Benchmarking Spike Rate Inference in Population Calcium Imaging

Neuron

Volumn 90, Issue 3, 2016, Pages 471-482

  Theis, Lucas ^a   Berens, Philipp ^a,b   Froudarakis, Emmanouil ^b   Reimer, Jacob ^b   Román Rosón, Miroslav ^a   Baden, Tom ^a,c   Euler, Thomas ^a   Tolias, Andreas S ^a,b   Bethge, Matthias ^a,d  

^a UNIVERSITY OF TÜBINGEN   (Germany)

^b BAYLOR COLLEGE OF MEDICINE   (United States)

^c UNIVERSITY OF SUSSEX   (United Kingdom)

^d MAX PLANCK INSTITUTE FOR BIOLOGICAL CYBERNETICS   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ANIMAL CELL; ANIMAL TISSUE; ARTICLE; BAYES THEOREM; CALCIUM SIGNALING; CONTROLLED STUDY; ENTROPY; EX VIVO STUDY; FIRING RATE; IN VIVO STUDY; MALE; MOLECULAR IMAGING; MOUSE; NERVE CELL NETWORK; NONHUMAN; POISSON DISTRIBUTION; PRIORITY JOURNAL; QUALITY CONTROL; SPIKE INFERENCE ALGORITHM; SPIKE WAVE; STRIATE CORTEX; SUPPORT VECTOR MACHINE; VALIDATION PROCESS; ACTION POTENTIAL; ANIMAL; BIOLOGICAL MODEL; METABOLISM; NERVE CELL; PHYSIOLOGY; RETINA; SIGNAL PROCESSING;

CALCIUM;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; CALCIUM; MALE; MICE; MODELS, NEUROLOGICAL; NEURONS; RETINA; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84964766179     PISSN: 08966273     EISSN: 10974199     Source Type: Journal    
DOI: 10.1016/j.neuron.2016.04.014     Document Type: Article

References (37)

