메뉴 건너뛰기




Volumn 26, Issue 11, 2014, Pages 2379-2394

High-dimensional cluster analysis with the masked EM algorithm

Author keywords

[No Author keywords available]

Indexed keywords

ACTION POTENTIAL; ALGORITHM; BIOLOGICAL MODEL; CLUSTER ANALYSIS; HUMAN; NERVE CELL; PHYSIOLOGY; THEORETICAL MODEL;

EID: 84924522347     PISSN: 08997667     EISSN: 1530888X     Source Type: Journal    
DOI: 10.1162/NECO_a_00661     Document Type: Article
Times cited : (234)

References (29)
  • 1
    • 0016355478 scopus 로고
    • Anew look at the statistical model identification
    • Akaike,H. (1974).Anew look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716-723.
    • (1974) IEEE Transactions on Automatic Control, , vol.19 , Issue.6 , pp. 716-723
    • Akaike, H.1
  • 3
    • 79951551997 scopus 로고    scopus 로고
    • Kalman filter mixture model for spike sorting of non-stationary data
    • Calabrese, A., & Paninski, L. (2011). Kalman filter mixture model for spike sorting of non-stationary data. Journal of Neuroscience Methods, 196(1), 159-169.
    • (2011) Journal of Neuroscience Methods, , vol.196 , Issue.1 , pp. 159-169
    • Calabrese, A.1    Paninski, L.2
  • 5
    • 34249753618 scopus 로고
    • Support-vector networks
    • Cortes, C., & Vapnik, V. (1995). Support-vector networks. Machine Learning, 20(3), 273-297.
    • (1995) Machine Learning, , vol.20 , Issue.3 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 7
    • 84857686815 scopus 로고    scopus 로고
    • Towards reliable spike-train recordings from thousands of neurons with multielectrodes
    • Einevoll, G. T., Franke, F., Hagen, E., Pouzat, C., & Harris, K. D. (2012). Towards reliable spike-train recordings from thousands of neurons with multielectrodes. Current Opinion in Neurobiology, 22(1), 11-17.
    • (2012) Current Opinion in Neurobiology, , vol.22 , Issue.1 , pp. 11-17
    • Einevoll, G.T.1    Franke, F.2    Hagen, E.3    Pouzat, C.4    Harris, K.D.5
  • 9
    • 0035998835 scopus 로고    scopus 로고
    • Model-based clustering, discriminant analysis, and density estimation
    • Fraley,C.,&Raftery, A. E. (2002).Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association, 97(458), 611-631.
    • (2002) Journal of the American Statistical Association, , vol.97 , Issue.458 , pp. 611-631
    • Fraley, C.1    Raftery, A.E.2
  • 10
    • 77956931641 scopus 로고    scopus 로고
    • An online spike detection and spike classification algorithm capable of instantaneous resolution of overlapping spikes
    • Franke, F., Natora, M., Boucsein, C., Munk, M. H. J., & Obermayer, K. (2010). An online spike detection and spike classification algorithm capable of instantaneous resolution of overlapping spikes. Journal of Computational Neuroscience, 29(1-2), 127-148.
    • (2010) Journal of Computational Neuroscience, , vol.29 , Issue.1-2 , pp. 127-148
    • Franke, F.1    Natora, M.2    Boucsein, C.3    Munk, M.H.J.4    Obermayer, K.5
  • 12
    • 84858778469 scopus 로고    scopus 로고
    • Dependent Dirichlet process spike sorting.
    • D. Koller, D. Schuurmans, Y. Bengio,& L. Bottou (Eds.) Cambridge,MA: MIT Press.
    • Gasthaus, J., Wood, F., Gorur, D., & Teh, Y. W. (2008). Dependent Dirichlet process spike sorting. InD. Koller, D. Schuurmans, Y. Bengio,& L. Bottou (Eds.), Advances in neural information processing systems (pp. 497-504). Cambridge,MA: MIT Press.
    • (2008) Advances in neural information processing systems , pp. 497-504
    • Gasthaus, J.1    Wood, F.2    Gorur, D.3    Teh, Y.W.4
  • 13
    • 0003744820 scopus 로고    scopus 로고
    • The EMalgorithm for mixtures of factor analyzers (Tech. Rep. CRG-TR-96-1).
    • Toronto: University of Toronto.
    • Ghahramani,Z.,&Hinton,G. E. (1996). The EMalgorithm for mixtures of factor analyzers (Tech. Rep. CRG-TR-96-1). Toronto: University of Toronto.
    • (1996)
    • Ghahramani, Z.1    Hinton, G.E.2
