About sim-2
Summary
Here we share a simulated extracellular recording dataset that was generated using a real action potential waveform and analyzed in Okatan (2018a, 2018b). The method for generating these data was first explained and used in Okatan and Kocatürk (2017), where a narrower range of firing rates was considered.
This is a resource (simulation), which could help analyze experimental neuroscience data in view of the fact that these data can contribute to the development of improved spike detection algorithms both for basic neuroscience research and for brain-computer interfaces.
The simulated data are high quality and potentially useful to individuals other than those who were involved in the generation of these data.
This data set was analyzed in Okatan (2018a, 2018b) using various methods to estimate the standard deviation of the background activity (noise) and its dependency on firing rate. This analysis revealed that the Truncation Thresholds Software (developed by Okatan and Kocatürk (2017) and available at SciCrunch.org under RRID:SCR_014637) yielded the most accurate estimate among all the methods tested. Later, in Kabakçı et al. (2020, in press), this same data set was used to develop an even more accurate estimator of the standard deviation of background activity, inspired by Otsu’s thresholding technique, which is an automatic image thresholding method that is widely used in computer vision and image processing.
It is our hope that these data can be used as a testbed in studies that aim to develop new methods for estimating noise standard deviation and spike detection in extracellular neural recordings.
Okatan, M. "A comparative study on the estimation of noise standard deviation using DATE and Truncation Thresholds." 2018 26th Signal Processing and Communications Applications Conference (SIU). IEEE, 2018a.
Okatan, M. "Comparison of Truncation Thresholds with four different robust scale estimators." 2018 26th Signal Processing and Communications Applications Conference (SIU). IEEE, 2018b.
Kabakçı, KA, Töreyin, BU, Okatan M. "Estimation of Noise Standard Deviation Using an Otsu-Based Approach in Extracellular Neural Recordings." 2020 28th Signal Processing and Communications Applications Conference (SIU). IEEE, 2020, in press.
Format of the data
The data is stored in Matlab format. A demo script for using the data in included. Details are in the document linked to at the end of this page.
How to download the data
Data may be downloaded from:
https://portal.nersc.gov/project/crcns/download/sim-2
A CRCNS.org account is required. See the download link for more instructions.
Getting help using the data.
If you have questions about using the data, post them on the forum for using data sets.
Conditions for using the data
Conditions for using the data If you publish any work using the data, please cite the publications above (Okatan and Kocatürk, 2017; Okatan, 2018a; Okatan, 2018b) also cite the data set in the following:
Murat Okatan and Mehmet Kocatürk (2020); Simulated extracellular neural recordings, with white noise of physiologically relevant variance, and firing rates in the range of 0-100 Hz, generated using the action potential of a putative pyramidal neuron recorded from the primary motor cortex of an awake behaving rat. CRCNS.org
http://dx.doi.org/10.6080/K0S180QW
The above citation uses a Digital Object Identifier (DOI) which is assigned to the data set. The DOI was created using DataCite (www.datacite.org) and the California Digital Library, "EZID" system (n2t.net/ezid/).
2018 summer course videos available online
