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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 `benchmark_benchmark`.`id` = 9
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ID DATE_CREATED ADDED_BY_ID NAME DESCRIPTION STATE PARAMETER GT_ACCESS OWNER_ID
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