Computationally efficient simulation of extracellular recordings with multielectrode arrays

Journal of Neuroscience Methods

Volumn 211, Issue 1, 2012, Pages 133-144

  Thorbergsson, Palmi Thor ^a,b   Garwicz, Martin ^b,c   Schouenborg, Jens ^b,c   Johansson, Anders J ^a,b  

^a LUND UNIVERSITY   (Sweden)

^b LUND UNIVERSITY   (Sweden)

^c LUND UNIVERSITY   (Sweden)

Author keywords

Electrode movements simulation; Extracellular recordings; Multielectrode arrays; NEURON; Spike detection; Spike sorting

Indexed keywords

ARTICLE; ELECTRODE; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; MULTIELECTRODE ARRAY; NERVE CELL; NERVE POTENTIAL; PRIORITY JOURNAL; SIMULATION;

ALGORITHMS; ANIMALS; CA1 REGION, HIPPOCAMPAL; COMPUTER SIMULATION; ELECTRIC STIMULATION; ELECTROPHYSIOLOGICAL PHENOMENA; ELECTROPHYSIOLOGY; EXTRACELLULAR SPACE; MICROELECTRODES; MODELS, NEUROLOGICAL; NEURONS; PRINCIPAL COMPONENT ANALYSIS; PYRAMIDAL CELLS; REPRODUCIBILITY OF RESULTS; SIGNAL PROCESSING, COMPUTER-ASSISTED; SIGNAL-TO-NOISE RATIO;

EID: 84866154020     PISSN: 01650270     EISSN: 1872678X     Source Type: Journal    
DOI: 10.1016/j.jneumeth.2012.08.011     Document Type: Article

References (24)

1. Buzsáki G. Large-scale recording of neuronal ensembles. Nat Neurosci 2004, 7(5):446-451.
2. Duda R., Hart P., Stork D. Pattern classification 2001, Wiley, New York, NY. 2nd ed.
3. Fee M., Mitra P., Kleinfeld D. Automatic sorting of multiple unit neuronal signals in the presence of anisotropic and non-Gaussian variability. J Neurosci Methods 1996, 69(2):175-188.
4. Fee M.S., Mitra P.P., Kleinfeld D. Variability of extracellular spike waveforms of cortical neurons. J Neurophysiol 1996, 76(6):3823-3833.
5. Franke F., Natora M., Boucsein C., Munk M., Obermayer K. An online spike detection and spike classification algorithm capable of instantaneous resolution of overlapping spikes. J Comput Neurosci 2010, 29:127-148.
6. Franke F., Natora M., Meier P., Hagen E., Pettersen K., Linden H., et al. An automated online positioning system and simulation environment for multi-electrodes in extracellular recordings. Proc. annual international conference of the IEEE engineering in medicine and biology society (EMBC), 2010 2010, 593-597.
7. Gold C., Henze D., Koch C. Using extracellular action potential recordings to constrain compartmental models. J Comput Neurosci 2007, 23(1):39-58.
8. Gold C., Henze D., Koch C., Buzsáki G. On the origin of the extracellular action potential waveform: a modeling study. J Neurophysiol 2006, 95(5):3113-3128.
9. Harris K.D., Henze D.A., Csicsvari J., Hirase H., Buzsáki G. Accuracy of tetrode spike separation as determined by simultaneous intracellular and extracellular measurements. J Neurophysiol 2000, 84(1):401-414.
10. Heeger D. Poisson model of spike generation. Technical Report, 2000.
11. Hines M., Carnevale N. The neuron simulation environment. Neural Comput 1997, 9(6):1179-1209.
12. Holt G., Koch C. Electrical interactions via the extracellular potential near cell bodies. J Comput Neurosci 1999, 6(2):169-184.
13. Lempka S., Johnson M., Moffitt M., Otto K., Kipke D., McIntyre C. Theoretical analysis of intracortical microelectrode recordings. J Neural Eng 2011, 8:045006.
14. Lewicki M. A review of methods for spike sorting: the detection and classification of neural action potentials. Netw Comput Neural Syst 1998, 9(4):R53-R78.
15. Macke J., Berens P., Ecker A., Tolias A., Bethge M. Generating spike trains with specified correlation coefficients. Neural Comput 2009, 21(2):397-423.
16. Martinez J., Pedreira C., Ison M., Quian Quiroga R. Realistic simulation of extracellular recordings. J Neurosci Methods 2009, 184(2):285-293.
17. Obeid I., Wolf P. Evaluation of spike-detection algorithms for a brain-machine interface application. IEEE Trans Biomed Eng 2004, 51(6):905-911.
18. Pettai R. Noise in receiving systems 1984, Wiley, New York, NY.
19. Pettersen K., Einevoll G. Amplitude variability and extracellular low-pass filtering of neuronal spikes. Biophys J 2008, 94(3):784-802.
20. Pouzat C., Mazor O., Laurent G. Using noise signature to optimize spike-sorting and to assess neuronal classification quality. J Neurosci Methods 2002, 122(1):43-57.
21. Smith L.S., Mtetwa N. A tool for synthesizing spike trains with realistic interference. J Neurosci Methods 2007, 159(1):170-180.
22. The HDF Group. 2012. http://www.hdfgroup.org/.
23. Thorbergsson P., Garwicz M., Schouenborg J., Johansson A. Statistical modelling of spike libraries for simulation of extracellular recordings in the cerebellum. Proc. 32nd annual international conference of the IEEE engineering in medicine and biology society (EMBS), 2010 2010, 4250-4253.
24. Thorbergsson P., Jorntell H., Bengtsson F., Garwicz M., Schouenborg J., Johansson A. Spike library based simulator for extracellular single unit neuronal signals. Proc. 31st annual international conference of the IEEE engineering in medicine and biology society (EMBS), 2009, vol. 1 2009, 6998-7001.