Multichannel electrophysiological spike sorting via joint dictionary learning and mixture modeling

IEEE Transactions on Biomedical Engineering

Volumn 61, Issue 1, 2014, Pages 41-54

  Carlson, David E ^a   Vogelstein, Joshua T ^a,b   Wu, Qisong ^a   Lian, Wenzhao ^a   Zhou, Mingyuan ^a   Stoetzner, Colin R ^c   Kipke, Daryl ^c   Weber, Douglas ^d   Dunson, David B ^b   Carin, Lawrence ^a  

^a Duke University   (United States)

^b Duke University   (United States)

^c UNIVERSITY OF MICHIGAN   (United States)

^d UNIVERSITY OF PITTSBURGH   (United States)

Author keywords

Bayesian; Clustering; Dirichlet process; Spike sorting

Indexed keywords

ACTION POTENTIAL DETECTION; BAYESIAN; BAYESIAN METHODOLOGY; CLUSTERING; DIRICHLET PROCESS; SHARING INFORMATION; SPIKE-SORTING; STATE-OF-THE-ART PERFORMANCE;

ELECTROPHYSIOLOGY; MIXTURES;

SORTING;

ACTION POTENTIAL; ANIMAL EXPERIMENT; ARTICLE; ARTIFACT; BAYESIAN LEARNING; CLASSIFICATION; CLUSTER ANALYSIS; CONTROLLED STUDY; DATA PROCESSING; ELECTROPHYSIOLOGY; INFORMATION PROCESSING; JOINT DICTIONARY LEARNING; MACHINE LEARNING; MATHEMATICAL MODEL; MATHEMATICAL PARAMETERS; MULTICHANNEL RECORDER; NERVE CELL; NERVE CONDUCTION; NONHUMAN; RAT; SPIKE SORTING;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; ARTIFICIAL INTELLIGENCE; ELECTROPHYSIOLOGICAL PHENOMENA; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; NEURONS; RATS;

EID: 84891595145     PISSN: 00189294     EISSN: 15582531     Source Type: Journal    
DOI: 10.1109/TBME.2013.2275751     Document Type: Article

References (39)

