A comparative study on the estimation of noise standard deviation using DATE and truncation thresholds

D-dimensional amplitude trimmed estimator (DATE) is used for estimating the noise standard deviation in data that can be modelled as a signal in additive white Gaussian noise. Truncation thresholds are a pair of amplitude thresholds that are used for spike detection in extracellular neural recordings. Noise standard deviation is estimated as a byproduct of the computation of the truncation thresholds. Here, standard deviation estimates obtained using DATE and truncation thresholds are compared in realistic simulations of extracellular neural recordings. The results show that noise standard deviation is estimated more accurately and faster with truncation thresholds. These findings are important for developing a suitable method for amplitude thresholding in brain-machine-interfaces.

[1]  M S Lewicki,et al.  A review of methods for spike sorting: the detection and classification of neural action potentials. , 1998, Network.

[2]  Dominique Pastor,et al.  Robust Estimation of Noise Standard Deviation in Presence of Signals With Unknown Distributions and Occurrences , 2012, IEEE Transactions on Signal Processing.

[3]  Andrew S. Whitford,et al.  Cortical control of a prosthetic arm for self-feeding , 2008, Nature.

[4]  John P. Donoghue,et al.  Automated spike sorting using density grid contour clustering and subtractive waveform decomposition , 2007, Journal of Neuroscience Methods.

[5]  R. Quian Quiroga,et al.  Unsupervised Spike Detection and Sorting with Wavelets and Superparamagnetic Clustering , 2004, Neural Computation.

[6]  M. Okatan,et al.  Firing rate dependence of "truncation thresholds" , 2015, 2015 Medical Technologies National Conference (TIPTEKNO).

[7]  G. Buzsáki.  Large-scale recording of neuronal ensembles , 2004, Nature Neuroscience.

[8]  Murat Okatan,et al.  Truncation thresholds: a pair of spike detection thresholds computed using truncated probability distributions , 2017 .

[9]  I. Johnstone,et al.  Ideal spatial adaptation by wavelet shrinkage , 1994 .

[10]  Valérie Ventura,et al.  To sort or not to sort: the impact of spike-sorting on neural decoding performance , 2014, Journal of neural engineering.

[11]  D. Hubel.  Tungsten Microelectrode for Recording from Single Units. , 1957, Science.

[12]  Vijay Viswam,et al.  In Vitro Multi-Functional Microelectrode Array Featuring 59 760 Electrodes, 2048 Electrophysiology Channels, Stimulation, Impedance Measurement, and Neurotransmitter Detection Channels , 2017, IEEE Journal of Solid-State Circuits.

[13]  David R. Anderson,et al.  Model Selection and Multimodel Inference , 2003 .