Table 2

Number of classification errors for all simulated examples and overlapping spike shapes
Example no. Noise level Number of overlapping spikes False matches
N°. %
1 2 3 4
1. 1 [0.05] 785 161 20.5
2. [0.10] 769 146 19.0
3. [0.15] 784 185 23.6
4. [0.20] 796 165 20.7
5. [0.25] 712 208 29.2
6. [0.30] 846 250 29.6
7. [0.35] 832 270 32.5
8. [0.40] 741 270 36.4
9. 2 [0.05] 791 152 19.2
10. [0.10] 826 167 20.2
11. [0.15] 763 152 19.9
12. [0.20] 811 301 37.1
13. 3 [0.05] 767 88 11.5
14. [0.10] 810 131 16.2
15. [0.15] 812 152 18.7
16. [0.20] 790 287 36.3
17. 4 [0.05] 829 39 4.7
18 [0.10] 720 114 15.8
19. [0.15] 809 209 25.8
20. [0.20] 777 282 36.3
Average 789 186 23.7

Noise level is represented in terms of its standard deviation relative to the peak amplitude of the spikes. All spike classes had a peak value of 1. The absolute number of false matching spikes is shown in column 3 as the outcome of our algorithm corresponding to the datasets containing overlapped spikes (column 2).

Oliynyk et al.

Oliynyk et al. BMC Neuroscience 2012 13:96   doi:10.1186/1471-2202-13-96

Open Data