Display options
Cite
Nasiotis K, Cousineau M, Tadel F, et al. Integrated open-source software for multiscale electrophysiology. Sci Data. 2019;6(1):231doi: 10.1038/s41597-019-0242-z.
Nasiotis, K., Cousineau, M., Tadel, F., Peyrache, A., Leahy, R. M., Pack, C. C., & Baillet, S. (2019). Integrated open-source software for multiscale electrophysiology. Scientific data, 6(1), 231. https://doi.org/10.1038/s41597-019-0242-z
Nasiotis, Konstantinos, et al. "Integrated open-source software for multiscale electrophysiology." Scientific data vol. 6,1 (2019): 231. doi: https://doi.org/10.1038/s41597-019-0242-z
Nasiotis K, Cousineau M, Tadel F, Peyrache A, Leahy RM, Pack CC, Baillet S. Integrated open-source software for multiscale electrophysiology. Sci Data. 2019 Oct 25;6(1):231. doi: 10.1038/s41597-019-0242-z. PMID: 31653867; PMCID: PMC6814804.
Copy Download .nbib Format: NLM
Share it on

Sci Data. 2019 Oct 25;6(1):231. doi: 10.1038/s41597-019-0242-z.

Integrated open-source software for multiscale electrophysiology.

Scientific data

Konstantinos Nasiotis, Martin Cousineau, François Tadel, Adrien Peyrache, Richard M Leahy, Christopher C Pack, Sylvain Baillet

Affiliations

  1. Montreal Neurological Institute, McGill University, Montreal, QC, Canada. [email protected].
  2. Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
  3. Grenoble Institute of Neuroscience, Grenoble, France.
  4. Signal & Image Processing Institute, University of Southern California, Los Angeles, USA.

PMID: 31653867 PMCID: PMC6814804 DOI: 10.1038/s41597-019-0242-z

Abstract

The methods for electrophysiology in neuroscience have evolved tremendously over the recent years with a growing emphasis on dense-array signal recordings. Such increased complexity and augmented wealth in the volume of data recorded, have not been accompanied by efforts to streamline and facilitate access to processing methods, which too are susceptible to grow in sophistication. Moreover, unsuccessful attempts to reproduce peer-reviewed publications indicate a problem of transparency in science. This growing problem could be tackled by unrestricted access to methods that promote research transparency and data sharing, ensuring the reproducibility of published results. Here, we provide a free, extensive, open-source software that provides data-analysis, data-management and multi-modality integration solutions for invasive neurophysiology. Users can perform their entire analysis through a user-friendly environment without the need of programming skills, in a tractable (logged) way. This work contributes to open-science, analysis standardization, transparency and reproducibility in invasive neurophysiology.

