NEURAL SPIKE SORTING AND CLASSIFICATION
Keywords:
biomedical signal processing, Spike Sorting, Classification, PCA, Dimensionality reduction, Feature Extraction, neural signal processing.
Abstract
Spike sorting is the process of separating the extracellular recording of the brain signal into one unit
activity. There are a number of proposed algorithms for this purpose, but there is still no acceptable
solution. In this paper a spike sorting method has been proposed based on the Euclidean distance of the
most effective features of spikes represented by principle components (PCs) of the detected and aligned
spikes. The assessments of the method, based on signal-to-noise ratio (SNR) representing background
noise, showed that the method performed spike sorting to a high level of accuracy.
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References
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sorting: the detection and classification of
neural action potentials. Network:
Computation in Neural Systems, R53-R78.
Rey, H., Ison, M., Pedreira, C., Antonio Valentin, A.,
Gonzalo, Selway, R., Quiroga, Q. R. (2015).
Single-cell recordings in the human medial
temporal lobe. Journal of Anatomy.
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Studies of Firing Patterns in Several Neurons.
Science, 1325-1327.
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The contributions of position, direction, and
velocity to single unit activity in the
hippocampus of freely-moving rats.
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Issue 1, pp 41–49.
Gray CM., Maldonado PW., Wilson M., and
McNaughton B. (1995). Tetrodes markedly
improve the reliability and yield of multiple
single-unit isolation from multi-unit
recordings in cat striate cortex. J Neurosci
Methods.; 63(1-2):43-54.
Thomas Jr. CA., Springer P., Loeb GE., Berwald-
Netter Y., and Okun LM. (1972). A miniature
microelectrode array to monitor the bioelectric
activity of cultured cells. Exp Cell
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Pedreira, C., Martinez, J., J.Ison, M., & Quiroga, R.
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current spike sorting algorithms? Journal of
Neuroscience Methods, Volume 211, Issue 1,
Pages 58-65.
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(1992). A Glass/Silicon Composite
Intracortical Electrode Array. Annals of
Biomedical Engineering, 20, 423-437.
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(2003). Robust, automatic spike sorting using
mixtures of multivariate t-distributions.
Journal of Neuroscience Methods.
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of spike sorting in the era of big data. Current
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90-96.
Franke, F., Pröpper, R., Alle, H., Meier, P., Geiger, J.,
Obermayer, K., & Munk, M. (2015). Spike
sorting of synchronous spikes from local
neuron ensembles. Journal of Neuroscience
Methods, 114(4):2535-49.
Trautmann, E., Sergey, D., Subhaneil, L., Ames, K.,
T.Kaufman, M., J.O’Shea, D., . . . V.Shenoy,
K. (2019). Accurate Estimation of Neural
Population Dynamics without Spike Sorting.
Neuron, Volume 103, Issue 2, Pages 292-308.
Harris, K., Henze, D., Csicsvari, J., Hirase, H., &
Buzsáki, G. (2000). Accuracy of tetrode spike
separation as determined by simultaneous
intracellular and extracellular measurements.
Journal Of Neurophysiology, 84(1):401-14.
Gao, Solages, C., & Lena, C. (2012). Tetrode
recordings in the cerebellar cortex. Journal of
Physiology-Paris, 106(3-4):128-36.
Caro-Martín, C. R., Delgado-García, J. M., Gruart,
A., & Sánchez-Campusano, R. (2018). Spike
sorting based on shape, phase, and distribution
features, and K-TOPS clustering with validity
and error indices. Scientific Reports.
Berdondinia, L., Wala, P. v., Guenata, O., Rooija, N.
d., & Koudelka-Hepa, M. (2005). High-
density electrode array for imaging in vitro electrophysiological activity. Biosensors and
Bioelectronics, 167-174.
Fiscella, M., Farrow, K., Jones, I. L., Jäckel, D.,
Müller, J., Frey, U., . . . Hierlemann, A.
(2012). Recording from defined populations of
retinal ganglion cells using a high-density
CMOS-integrated microelectrode array with
real-time switchable electrode selection.
Journal of Neuroscience Methods, 103-113.
