SignificanceAn array of techniques for targeted neuromodulation is emerging, with high potential in brain research and therapy. Calcium imaging or other forms of functional fluorescence imaging are central solutions for monitoring cortical neural responses to targeted neuromodulation, but often are confounded by thermal effects that are inter-mixed with neural responses.AimHere, we develop and demonstrate a method for effectively suppressing fluorescent thermal transients from calcium responses.ApproachWe use high precision phased-array 3 MHz focused ultrasound delivery integrated with fiberscope-based widefield fluorescence to monitor cortex-wide calcium changes. Our approach for detecting the neural activation first takes advantage of the high inter-hemispheric correlation of resting state Ca2+ dynamics and then removes the ultrasound-induced thermal effect by subtracting its simulated spatio–temporal signature from the processed profile.ResultsThe focused 350 μm-sized ultrasound stimulus triggered rapid localized activation events dominated by transient thermal responses produced by ultrasound. By employing bioheat equation to model the ultrasound heat deposition, we can recover putative neural responses to ultrasound.ConclusionsThe developed method for canceling transient thermal fluorescence quenching could also find applications with optical stimulation techniques to monitor thermal effects and disentangle them from neural responses. This approach may help deepen our understanding of the mechanisms and macroscopic effects of ultrasound neuromodulation, further paving the way for tailoring the stimulation regimes toward specific applications.
Optoacoustic images are often afflicted with distortions and artifacts corresponding to system limitations, including limited-view tomographic data. We developed a convolutional neural network (CNN) approach for optoacoustic image quality enhancement combining training on both time-resolved signals and tomographic reconstructions. Reference human finger data for training the CNN were recorded using a full-ring array system with optimal tomographic coverage. The reconstructions were further refined with a dedicated algorithm that minimizes acoustic reflection artifacts induced by acoustically mismatch structures, such as bones. The combined methodology is shown to outperform other CNN-based methods solely operating on image-domain data.
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