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Achieving nanoscale precision using neuromorphic localization microscopy

Mangalwedhekar, R and Singh, N and Thakur, CS and Seelamantula, CS and Jose, M and Nair, D (2023) Achieving nanoscale precision using neuromorphic localization microscopy. In: Nature Nanotechnology .

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Official URL: https://doi.org/10.1038/s41565-022-01291-1


Neuromorphic cameras are a new class of dynamic-vision-inspired sensors that encode the rate of change of intensity as events. They can asynchronously record intensity changes as spikes, independent of the other pixels in the receptive field, resulting in sparse measurements. This recording of such sparse events makes them ideal for imaging dynamic processes, such as the stochastic emission of isolated single molecules. Here we show the application of neuromorphic detection to localize nanoscale fluorescent objects below the diffraction limit, with a precision below 20 nm. We demonstrate a combination of neuromorphic detection with segmentation and deep learning approaches to localize and track fluorescent particles below 50 nm with millisecond temporal resolution. Furthermore, we show that combining information from events resulting from the rate of change of intensities improves the classical limit of centroid estimation of single fluorescent objects by nearly a factor of two. Additionally, we validate that using post-processed data from the neuromorphic detector at defined windows of temporal integration allows a better evaluation of the fractalized diffusion of single particle trajectories. Our observations and analysis is useful for event sensing by nonlinear neuromorphic devices to ameliorate real-time particle localization approaches at the nanoscale. © 2023, The Author(s), under exclusive licence to Springer Nature Limited.

Item Type: Journal Article
Publication: Nature Nanotechnology
Publisher: Nature Research
Additional Information: The copyright for this article belongs to Nature Research.
Keywords: Deep learning; Diffraction; Fluorescence; Nanotechnology; Object detection, Dynamic process; Dynamic vision; Intensity change; Localisation; Nano scale; Nanoscale precision; Neuromorphic; Rate of change; Receptive fields; Stochastics, Stochastic systems, article; deep learning; diffraction; diffusion; microscopy
Department/Centre: Division of Biological Sciences > Centre for Neuroscience
Division of Electrical Sciences > Electronic Systems Engineering (Formerly Centre for Electronic Design & Technology)
Division of Electrical Sciences > Electrical Engineering
Date Deposited: 10 Feb 2023 08:21
Last Modified: 10 Feb 2023 08:21
URI: https://eprints.iisc.ac.in/id/eprint/80147

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