References

  1. J Neurosci Methods. 1996 Nov;69(2):175-88 - PubMed
  2. Trends Cogn Sci. 2005 Oct;9(10):474-80 - PubMed
  3. J Neurosci. 2016 Apr 6;36(14):4121-35 - PubMed
  4. Front Neuroinform. 2019 Jul 30;13:57 - PubMed
  5. Nat Rev Neurosci. 2006 May;7(5):358-66 - PubMed
  6. Proc Biol Sci. 1999 May 22;266(1423):1001-12 - PubMed
  7. Biomed Eng Online. 2010 Sep 06;9:45 - PubMed
  8. J Neurophysiol. 2011 Jan;105(1):474-86 - PubMed
  9. Neural Comput. 2004 Aug;16(8):1661-87 - PubMed
  10. J Neurosci. 2018 Jan 24;38(4):989-999 - PubMed
  11. Elife. 2016 May 26;5: - PubMed
  12. Sci Data. 2018 Jun 19;5:180110 - PubMed
  13. Front Neuroinform. 2011 Aug 22;5:13 - PubMed
  14. Nat Neurosci. 2002 Aug;5(8):805-11 - PubMed
  15. Neural Comput. 1995 Nov;7(6):1129-59 - PubMed
  16. Neuroimage. 2014 Feb 1;86:446-60 - PubMed
  17. Comput Intell Neurosci. 2011;2011:879716 - PubMed
  18. Nature. 1994 Jul 14;370(6485):140-3 - PubMed
  19. Front Neuroinform. 2014 Feb 21;8:14 - PubMed
  20. Front Comput Neurosci. 2013 Mar 26;7:21 - PubMed
  21. Med Biol Eng Comput. 1997 Mar;35(2):135-40 - PubMed
  22. Nat Neurosci. 2008 Jan;11(1):88-94 - PubMed
  23. Comput Intell Neurosci. 2011;2011:156869 - PubMed
  24. J Neurosci. 2002 May 1;22(9):3739-54 - PubMed
  25. Neuron. 1999 Sep;24(1):49-65, 111-25 - PubMed
  26. Int J Psychophysiol. 2017 Jan;111:1-4 - PubMed
  27. Proc Natl Acad Sci U S A. 2006 Nov 14;103(46):17507-12 - PubMed
  28. Nat Neurosci. 2014 Mar;17(3):455-62 - PubMed
  29. Nature. 2016 May 25;533(7604):452-4 - PubMed
  30. J Neurosci. 2008 Apr 30;28(18):4823-35 - PubMed
  31. IEEE Trans Med Imaging. 2005 Jan;24(1):12-28 - PubMed
  32. Neuron. 2015 Nov 18;88(4):629-34 - PubMed
  33. J Neurosci. 2011 Aug 31;31(35):12674-82 - PubMed
  34. J Neurosci. 2013 Nov 6;33(45):17921-36 - PubMed
  35. Nat Neurosci. 2009 Jan;12(1):70-6 - PubMed
  36. J Neurosci. 2011 Jun 15;31(24):8699-705 - PubMed
  37. Neuroimage. 2017 Oct 1;159:270-279 - PubMed
  38. Sci Data. 2016 Jun 21;3:160044 - PubMed
  39. Curr Biol. 2017 Oct 23;27(20):3086-3096.e3 - PubMed
  40. PLoS Biol. 2016 Jul 07;14(7):e1002506 - PubMed
  41. J Neural Eng. 2017 Aug;14(4):045003 - PubMed
  42. Science. 2009 May 29;324(5931):1207-10 - PubMed
  43. Phys Rev E Stat Nonlin Soft Matter Phys. 2001 Nov;64(5 Pt 1):051904 - PubMed
  44. Sci Data. 2019 Jun 25;6(1):102 - PubMed
  45. J Neurosci Methods. 2006 Sep 15;155(2):207-16 - PubMed
  46. Nat Neurosci. 2012 Jan 29;15(3):456-62, S1-2 - PubMed
  47. Neuron. 2017 Jul 19;95(2):436-446.e3 - PubMed
  48. J Neurosci Methods. 1980 Apr;2(2):203-17 - PubMed
  49. Neural Comput. 1999 Jan 1;11(1):157-92 - PubMed
  50. Science. 2007 Jun 15;316(5831):1609-12 - PubMed
  51. Science. 2001 Feb 23;291(5508):1560-3 - PubMed
  52. Proc Natl Acad Sci U S A. 2019 Mar 19;116(12):5747-5755 - PubMed
  53. Nature. 2006 Feb 9;439(7077):733-6 - PubMed
  54. Front Neuroinform. 2009 Feb 04;3:3 - PubMed
  55. IEEE Trans Med Imaging. 2001 Jan;20(1):70-80 - PubMed
  56. Science. 2006 Sep 15;313(5793):1626-8 - PubMed
  57. Neural Comput. 1999 Jan 1;11(1):91-101 - PubMed
  58. Sci Data. 2019 Jun 25;6(1):103 - PubMed
  59. Comput Intell Neurosci. 2011;2011:972050 - PubMed
  60. J Clin Neurophysiol. 2016 Oct;33(5):403-413 - PubMed
  61. J Neurophysiol. 2018 Jul 1;120(1):226-238 - PubMed
  62. Front Neurosci. 2013 Dec 26;7:267 - PubMed

MeSH terms

Publication Types

Grant support