Automated spike sorting algorithm based on Laplacian eigenmaps and k-means clustering

Journal of Neural Engineering

Volumn 8, Issue 1, 2011, Pages

  Chah, E ^a   Hok, V ^a   Della Chiesa, A ^a   Miller, J J H ^a   O'Mara, S M ^a   Reilly, R B ^a  

^a TRINITY COLLEGE DUBLIN   (Ireland)

Author keywords

[No Author keywords available]

Indexed keywords

EXPECTATION MAXIMIZATION; FEATURE SETS; IN-VIVO; K-MEANS; K-MEANS CLUSTERING; LAPLACIAN EIGENMAPS; MULTI-CHANNEL RECORDING; SIMULATED DATASETS; SPIKE SORTING ALGORITHMS; SPIKE-SORTING;

CLUSTER ANALYSIS; FEATURE EXTRACTION; LAPLACE TRANSFORMS; PRINCIPAL COMPONENT ANALYSIS; SORTING;

CLUSTERING ALGORITHMS;

ACCURACY; ALGORITHM; ARTICLE; CLASSIFICATION EXPECTATION MAXIMIZATION; CLASSIFIER; ERROR; K MEAN; MULTICHANNEL RECORDER; NERVE CELL MEMBRANE POTENTIAL; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; SIMULATION; SPIKE SORTING ALGORITHM; SPIKE WAVE; ACTION POTENTIAL; BIOLOGICAL MODEL; CLUSTER ANALYSIS; COMPARATIVE STUDY; FACTUAL DATABASE; NERVE CELL; PHYSIOLOGY;

ACTION POTENTIALS; ALGORITHMS; CLUSTER ANALYSIS; DATABASES, FACTUAL; MODELS, NEUROLOGICAL; NEURONS; PRINCIPAL COMPONENT ANALYSIS;

EID: 79952634664     PISSN: 17412560     EISSN: 17412552     Source Type: Journal    
DOI: 10.1088/1741-2560/8/1/016006     Document Type: Article

References (42)