1. Akerboom J., Chen T.-W., Wardill T.J., Tian L., Marvin J.S., Mutlu S., Calderón N.C., Esposti F., Borghuis B.G., Sun X.R., et al. Optimization of a GCaMP calcium indicator for neural activity imaging. J. Neurosci. 2012, 32:13819-13840.
2. Briggman K.L., Euler T. Bulk electroporation and population calcium imaging in the adult mammalian retina. J. Neurophysiol. 2011, 105:2601-2609.
3. Byrd R.H., Lu P., Nocedal J., Zhu C. A limited memory algorithm for bound constrained optimization. SIAM J. Sci. Comput. 1995, 16:1190-1208.
4. Chen T.-W., Wardill T.J., Sun Y., Pulver S.R., Renninger S.L., Baohan A., Schreiter E.R., Kerr R.A., Orger M.B., Jayaraman V., et al. Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 2013, 499:295-300. 10.1038/nature12354.
5. Cotton R.J., Froudarakis E., Storer P., Saggau P., Tolias A.S. Three-dimensional mapping of microcircuit correlation structure. Front. Neural Circuits 2013, 7:151.
6. Denk W., Strickler J.H., Webb W.W. Two-photon laser scanning fluorescence microscopy. Science 1990, 248:73-76.
7. Diego F., Hamprecht F.A. Sparse space-time deconvolution for calcium image analysis. Advances in Neural Information Processing Systems 27 (NIPS 2014) 2014, 64-72. Curran Associates. Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence, K.Q. Weinberger (Eds.).
8. Euler T., Hausselt S.E., Margolis D.J., Breuninger T., Castell X., Detwiler P.B., Denk W. Eyecup scope--optical recordings of light stimulus-evoked fluorescence signals in the retina. Pflugers Arch. 2009, 457:1393-1414.
9. Fawcett T. An introduction to ROC analysis. Pattern Recognit. Lett. 2006, 27:861-874.
10. Franz V.H., Loftus G.R. Standard errors and confidence intervals in within-subjects designs: generalizing Loftus and Masson (1994) and avoiding the biases of alternative accounts. Psychon. Bull. Rev. 2012, 19:395-404.
11. Froudarakis E., Berens P., Ecker A.S., Cotton R.J., Sinz F.H., Yatsenko D., Saggau P., Bethge M., Tolias A.S. Population code in mouse V1 facilitates readout of natural scenes through increased sparseness. Nat. Neurosci. 2014, 17:851-857.
12. Ganmor, E., Krumin, M., Rossi, L.F., Carandini, M., and Simoncelli, E.P. (2016). Direct estimation of firing rates from calcium imaging data. arXiv, arXiv:1601.00364 [q-bio.NC], http://arxiv.org/abs/1601.00364.
13. Greenberg D.S., Houweling A.R., Kerr J.N.D. Population imaging of ongoing neuronal activity in the visual cortex of awake rats. Nat. Neurosci. 2008, 11:749-751.
14. Grewe B.F., Langer D., Kasper H., Kampa B.M., Helmchen F. High-speed in vivo calcium imaging reveals neuronal network activity with near-millisecond precision. Nat. Methods 2010, 7:399-405.
15. Inoue M., Takeuchi A., Horigane S., Ohkura M., Gengyo-Ando K., Fujii H., Kamijo S., Takemoto-Kimura S., Kano M., Nakai J., et al. Rational design of a high-affinity, fast, red calcium indicator R-CaMP2. Nat. Methods 2015, 12:64-70.
16. Kerr J.N.D., Denk W. Imaging in vivo: watching the brain in action. Nat. Rev. Neurosci. 2008, 9:195-205.
17. Kerr J.N.D., Greenberg D., Helmchen F. Imaging input and output of neocortical networks in vivo. Proc. Natl. Acad. Sci. USA 2005, 102:14063-14068.
18. Lütcke H., Gerhard F., Zenke F., Gerstner W., Helmchen F. Inference of neuronal network spike dynamics and topology from calcium imaging data. Front. Neural Circuits 2013, 7:201.
19. Maruyama R., Maeda K., Moroda H., Kato I., Inoue M., Miyakawa H., Aonishi T. Detecting cells using non-negative matrix factorization on calcium imaging data. Neural Netw. 2014, 55:11-19.
20. Niell C.M., Stryker M.P. Modulation of visual responses by behavioral state in mouse visual cortex. Neuron 2010, 65:472-479.
21. Oñativia J., Schultz S.R., Dragotti P.L. A finite rate of innovation algorithm for fast and accurate spike detection from two-photon calcium imaging. J. Neural Eng. 2013, 10:046017.
22. Park I.J., Bobkov Y.V., Ache B.W., Principe J.C. Quantifying bursting neuron activity from calcium signals using blind deconvolution. J. Neurosci. Methods 2013, 218:196-205.
23. Pedregosa F., Varoquaux G., Gramfort A., Michel V., Thirion B., Grisel O., Blondel M., Prettenhofer P., Weiss R., Dubourg V., et al. Scikit-learn: Machine Learning in Python. J. Mach. Learn. Res. 2011, 12:2825-2830.
24. Pnevmatikakis, E.A., Merel, J., Pakman, A., and Paninski, L. (2013). Bayesian spike inference from calcium imaging data. In 2013 Asilomar Conference on Signals, Systems and Computers, IEEE, pp. 349-353. doi:10.1109/ACSSC.2013.6810293.
25. Pnevmatikakis E.A., Soudry D., Gao Y., Machado T.A., Merel J., Pfau D., Reardon T., Mu Y., Lacefield C., Yang W., et al. Simultaneous denoising, deconvolution, and demixing of calcium imaging data. Neuron 2016, 89:285-299.
26. Reimer J., Froudarakis E., Cadwell C.R., Yatsenko D., Denfield G.H., Tolias A.S. Pupil fluctuations track fast switching of cortical states during quiet wakefulness. Neuron 2014, 84:355-362.
27. Sasaki T., Takahashi N., Matsuki N., Ikegaya Y. Fast and accurate detection of action potentials from somatic calcium fluctuations. J. Neurophysiol. 2008, 100:1668-1676.
28. St-Pierre F., Marshall J.D., Yang Y., Gong Y., Schnitzer M.J., Lin M.Z. High-fidelity optical reporting of neuronal electrical activity with an ultrafast fluorescent voltage sensor. Nat. Neurosci. 2014, 17:884-889.
29. Stosiek C., Garaschuk O., Holthoff K., Konnerth A. In vivo two-photon calcium imaging of neuronal networks. Proc. Natl. Acad. Sci. USA 2003, 100:7319-7324.
30. Svoboda, K. (2014). Simultaneous imaging and loose-seal cell-attached electrical recordings from neurons expressing a variety of genetically encoded calcium indicators. CRCNS: Collaborative Research in Computational Neuroscience. doi:10.6080/K02R3PMN.
31. Theis L., Chagas A.M., Arnstein D., Schwarz C., Bethge M. Beyond GLMs: a generative mixture modeling approach to neural system identification. PLoS Comput. Biol. 2013, 9:e1003356.
32. Thestrup T., Litzlbauer J., Bartholomäus I., Mues M., Russo L., Dana H., Kovalchuk Y., Liang Y., Kalamakis G., Laukat Y., et al. Optimized ratiometric calcium sensors for functional in vivo imaging of neurons and T lymphocytes. Nat. Methods 2014, 11:175-182.
33. Valmianski I., Shih A.Y., Driscoll J.D., Matthews D.W., Freund Y., Kleinfeld D. Automatic identification of fluorescently labeled brain cells for rapid functional imaging. J. Neurophysiol. 2010, 104:1803-1811.
34. Vogelstein J.T., Watson B.O., Packer A.M., Yuste R., Jedynak B., Paninski L. Spike inference from calcium imaging using sequential Monte Carlo methods. Biophys. J. 2009, 97:636-655.
35. Vogelstein J.T., Packer A.M., Machado T.A., Sippy T., Babadi B., Yuste R., Paninski L. Fast nonnegative deconvolution for spike train inference from population calcium imaging. J. Neurophysiol. 2010, 104:3691-3704.
36. Wilt B.A., Fitzgerald J.E., Schnitzer M.J. Photon shot noise limits on optical detection of neuronal spikes and estimation of spike timing. Biophys. J. 2013, 104:51-62.
37. Yaksi E., Friedrich R.W. Reconstruction of firing rate changes across neuronal populations by temporally deconvolved Ca2+ imaging. Nat. Methods 2006, 3:377-383.