Abstract
SIGNIFICANCE: Several miniaturized optical neuroimaging devices for preclinical studies mimicking benchtop instrumentation have been proposed in the past. However, they are generally relatively large, complex, and power-hungry, limiting their usability for long-term measurements in freely moving animals. Further, there is limited research in the development of algorithms to analyze long-term signals. AIM: We aim to develop a cost-effective, easy-to-use miniaturized intrinsic optical monitoring system (TinyIOMS) that can be reliably used to record spontaneous and stimulus-evoked hemodynamic changes and further cluster brain states based on hemodynamic features. APPROACH: We present the design and fabrication of TinyIOMS ( 8 mm × 13 mm × 9 mm3 , 1.2 g with battery). A standard camera-based widefield system (WFIOS) is used to validate the TinyIOMS signals. Next, TinyIOMS is used to continuously record stimulus-evoked activity and spontaneous activity for 7 h in chronically implanted mice. We further show up to 2 days of intermittent recording from an animal. An unsupervised machine learning algorithm is used to analyze the TinyIOMS signals. RESULTS: We observed that the TinyIOMS data is comparable to the WFIOS data. Stimulus-evoked activity recorded using the TinyIOMS was distinguishable based on stimulus magnitude. Using TinyIOMS, we successfully achieved 7 h of continuous recording and up to 2 days of intermittent recording in its home cage placed in the animal housing facility, i.e., outside a controlled lab environment. Using an unsupervised machine learning algorithm ( k -means clustering), we observed the grouping of data into two clusters representing asleep and awake states with an accuracy of ∼ 91% . The same algorithm was then applied to the 2-day-long dataset, where similar clusters emerged. CONCLUSIONS: TinyIOMS can be used for long-term hemodynamic monitoring applications in mice. Results indicate that the device is suitable for measurements in freely moving mice during behavioral studies synchronized with behavioral video monitoring and external stimuli.