[18] Müller, J., Ballini, M., Livi, P., Chen, Y.,
Radivojevic, M., Shadmani, A., . . .
Hierlemann, A. (2015). High-resolution
CMOS MEA platform to study neurons at
subcellular, cellular, and network levels. Lab
on a Chip, 15(13):2767-80.
Hilgen, G., M, S., S, P., JO, M., IE, K., S, U., . . .
MH, H. (2017). Unsupervised Spike Sorting
for Large-Scale, High-Density Multielectrode
Arrays. Cell Reports, 2521–2532.
Pouzat, C., Mazor, O., & Laurent, G. (2002). Using
noise signature to optimize spike-sorting and
to assess neuronal classification quality.
Journal of Neuroscience Methods, 122(1):43-
57.
Donoho, D. L. (1995). De-noising by soft-
thresholding. IEEE Transactions on
Information Theory, 613 - 627.
Quiroga, R. Q., Nadasdy, Z., & Ben-Shaul, Y. (2004).
Unsupervised Spike Detection and Sorting
with Wavelets and Superparamagnetic
Clustering. Neural Computation, 1661-1687.
Nenadic, Z., & Burdick, J. (2005). Spike detection
using the continuous wavelet transform. IEEE
Trans Biomed Eng., 74-87.
Quiroga, R. Q., Reddy, L., Koch, C., & Fried, I.
(2007). Decoding visual inputs from multiple
neurons in the human temporal lobe. Journal
of Neurophysiology, 1997-2007.
Drongelen, W. v. (2018). Signal Processing for
Neuroscientists . In W. v. Drongelen, Signal
Processing for Neuroscientists (pp. 126-131).
London: Academic Press.
Yang, Y., Boling, C. S., Kamboh, A. M., & Mason,
A. J. (2015). Adaptive Threshold Neural Spike
Detector Using Stationary Wavelet Transform
in CMOS. IEEE Transactions on Neural
Systems and Rehabilitation Engineering, 946 -
955
sorting: the detection and classification of
neural action potentials. Network:
Computation in Neural Systems, R53-R78.
Rey, H., Ison, M., Pedreira, C., Antonio Valentin, A.,
Gonzalo, Selway, R., Quiroga, Q. R. (2015).
Single-cell recordings in the human medial
temporal lobe. Journal of Anatomy.
Gerstein, G. L., & Clark, W. A. (1964). Simultaneous
Studies of Firing Patterns in Several Neurons.
Science, 1325-1327.
McNaughton, B., Barnes, C., & O'Keefe, J. (1983).
The contributions of position, direction, and
velocity to single unit activity in the
hippocampus of freely-moving rats.
Experimental Brain Research, Volume 52,
Issue 1, pp 41–49.
Gray CM., Maldonado PW., Wilson M., and
McNaughton B. (1995). Tetrodes markedly
improve the reliability and yield of multiple
single-unit isolation from multi-unit
recordings in cat striate cortex. J Neurosci
Methods.; 63(1-2):43-54.
Thomas Jr. CA., Springer P., Loeb GE., Berwald-
Netter Y., and Okun LM. (1972). A miniature
microelectrode array to monitor the bioelectric
activity of cultured cells. Exp Cell
Res.;74(1):61-6.
Pedreira, C., Martinez, J., J.Ison, M., & Quiroga, R.
Q. (2012). How many neurons can we see with
current spike sorting algorithms? Journal of
Neuroscience Methods, Volume 211, Issue 1,
Pages 58-65.
Jones, K. E., Campbell, P. K., & Normann, R. A.
(1992). A Glass/Silicon Composite
Intracortical Electrode Array. Annals of
Biomedical Engineering, 20, 423-437.
Shoham, S., Fellows, M. R., & Normann, R. A.
(2003). Robust, automatic spike sorting using
mixtures of multivariate t-distributions.
Journal of Neuroscience Methods.
Carlson, D., & Carin, L. (2019). Continuing progress
of spike sorting in the era of big data. Current
Opinion in Neurobiology, Volume 55, Pages
90-96.
