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SELECT ••• `benchmark_benchmark`.`id`, `benchmark_benchmark`.`date_created`, `benchmark_benchmark`.`added_by_id`, `benchmark_benchmark`.`name`, `benchmark_benchmark`.`description`, `benchmark_benchmark`.`state`, `benchmark_benchmark`.`parameter`, `benchmark_benchmark`.`gt_access`, `benchmark_benchmark`.`owner_id` FROM `benchmark_benchmark` WHERE NOT (`benchmark_benchmark`.`state` IN (10, 30))
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ID DATE_CREATED ADDED_BY_ID NAME DESCRIPTION STATE PARAMETER GT_ACCESS OWNER_ID
2 2012-06-14 15:03:15 9 Quiroga2004 - Easy 1 This is the benchmark published with the paper Quiroga et. al. 2004. Downloaded from: http://www2.le.ac.uk/departments/engineering/research/bioengineering/neuroengineering-lab/spike-sorting The ground truth was shifted by 35 samples since the original timestamps were too far in front of the peaks of the spikes. 20 Noise 20 9
3 2012-06-14 15:07:50 9 Quiroga2004 - Easy 2 This is the benchmark published with the paper Quiroga et. al. 2004. Downloaded from: http://www2.le.ac.uk/departments/engineering/research/bioengineering/neuroengineering-lab/spike-sorting The ground truth was shifted by 35 samples since the original timestamps were too far in front of the peaks of the spikes. 20 Noise 20 9
4 2012-06-14 15:16:29 9 Quiroga2004 - Difficult 1 This is the benchmark published with the paper Quiroga et. al. 2004. Downloaded from: http://www2.le.ac.uk/departments/engineering/research/bioengineering/neuroengineering-lab/spike-sorting The ground truth was shifted by 35 samples since the original timestamps were too far in front of the peaks of the spikes. 20 Noise 20 9
5 2012-06-14 15:20:20 9 Quiroga2004 - Difficult 2 This is the benchmark published with the paper Quiroga et. al. 2004. Downloaded from: http://www2.le.ac.uk/departments/engineering/research/bioengineering/neuroengineering-lab/spike-sorting The ground truth was shifted by 35 samples since the original timestamps were too far in front of the peaks of the spikes. 20 Noise 20 9
7 2012-06-17 07:11:28 11 Hippocampus, tetrode, forward model rat Hippocampus recording generated using a forward model in LFPy, with realistic hippocampal morphologies with passive membranes and somatic playback of experimentally obtained voltage traces driving the cells. Sampling rate 20 kHz, contain 240 s of recordings for a tetrode geometry similar to a Thomas Recordings device 20 #neurons 10 13
9 2012-09-05 11:33:38 13 L5 tetrode, varying noise level Model rat L5 tetrode recording generated using a forward model in LFPy, with realistic L5 pyramidal cell models with active dynamics and synaptic event times from a spiking network driving the cells. Sampling rate 32 kHz, contain 120 s of recordings for a tetrode geometry similar to a Thomas Recordings device. In this benchmark, the ability of the algorithm to extract spikes at different noise levels is tested. The underlying population geometry is equal between trials, but network- and noise-realizations are different, so firing patterns are different of the post-synaptic cells. 20 Noise 10 13
10 2012-09-07 15:24:17 13 L5 tetrode, varying unit count Model rat L5 tetrode recording generated using a forward model in LFPy, with realistic L5 pyramidal cell models with active dynamics and synaptic event times from a spiking network driving the cells. Sampling rate 32 kHz, contain 120 s of recordings for a tetrode geometry similar to a Thomas Recordings device. In this benchmark, the ability of the sorting algorithm to extract an increasing number of unique units in the recordings is tested 20 Unit count 10 13
13 2012-11-19 09:43:45 23 HD-MEA Salamander retina test 2 New test for HD-MEA testdata. The signals are driven more gently, as they might have acted somewhat unphysiologically earlier. The ground truth is made in a different manner, so that one should expect fewer false positives, but maybe more false negatives? 20 ID 20 23