1. D. A. Adamos, N. A. Laskaris, E. K. Kosmidis, and G. Theophilidis, "NASS: An empirical approach to spike sorting with overlap resolution based on a hybrid noise-assisted methodology," J. Neurosci. Methods, vol. 190, no. 1, pp. 129-142, 2010.
2. D. A. Adamos, N. A. Laskaris, E. K. Kosmidis, and G. Theophilidis, "In quest of the missing neuron: Spike sorting based on dominant-sets clustering," Comput. Methods Progr. Biomed., vol. 107, no. 1, pp. 28-35, 2012.
3. F. J. Anscombe, "The statistical analysis of insect counts based on the negative binomial distribution," Biometrics, vol. 5, no. 2, pp. 165-173, 1949.
4. C. Antoniak, "Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems," Ann. Statist., vol. 2, pp. 1152-1174, 1974.
5. I. Bar-Gad, Y. Ritov, E. Vaadia, and H. Bergman, "Failure in identification of overlapping spikes from multiple neuron activity causes artificial correlations," J. Neurosci. Methods, vol. 107, no. 1-2, pp. 1-13, 2001. (Pubitemid 32487604)
6. R. Biran, D. C. Martin, and P. A. Tresco, "Neuronal cell loss accompanies the brain tissue response to chronically implanted silicon microelectrode arrays," Exp. Neurol., vol. 195, pp. 115-126, 2005. (Pubitemid 41116819)
7. C. M. Bishop, Pattern Recognition and Machine Learning. New York, NY, USA: Springer-Verlag, 2006.
8. A. Calabrese and L. Paniski, "Kalman filter mixture model for spike sorting of non-stationary data," J. Neurosci. Methods, vol. 196, pp. 159-169, 2011.
9. B. Chen, D. E. Carlson, and L. Carin, "On the analysis of multi-channel neural spike data," in Proc. Adv. Neural Inform. Process. Syst., 2011, vol. 24, pp. 936-944.
10. J. P. Donoghue, A. Nurmikko, M. Black, and L. R. Hochberg, "Assistive technology and robotic control using mortor cortex ensemble-based neural interface systems in humans with tetraplegia," J. Physiol., vol. 579, pp. 603-611, 2007. (Pubitemid 46404344)
11. G. T. Einevoll, F. Franke, E. Hagen, C. Pouzat, and K. D. Harris, "Towards reliable spike-train recordings from thousands of neurons with multielectrodes," Curr. Opin. Neurobiol., vol. 22, no. 1, pp. 11-17, 2012.
12. A. A. Emondi, S. P. Rebrik, A. V. Kurgansky, and K. D. Miller, "Tracking neurons recorded from tetrodes across time," J. Neurosci. Methods, vol. 135, pp. 95-105, 2004. (Pubitemid 38333130)
13. F. Franke, M. Natora, C. Boucsein, M. H. J. Munk, and K. Obermayer, "An online spike detection and spike classification algorithm capable of instantaneous resolution of overlapping spikes," J. Comput. Neurosci., vol. 29, no. 1-2, pp. 127-148, 2010.
14. J. Gasthaus, F. Wood, D. Gorur, and Y. W. Teh, "Dependent Dirichlet process spike sorting," in Proc. Adv. Neural Inf. Process. Syst., 2009, pp. 497-504
15. D. Gorur, C. Rasmussen, A. Tolias, F. Sinz, and N. Logothetis, "Modelling spikes with mixtures of factor analysers," Pattern Recognit., vol. 3175, pp. 391-398, 2004.
16. T. L. Griffiths and Z. Ghahramani, "Infinite latent feature models and the Indian buffet process," in Proc. Adv. Neural Inf. Process. Syst., 2005, pp. 475-482.
17. D. A. Henze, Z. Borhegyi, J. Csicsvari, A. Mamiya, K. D. Harris, and G. Buzsaki, "Intracellular features predicted by extracellular recordings in the hippocampus in vivo," J. Neurophysiol., vol. 84, pp. 390-400, 2000. (Pubitemid 30490059)
18. J. A. Herbst, S. Gammeter, D. Ferrero, and R. H. R. Hahnloser, "Spike sorting with hidden Markov models," J. Neurosci. Methods, vol. 174, no. 1, pp. 126-134, 2008.
19. N. L. Johnson, A. W. Kemp, and S. Kotz, Univariate Discrete Distributions. New York, NY, USA: Wiley, 2005.
20. J. C. Letelier and P. P. Weber, "Spike sorting based on discrete wavelet transform coefficients," J. Neurosci. Methods, vol. 101, pp. 93-106, 2000.
21. M. S. Lewicki, "A review of methods for spike sorting: The detection and classification of neural action potentials," Netw.: Comput. Neural Syst., vol. 9, pp. 53-68, 1998.
22. M. A. L. Nicolelis and M. A. Lebedev, "Principles of neural ensemble physiology underlying the operation of brain-machine interfaces," Nature Rev. Neurosci., vol. 10, no. 7, pp. 530-540, 2009.
23. C. Pedreira, Z. J. Martinez, M. J. Ison, and R. Q. Quiroga, "How many neurons can we see with current spike sorting algorithms?," J. Neurosci. Methods, vol. 211, no. 1, pp. 58-65, 2012.
24. F. D. Rieke, R. Warland, D. R. V. Steveninck, and W. Bialek, Spikes: Exploring the Neural Code. vol. 20, Cambridge, MA, USA: MIT Press, 1997.
25. D. A. Spielman, H. Wang, and J. Wright, "Exact recovery of sparsely-used dictionaries," Comput. Res. Reposit., 2012
26. S. Suner, M. R. Fellows, C. Vargas-Irwin, G. K. Nakata, and J. P. Donoghue, "Reliability of signals from a chronically implanted, silicon-based electrode array in non-human primate primary motor cortex," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 13, no. 4, pp. 524-541, Dec. 2005. (Pubitemid 43015559)
27. D. H. Szarowski, M. D. Andersen, S. Retterer, A. J. Spence, M. Isaacson, H. G. Craighead, J. N. Turner, and W. Shain, "Brain responses to micromachined silicon devices," Brain Res., vol. 983, pp. 23-25, 2003.
28. Y. W. Teh, "Dirichlet processes, and " i, Encyclopedia of Machine Learning. New York, NY, USA: Springer-Verlag, 2010.
29. Y. W. Teh, M. I. Jordan, M. J. Beal, and D. M. Blei, "Hierarchical dirichlet processes," J. Amer. Statist. Assoc., vol. 101, pp. 1566-1581, 2006.
30. C. Vargas-Irwin and J. P. Donoghue, "Automated spike sorting using density grid contour clustering and subtractive waveform decomposition," J. Neurosci. Methods, vol. 164, no. 1, pp. 1-18, 2007. (Pubitemid 46935967)
31. V. Ventura, "Automatic spike sorting using tuning information," Neural Comput., vol. 21, pp. 2466-2501, 2009.
32. C. Wang, J. Paisley, and D. Blei, "Online variational inference for the hierarchical Dirichlet process," presented at the 14th Int. Conf. Artificial Intelligence and Statistics, Ft. Lauderdale, FL, USA, 2011
33. X. Wang and A. McCallum, "Topics over time:Anon-Markov continuoustime model of topical trends," in Proc. 12th ACM SIGKDD Int. Conf. Knowl. Discov. Data Mining, 2006, pp. 424-433. (Pubitemid 44535539)
34. B. C. Wheeler, "Multi-unit neural spike sorting," Ann. Biomed. Eng., vol. 19, no. 5, 1991.
35. S. Williamson, C. Wang, K. A. Heller, and D. M. Blei, "The IBP compound Dirichlet process and its application to focused topic modeling," in Proc. Int. Conf. Mach. Learn., 2010.
36. J. Wright, Y. Peng, Y. Ma, A. Ganesh, and S. Rao, "Robust principal component analysis: Exact recovery of corrupted low-rank matrices by convex optimization," in Proc. Adv. Neural Inf. Process. Syst, 2009, pp. 2080-2088.
37. J. Zhang, Z. Ghahramani, and Y. Yang, "A probabilistic model for online document clustering with application to novelty detection," in Proc. Adv. Neural Inf. Process. Syst., 2004, pp. 1617-1624.
38. M. Zhou, H. Chen, J. Paisley, L. Ren, L. Li, Z. Xing, D. B. Dunson, G. Sapiro, and L. Carin, "Nonparametric Bayesian dictionary learning for analysis of noisy and incomplete images," IEEE Trans. Image Process., vol. 21, no. 1, pp. 130-144, Jan. 2012.
39. M. Zhou, L. A. Hannah, D. B. Dunson, and L. Carin, "Beta-negative binomial process and Poisson factor analysis," in Proc. Artif. Intell. Statist., 2012.