Franke, F., Pröpper, R., Alle, H., Meier, P., Geiger, J.,
Obermayer, K., & Munk, M. (2015). Spike
sorting of synchronous spikes from local
neuron ensembles. Journal of Neuroscience
Methods, 114(4):2535-49.
Trautmann, E., Sergey, D., Subhaneil, L., Ames, K.,
T.Kaufman, M., J.O’Shea, D., . . . V.Shenoy,
K. (2019). Accurate Estimation of Neural
Population Dynamics without Spike Sorting.
Neuron, Volume 103, Issue 2, Pages 292-308.
Harris, K., Henze, D., Csicsvari, J., Hirase, H., &
Buzsáki, G. (2000). Accuracy of tetrode spike
separation as determined by simultaneous
intracellular and extracellular measurements.
Journal Of Neurophysiology, 84(1):401-14.
Gao, Solages, C., & Lena, C. (2012). Tetrode
recordings in the cerebellar cortex. Journal of
Physiology-Paris, 106(3-4):128-36.
Caro-Martín, C. R., Delgado-García, J. M., Gruart,
A., & Sánchez-Campusano, R. (2018). Spike
sorting based on shape, phase, and distribution
features, and K-TOPS clustering with validity
and error indices. Scientific Reports.
Berdondinia, L., Wala, P. v., Guenata, O., Rooija, N.
d., & Koudelka-Hepa, M. (2005). High-
density electrode array for imaging in vitro electrophysiological activity. Biosensors and
Bioelectronics, 167-174.
Fiscella, M., Farrow, K., Jones, I. L., Jäckel, D.,
Müller, J., Frey, U., . . . Hierlemann, A.
(2012). Recording from defined populations of
retinal ganglion cells using a high-density
CMOS-integrated microelectrode array with
real-time switchable electrode selection.
Journal of Neuroscience Methods, 103-113.
[18] Müller, J., Ballini, M., Livi, P., Chen, Y.,
Radivojevic, M., Shadmani, A., . . .
Hierlemann, A. (2015). High-resolution
CMOS MEA platform to study neurons at
subcellular, cellular, and network levels. Lab
on a Chip, 15(13):2767-80.
Hilgen, G., M, S., S, P., JO, M., IE, K., S, U., . . .
MH, H. (2017). Unsupervised Spike Sorting
for Large-Scale, High-Density Multielectrode
Arrays. Cell Reports, 2521–2532.
Pouzat, C., Mazor, O., & Laurent, G. (2002). Using
noise signature to optimize spike-sorting and
to assess neuronal classification quality.
Journal of Neuroscience Methods, 122(1):43-
57.
Donoho, D. L. (1995). De-noising by soft-
thresholding. IEEE Transactions on
Information Theory, 613 - 627.
Quiroga, R. Q., Nadasdy, Z., & Ben-Shaul, Y. (2004).
Unsupervised Spike Detection and Sorting
with Wavelets and Superparamagnetic
Clustering. Neural Computation, 1661-1687.
Nenadic, Z., & Burdick, J. (2005). Spike detection
using the continuous wavelet transform. IEEE
Trans Biomed Eng., 74-87.
Quiroga, R. Q., Reddy, L., Koch, C., & Fried, I.
(2007). Decoding visual inputs from multiple
neurons in the human temporal lobe. Journal
of Neurophysiology, 1997-2007.
Drongelen, W. v. (2018). Signal Processing for
Neuroscientists . In W. v. Drongelen, Signal
Processing for Neuroscientists (pp. 126-131).
London: Academic Press.
Yang, Y., Boling, C. S., Kamboh, A. M., & Mason,
A. J. (2015). Adaptive Threshold Neural Spike
Detector Using Stationary Wavelet Transform
in CMOS. IEEE Transactions on Neural
Systems and Rehabilitation Engineering, 946 -
955
Published
2020-12-13
How to Cite
BERJIS, Z. H., & AL-SULAIFANIE, A. K. (2020). NEURAL SPIKE SORTING AND CLASSIFICATION. Journal of Duhok University, 23(2), 166-178. https://doi.org/10.26682/sjuod.2020.23.2.18
Section
Pure and Engineering Sciences
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