Achieving nanoscale precision using neuromorphic localization microscopy

Nyquist, H. Certain topics in telegraph transmission theory. Trans. Am. Inst. Electr. Eng. 47, 617–644 (1928).

Article  Google Scholar 

Shannon, C. E. Communication in the presence of noise. Proc. IRE 37, 10–21 (1949).

Article  Google Scholar 

Betzig, E. Proposed method for molecular optical imaging. Opt. Lett. 20, 237–239 (1995).

Article  CAS  Google Scholar 

Betzig, E. et al. Imaging intracellular fluorescent proteins at nanometer resolution. Science 313, 1642–1645 (2006).

Article  CAS  Google Scholar 

Moerner, W. E. & Kador, L. Optical detection and spectroscopy of single molecules in a solid. Phys. Rev. Lett. 62, 2535–2538 (1989).

Article  CAS  Google Scholar 

Moerner, W. E. & Basché, T. Optical spectroscopy of single impurity molecules in solids. Angew. Chem. Int. Ed. 32, 457–476 (1993).

Article  Google Scholar 

Gahlmann, A. & Moerner, W. E. Exploring bacterial cell biology with single-molecule tracking and super-resolution imaging. Nat. Rev. Microbiol. 12, 9–22 (2014).

Article  CAS  Google Scholar 

Orrit, M. & Bernard, J. Single pentacene molecules detected by fluorescence excitation in a p-terphenyl crystal. Phys. Rev. Lett. 65, 2716–2719 (1990).

Article  CAS  Google Scholar 

Lacoste, T. D. et al. Ultrahigh-resolution multicolor colocalization of single fluorescent probes. Proc. Natl Acad. Sci. USA 97, 9461–9466 (2000).

Article  CAS  Google Scholar 

Thompson, R. E., Larson, D. R. & Webb, W. W. Precise nanometer localization analysis for individual fluorescent probes. Biophys. J. 82, 2775–2783 (2002).

Article  CAS  Google Scholar 

Shroff, H. et al. Dual-color superresolution imaging of genetically expressed probes within individual adhesion complexes. Proc. Natl Acad. Sci. USA 104, 20308–20313 (2007).

Article  CAS  Google Scholar 

Gallego, G. et al. Event-based vision: a survey. IEEE Trans. Pattern Anal. Mach. Intell. https://doi.org/10.1109/TPAMI.2020.3008413 (2020).

Posch, C. Bio-inspired vision. J. Instrum. 7, C01054–C01054 (2012).

Article  Google Scholar 

Miao, S. et al. Neuromorphic vision datasets for pedestrian detection, action recognition, and fall detection. Front. Neurorobot. 13, 38 (2019).

Article  Google Scholar 

Lichtsteiner, P., Posch, C. & Delbruck, T. A 128 × 128 120 dB 15 μs latency asynchronous temporal contrast vision sensor. IEEE J. Solid-State Circuits 43, 566–576 (2008).

Article  Google Scholar 

Son, B. et al. 4.1 A 640×480 dynamic vision sensor with a 9µm pixel and 300Meps address-event representation. In Proc. 2017 IEEE International Solid-State Circuits Conference (ISSCC) 66–67 (IEEE, 2017).

Liu, S. C. & Delbruck, T. Neuromorphic sensory systems. Curr. Opin. Neurobiol. 20, 288–295 (2010).

Article  Google Scholar 

Mead, C. Neuromorphic electronic systems. Proc. IEEE 78, 1629–1636 (1990).

Article  Google Scholar 

Mangalore, A. R., Seelamantula, C. S. & Thakur, C. S. Neuromorphic fringe projection profilometry. IEEE Signal Process. Lett. 27, 1510–1514 (2020).

Article  Google Scholar 

Liao, F., Zhou, F. & Chai, Y. Neuromorphic vision sensors: principle, progress and perspectives. J. Semicond. 42, 013105 (2021).

Article  Google Scholar 

Ham, D., Park, H., Hwang, S. & Kim, K. Neuromorphic electronics based on copying and pasting the brain. Nat. Electron. 4, 635–644 (2021).

Article  Google Scholar 

Hamilton, T. J., Afshar, S., Schaik, A. V. & Tapson, J. Stochastic electronics: a neuro-inspired design paradigm for integrated circuits. Proc. IEEE 102, 843–859 (2014).

Article  Google Scholar 

Lakshmi, A., Chakraborty, A. & Thakur, C. S. Neuromorphic vision: from sensors to event-based algorithms. WIREs Data Min. Knowl. Discov. 9, e1310 (2019).

Google Scholar 

Kedia, S. et al. Real-time nanoscale organization of amyloid precursor protein. Nanoscale 12, 8200–8215 (2020).

Article  CAS  Google Scholar 

Nair, D. et al. Super-resolution imaging reveals that AMPA receptors inside synapses are dynamically organized in nanodomains regulated by PSD95. J. Neurosci. 33, 13204–13224 (2013).

Article  CAS  Google Scholar 

Mueggler, E., Rebecq, H., Gallego, G., Delbruck, T. & Scaramuzza, D. The event-camera dataset and simulator: event-based data for pose estimation, visual odometry, and SLAM. Int. J. Robot. Res. 36, 142–149 (2017).

Article  Google Scholar 

Annamalai, L., Chakraborty, A. & Thakur, C. S. EvAn: neuromorphic event-based sparse anomaly detection. Front. Neurosci. 15, 699003 (2021).

Article  Google Scholar 

Kechkar, A., Nair, D., Heilemann, M., Choquet, D. & Sibarita, J.-B. Real-time analysis and visualization for single-molecule based super-resolution microscopy. PLoS One 8, e62918 (2013).

Article  CAS  Google Scholar 

Izeddin, I. et al. Wavelet analysis for single molecule localization microscopy. Opt. Express 20, 2081–2095 (2012).

Article  CAS  Google Scholar 

Helgadottir, S., Argun, A. & Volpe, G. Digital video microscopy enhanced by deep learning. Optica 6, 506–513 (2019).

Article  Google Scholar 

Hedde, P. N. miniSPIM—a miniaturized light-sheet microscope. ACS Sens. 6, 2654–2663 (2021).

Article  CAS  Google Scholar 

Mitchell, M. W., Lundeen, J. S. & Steinberg, A. M. Super-resolving phase measurements with a multiphoton entangled state. Nature 429, 161–164 (2004).

Article  CAS  Google Scholar 

Napolitano, M. et al. Interaction-based quantum metrology showing scaling beyond the Heisenberg limit. Nature 471, 486–489 (2011).

Article  CAS  Google Scholar 

Racine, V. et al. Multiple-target tracking of 3D fluorescent objects based on simulated annealing. In Proc. 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro 1020–1023 (IEEE, 2006).

Smith, S. L., Kindermans, P.-J. & Le, Q. V. Don’t decay the learning rate, increase the batch size. In Proc. 6th International Conference on Learning Representations (OpenReview, 2018); https://openreview.net/forum?id=B1Yy1BxCZ