This dataset contains synthetic data from simulations (for a total duration of 10 minutes) including the activity of one multi-unit and two single-units for different firing rates and signal-to-noise ratio levels. It is intended to be used as a standardized dataset to evaluate spike sorting algorithms. Recordings were taken using a sampling rate of 24 kHz, and are comprised of spikes from a database with 594 different average spike shapes, taken from real recordings from monkey neocortex and basal ganglia. This dataset is comprised of two files: data.npy and labels.csv. data.npy contains 14,400,000 sampled voltage values, from a single channel, taken at a sampling rate of 24 kHz. labels.csv contains the timestep, spike class, amplitude (SNR), and firing rate associated with each spiking event. The original samples used to construct this dataset where previously constructed and made available in [1]. This dataset is an amalgamation of simulation files, which were previously publicly accessible at: http://www2.le.ac.uk/departments/engineering/research/bioengineering/neuroengineering-lab/software. Consequently, when using or making modifications to this dataset, in addition to acknowledging this record, [1] must also be acknowledged, as per the original author's request. [1] J. Martinez, C. Pedreira, M. J. Ison, and R. Quian Quiroga, ���Realistic simulation of extracellular recordings,��� Journal of Neuroscience Methods, vol. 184, no. 2, pp. 285���293, Nov. 2009, doi: 10.1016/j.jneumeth.2009.08.017.

{"references": ["J. Martinez, C. Pedreira, M. J. Ison, and R. Quian Quiroga, \"Realistic simulation of extracellular recordings,\" Journal of Neuroscience Methods, vol. 184, no. 2, pp. 285\u2013293, Nov. 2009, doi: 10.1016/j.jneumeth.2009.08.017."]}