  • 14
    • 0033928411 scopus 로고    scopus 로고
    • Accuracy of tetrode spike separation as determined by simultaneous intracellular and extracellular measurements
    • Harris, K. D., Henze, D. A., Csicsvari, J., Hirase, H., & Buzśaki, G. (2000). Accuracy of tetrode spike separation as determined by simultaneous intracellular and extracellular measurements. Journal of Neurophysiology, 84(1), 401-414.
    • (2000) Journal of Neurophysiology, , vol.84 , Issue.1 , pp. 401-414
    • Harris, K.D.1    Henze, D.A.2    Csicsvari, J.3    Hirase, H.4    Buzśaki, G.5
  • 17
    • 0013130627 scopus 로고    scopus 로고
    • A review of methods for spike sorting: the detection and classification of neural action potentials
    • Lewicki, M. S. (1998). A review of methods for spike sorting: the detection and classification of neural action potentials. Network: Computation in Neural Systems, 9(4), R53-R78.
    • (1998) Network: Computation in Neural Systems, , vol.9 , Issue.4 , pp. R53-R78
    • Lewicki, M.S.1
  • 20
    • 9444274777 scopus 로고    scopus 로고
    • Comparing clusterings by the variation of information.
    • B. Schölkopf & M. K. Warmuth (Eds.) New York: Springer.
    • Meila, M. (2003). Comparing clusterings by the variation of information. In B. Schölkopf & M. K. Warmuth (Eds.), Learning theory and kernel machines (pp. 173- 187). New York: Springer.
    • (2003) Learning theory and kernel machines , pp. 173-187
    • Meila, M.1
  • 21
    • 84877057688 scopus 로고    scopus 로고
    • A modelbased spike sorting algorithm for removing correlation artifacts in multi-neuron recordings
    • Pillow, J. W., Shlens, J., Chichilnisky, E. J., & Simoncelli, E. P. (2013). A modelbased spike sorting algorithm for removing correlation artifacts in multi-neuron recordings. PLoS ONE, 8(5), e62123.
    • (2013) PLoS ONE, , vol.8 , Issue.5 , pp. e62123
    • Pillow, J.W.1    Shlens, J.2    Chichilnisky, E.J.3    Simoncelli, E.P.4
  • 23
    • 3042526258 scopus 로고    scopus 로고
    • Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering
    • Quian Quiroga, R., Nadasdy, Z., & Ben-Shaul, Y. (2004). Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering. Neural Computation, 16(8), 1661-1687.
    • (2004) Neural Computation, , vol.16 , Issue.8 , pp. 1661-1687
    • Quian Quiroga, R.1    Nadasdy, Z.2    Ben-Shaul, Y.3
  • 26
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6(2), 461-464.
    • (1978) Annals of Statistics, , vol.6 , Issue.2 , pp. 461-464
    • Schwarz, G.1
  • 27
    • 0042626402 scopus 로고    scopus 로고
    • Robust, automatic spike sorting using mixtures of multivariate t-distributions
    • Shoham, S., Fellows,M. R.,& Normann, R. A. (2003). Robust, automatic spike sorting using mixtures of multivariate t-distributions. Journal of Neuroscience Methods, 127(2), 111-122.
    • (2003) Journal of Neuroscience Methods, , vol.127 , Issue.2 , pp. 111-122
    • Shoham, S.1    Fellows, M.R.2    Normann, R.A.3
  • 28
    • 0037389201 scopus 로고    scopus 로고
    • Automatic sorting for multi-neuronal activity recorded with tetrodes in the presence of overlapping spikes
    • Takahashi, S., Anzai, Y., & Sakurai, Y. (2003). Automatic sorting for multi-neuronal activity recorded with tetrodes in the presence of overlapping spikes. Journal of Neurophysiology, 89(4), 2245-2258.
    • (2003) Journal of Neurophysiology, , vol.89 , Issue.4 , pp. 2245-2258
    • Takahashi, S.1    Anzai, Y.2    Sakurai, Y.3
  • 29
    • 54049132069 scopus 로고    scopus 로고
    • Anonparametric Bayesian alternative to spike sorting
    • Wood, F., Black,M. J. (2008).Anonparametric Bayesian alternative to spike sorting. Journal of Neuroscience Methods, 173(1), 1-12.
    • (2008) Journal of Neuroscience Methods, , vol.173 , Issue.1 , pp. 1-12
    • Wood, F.1    Black, M.J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.