1. Kandel E, Schwartz J H and Jessell T M 2000 Principles of Neural Science (New York: McGraw-Hill)
2. Mitra P P and Bokil H 2009 Observed Brain Dynamics (New York: Oxford University Press)
3. Brown E N, Kass R E and Mitra P P 2004 Multiple neural spike train data analysis: state-of-the-art and future challenges Nat. Neurosci. 7 456-61 (Pubitemid 38552378)
4. Rizk M et al 2009 A fully implantable 96-channel neural data acquisition system J. Neural Eng. 6 026002
5. Csicsvari J et al 2003 Massively parallel recording of unit and local field potentials with silicon-based electrodes J. Neurophysiol. 90 1314-23 (Pubitemid 37092608)
6. Fee M S, Mitra P P and Kleinfeld D 1996 Variability of extracellular spike waveforms of cortical neurons J. Neurophysiol. 76 3823-33 (Pubitemid 27009686)
7. Buzsaki G 2004 Large-scale recording of neuronal ensembles Nat. Neurosci. 7 446-51 (Pubitemid 38544574)
8. Lewicki M S 1998 A review of methods for spike sorting: the detection and classification of neural action potentials Network 9 R53-78
9. Quiroga R Q, Nadasdy Z and Ben-Shaul Y 2004 Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering Neural Comput. 16 1661-87 (Pubitemid 38835137)
10. Takekawa T, Isomura Y and Fukai T 2010 Accurate spike sorting for multi-unit recordings Eur. J. Neurosci. 31 263-72
11. Franke F, Natora M, Boucsein C, Munk M H and Obermayer K 2010 An online spike detection and spike classification algorithm capable of instantaneous resolution of overlapping spikes J. Comput. Neurosci. 29 127-48
12. Mukhopadhyay S and Ray G C 1998 A new interpretation of nonlinear energy operator and its efficacy in spike detection IEEE Trans. Biomed. Eng. 45 180-7 (Pubitemid 28128237)
13. Yang Z, Zhao Q and Liu W 2009 Improving spike separation using waveform derivatives J. Neural Eng. 6 046006
14. Harris K D, Henze D A, Csicsvari J, Hirase H and Buzsaki G 2000 Accuracy of tetrode spike separation as determined by simultaneous intracellular and extracellular measurements J. Neurophysiol. 84 401-14 (Pubitemid 30490060)
15. Thakur P H, Lu H, Hsiao S S and Johnson K O 2007 Automated optimal detection and classification of neural action potentials in extra-cellular recordings J. Neurosci. Methods 162 364-76 (Pubitemid 46527938)
16. Abeles M and Goldstein M H Jr 1977 Multispike train analysis Proc. IEEE 65 762-73
17. Vargas-Irwin C and Donoghue J P 2007 Automated spike sorting using density grid contour clustering and subtractive waveform decomposition J. Neurosci. Methods 164 1-18
18. Cheeseman P and Stutz J 1996 Bayesian classification (autoclass): theory and results Advances in Knowledge Discovery and Data Mining (Menlo Park, CA: American Association for Artificial Intelligence) 153-80
19. Hulata E, Segev R and Ben-Jacob E 2002 A method for spike sorting and detection based on wavelet packets and Shannon's mutual information J. Neurosci. Methods 117 1-12 (Pubitemid 34663896)
20. Takahashi S, Anzai Y and Sakurai Y 2003 A new approach to spike sorting for multi-neuronal activities recorded with a tetrode - how ICA can be practical Neurosci. Res. 46 265-72 (Pubitemid 36688011)
21. Harris K D http://klustakwik.sourceforge.net/
22. Gray C M, Maldonado P E, Wilson M and McNaughton B 1995 Tetrodes markedly improve the reliability and yield of multiple single-unit isolation from multi-unit recordings in cat striate cortex J. Neurosci. Methods 63 43-54 (Pubitemid 26009962)
23. Henze D A, Borhegyi Z, Csicsvari J, Mamiya A, Harris K D and Buzsaki G 2000 Intracellular features predicted by extracellular recordings in the hippocampus in vivo J. Neurophysiol. 84 390-400 (Pubitemid 30490059)
24. Anderson M I and O'Mara S M 2003 Analysis of recordings of single-unit firing and population activity in the dorsal subiculum of unrestrained, freely moving rats J. Neurophysiol. 90 655-65 (Pubitemid 37092550)
25. Belkin M and Niyogi P 2003 Laplacian eigenmaps for dimensionality reduction and data representation Neural Comput. 15 1373-96 (Pubitemid 37049796)
26. Chen C, Zhang L, Bu J, Wang C and Chen W 2010 Constrained Laplacian eigenmap for dimensionality reduction Neurocomputing 73 951-8
27. Ghanbari Y, Spence L and Papamichalis P 2009 A graph-Laplacian-based feature extraction algorithm for neural spike sorting Conf. Proc. IEEE Eng. Med. Biol. Soc. 2009 3142-5
28. Ghanbari Y, Papamichalis P and Spence L 2010 Graph-spectrum-based neural spike features for stereotrodes and tetrodes IEEE Int. Conf. on Acoustics, Speech, and Signal Processing pp 598-601
29. Wheeler B C and Heetderks W J 1982 A comparison of techniques for classification of multiple neural signals IEEE Trans. Biomed. Eng. 29 752-9 (Pubitemid 13178148)
30. Moffitt M A and McIntyre C C 2005 Model-based analysis of cortical recording with silicon microelectrodes Clin. Neurophysiol. 116 2240-50 (Pubitemid 41262214)
31. Theodoridis S and Koutroumbas K 1998 Pattern Recognition (San Diego: Academic)
32. Pakhira M K, Bandyopadhyay S and Maulik U 2004 Validity index for crisp and fuzzy clusters Pattern Recognit. 37 487-501 (Pubitemid 38003088)
33. Celeux G and Govaert G 1992 A classification EM algorithm for clustering and two stochastic versions Comput. Stat. Data Anal. 14 315-32
34. Friedman M 1937 The use of ranks to avoid the assumption of normality implicit in the analysis of variance J. Am. Stat. Assoc. 32 675-701
35. Sheldon M R, Fillyaw M J and Thompson W D 1996 The use and interpretation of the Friedman test in the analysis of ordinal-scale data in repeated measures designs Physiother. Res. Int. 1 221-8
36. von Luxburg U 2007 A tutorial on spectral clustering Stat. Comput. 17 395-416
37. Atiya A F 1992 Recognition of multiunit neural signals IEEE Trans. Biomed. Eng. 39 723-9 (Pubitemid 23133302)
38. Lewicki M S 1994 Bayesian modeling and classification of neural signals Neural Computation. 6 1005-30
39. Segev R, Goodhouse J, Puchalla J and Berry M J II 2004 Recording spikes from a large fraction of the ganglion cells in a retinal patch Nat. Neurosci. 7 1154-61 (Pubitemid 41184457)
40. Zhang P M, Wu J Y, Zhou Y, Liang P J and Yuan J Q 2004 Spike sorting based on automatic template reconstruction with a partial solution to the overlapping problem J. Neurosci. Methods 135 55-65 (Pubitemid 38333125)
41. Takahashi S, Anzai Y and Sakurai Y 2003 Automatic sorting for multi-neuronal activity recorded with tetrodes in the presence of overlapping spikes J. Neurophysiol. 89 2245-58 (Pubitemid 36444277)
42. Meier R, Egert U, Aertsen A and Nawrot M P 2008 FIND - a unified framework for neural data analysis Neural Netw. 21 1085-93