A robust and efficient method to recover neural events from noisy and corrupted data

International IEEE/EMBS Conference on Neural Engineering, NER

Volumn , Issue , 2013, Pages 593-596

  Dyer, Eva L ^a   Studer, Christoph ^a   Robinson, Jacob T ^a   Baraniuk, Richard G ^a  

^a Rice University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTION POTENTIALS; ANALYSIS OF DATA; ANALYSIS PROBLEMS; LARGE-SCALE STUDIES; MEASUREMENT NOISE; POST-SYNAPTIC POTENTIALS; REAL MEASURED DATA; TEMPLATE WAVEFORM;

CALCIUM; ELECTROPHYSIOLOGY;

RECOVERY;

EID: 84897713924     PISSN: 19483546     EISSN: 19483554     Source Type: Conference Proceeding    
DOI: 10.1109/NER.2013.6696004     Document Type: Conference Paper

References (11)

1. I. Stevenson and K. Kording, "How advances in neural recording affect data analysis," Nature Neurosci., vol. 14, pp. 139-142, Jan. 2011.
2. J. Clements and J. Bekkers, "Detection of spontaneous synaptic events with an optimally scaled template," Biophys J., vol. 73, no. 1, pp. 220-229, July 1997.
3. A. J. Perna-Andrade, S. P. Goswami, Y. Stickler, U. Frobe, A. Schlogl, and P. Jonas, "A deconvolution-based method with high sensitivity and temporal resolution for detection of spontaneous synaptic currents in vitro and in vivo," Biophys J., vol. 103, no. 7, pp. 1429-1439, Oct. 2012.
4. E. L. Dyer, M. F. Duarte, D. H. Johnson, and R. G. Baraniuk, "Recovering spikes from noisy neuronal calcium signals via structured sparse approximation," in Proc. 9th Intl. Conf. on Latent Variable Analysis and Signal Separation, Sep. 2010, pp. 604-611.
5. J. T. Vogelstein, B. O. Watson, A. M. Packer, R. Yuste, B. Jedynak, and L. Paninski, "Spike inference from calcium imaging using sequential Monte Carlo methods," Biophys J., vol. 97, no. 2, pp. 636-655, July 2009.
6. C. Ekanadham, D. Tranchina, and E. Simoncelli, "A blind sparse deconvolution method for neural spike identification," Proc. Adv. in Neural Processing Systems (NIPS), vol. 24, pp. 1440-1448, Dec. 2011.
7. S. S. Chen, D. L. Donoho, and M. A. Saunders, "Atomic decomposition by basis pursuit," SIAM J. Sci. Comput., vol. 20, no. 1, pp. 33-61, July 1998.
8. C. Studer, P. Kuppinger, G. Pope, and H. Bolcskei, "Recovery of sparsely corrupted signals," IEEE Trans. Inform. Theory, vol. 58, no. 5, pp. 3115-3130, May 2012.
9. C. Studer and R. G. Baraniuk, "Recovery guarantees for restoration and separation of approximately sparse signals," in Proc. 49th Annual Allerton Conf. on Commun., Control, and Computing (Allerton), Sep. 2011, pp. 736-743.
10. C. Hegde, M. F. Duarte, V. Cevher et al., "Compressive sensing recovery of spike trains using a structured sparsity model," in Proc. of Sig. Process. with Adaptive Sparse Structured Representations (SPARS), Mar. 2009.
11. A. Beck and M. Teboulle, "A fast iterative shrinkage-thresholding algorithm for linear inverse problems," SIAM Journal on Imaging Sciences, vol. 2, no. 1, pp. 183-202, Jan. 2009.