients using animal models of neurodegeneration, and when coupled with statistical methods to characterize functional signals, can reveal features that identify and discern between distinct mouse types. We studied four mouse models of neurodegenerative diseases, wild-type (WT) α-syn, E57K α-syn, amyloid precursor protein (APP), and triple-repeat (3R)-Tau and Non-transgenic (tg) littermates using two-photon microscopy. We found that for calcium transients, simple measures such as area under the curve (AUC) and peak width in the 1-Hz whisker pad stimulation paradigm, were significantly increased for WT α-syn, E57K α-syn and APP mice across all cortical depths compared to Non-tg mice. A similar result was found in the 3-Hz paradigm in E57K α-syn mice. Spontaneous calcium transient AUC was significantly higher in WT α-syn mice and lower for APP and 3R Tau mice at 150-μm depth. Going beyond simple measure differences such as group means for AUC, signal peak width, and spontaneous calcium activity counts, we built statistical classifiers to characterize neuronal calcium signals to identify and discern, with quantified measures of confidence, all mouse types. We tested our classifier with FK506, which regulates mitochondrial calcium and found that this drug modulated the WT α-syn calcium transients to such an extent that the classifier easily identified the calcium transients as belonging to Non-tg mice. The coupling of two-photon microscopy data and statistical classifiers serves to effectively create a bioassay where the number of animals and scientific resources can be reduced without compromising the results of the experiment.
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