Use of mouse models to test new interventions for Alzheimer’s disease is a cornerstone of Alzheimer’s disease therapeutic development. Current preclinical evaluation of Alzheimer’s disease pathology relies mostly on post-mortem analyses of animal models, which limits researchers’ ability to follow the progression of the disease or the efficacy of treatments over time. In search of a method to observe the development of the disease and its response to therapies in real-time, researchers at the University of Strathclyde and the Italian Institute of Technology (IIT) investigated fiber photometry, an optical approach to monitoring neural activity in live animals. The researchers expanded the capabilities of in vivo fiber photometry, using it to examine the pathological features of an AD mouse model in a freely behaving condition. This approach to could help researchers uncover information about how Alzheimer's disease develops and enable more flexible testing of potential therapies. Using a conventional, flat fiber-based photometry approach, the team confirmed in its initial experiments that amyloid plaque signals could be monitored across multiple depths in in vivo Alzheimer's disease mice models under anesthesia. Instead of relying on genetically encoded sensors, the researchers implemented a non-genetic strategy, and injected the mice with a blood-brain-barrier-permeable fluorescent tracer, Methoxy-X04. The hydrophobic structure of this compound allows it to enter the brain, where it specifically binds to beta-sheets found within amyloid fibrils, allowing visualization of amyloid plaques in Alzheimer's disease models. The team found that the depth profiles of the in vivo fluorescent signals correlated with the plaque density measured afterward in brain slices. A machine learning model could distinguish between the in vivo fluorescent signals of mice with and mice without amyloid plaques based on the depth profiles of their signals. The researchers then assessed whether tapered optical fibers would allow depth-resolved photometry for plaque signals in ex vivo tissue. Upon examination of brain tissue slices, they found that the tapered fibers reliably tracked plaque distribution. After validating the tapered fiber-based photometry approach in freely behaving mice, implantation into chronically in living mice revealed depth-specific increases in fluorescence after Methoxy-X04 injection in Alzheimer's disease model mice, but not in healthy controls. The technique showed age-dependent signal increases consistent with disease progression. By exploiting the photonic properties of tapered fibers, the researchers establish depth-resolved photometry of amyloid plaque signals in vivo and ex vivo. Combining a plaque-binding fluorescent dye with flat and tapered optical fibers enables depth-resolved monitoring across brain regions during natural behavior, offering a minimally invasive way to study disease progression and therapeutic effects in real time. Image courtesy of University of Strathclyde/S. Sakata (top-left image created in BioRender. In contrast to existing methods, such as optoacoustic tomography, the optical fiber-based approach allows long-term monitoring of amyloid pathology across multiple deep brain regions in freely behaving animals. While the photometry technique cannot resolve individual plaques, it can provide a minimally invasive way to track pathological changes across time and across brain regions. Amyloid plaques have long been recognized as a hallmark of Alzheimer's disease. Recent therapeutics targeting amyloid-β protofibrils or deposited amyloid plaques have proven effective in patients, and researchers have successfully translated early preclinical mouse data to the clinic. As such, evaluating new interventions in preclinical mouse models should continue to play an important role in accelerating future treatments for Alzheimer's disease. The results of this research demonstrate the potential of using fiber optic photometry, which has been widely used in the neuroscience community, to monitor plaque signals in order to optimize therapeutic approaches and develop intervention strategies for Alzheimer's in a preclinical setting. The research was published in Neurophotonics (www.doi.org/10.1117/1.NPh.12.3.035014).