From Event: SPIE Optical Engineering + Applications, 2017
Two-photon calcium imaging can be used to monitor the activity of thousands of neurons across multiple brain areas at single-cell resolution. To harness the power of this imaging technology, neuroscientists require algorithms to detect from the imaging data the time points at which each neuron was active. We present an algorithm based on Finite Rate of Innovation (FRI) theory to detect neuronal spiking activity from this data. By exploiting the parametric structure of the signal, the activity detection problem can be reduced to the classic FRI problem of reconstructing a stream of Diracs.
Stephanie Reynolds, Jon Oñativia, Simon R. Schultz, and Pier Luigi Dragotti, "Detecting neuronal activity from calcium imaging data using FRI methods (Conference Presentation)," Proc. SPIE 10394, Wavelets and Sparsity XVII, 103940Z (Presented at SPIE Optical Engineering + Applications: August 07, 2017; Published: 26 September 2017); https://doi.org/10.1117/12.2274043.5589086574001.
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Study of self-shadowing effect as a simple means to realize nanostructured thin films and layers with special attentions to birefringent obliquely deposited thin films and photo-luminescent porous silicon