Unsupervised Spike Detection and Sorting with Wavelets and Superparamagnetic Clustering

By R. Quian Quiroga, Zoltan Nadasdy, Yoram Ben-Shaul. Neural Computation, 2004

2,226 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Signal Processing

View Paper: https://www.semanticscholar.org/paper/798548b6995f327440100e0d7382ff2652c17c6f

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Citations in the corpus

Past, present and future of spike sorting techniques (2015, methodology): “Source : Adapted from (Quian Quiroga, 2012a of the noise, i.e., threshold ˆ n , where k is a constant typically between 3 and thresholding, e.g., applying an energy operator (Bestel et al., 2012; Rutishauser et al., 2006), the continuous wavelet transform (Nenadic and Burdick, 2005), or using fuzzy ”
Temporal cortex neurons encode articulated actions as slow sequences of integrated poses (2010, methodology): “The signals were thresholded and (when more than one unit was recorded at once) sorted using “wave_clus” (Quiroga et al., 2004).”
Progress Towards Biocompatible Intracortical Microelectrodes for Neural Interfacing Applications (2014, methodology): “To estimate noise amplitude during bursts, in order to eliminate the effect of the presence of spikes [44], a median value was used (see section 2, subsection 2.”
Quality Metrics to Accompany Spike Sorting of Extracellular Signals (2011, background): “…into groups that are based on similarity of their shape and possible other factors, such as the state of the animal and the statistics of neuronal spiking (Abeles and Goldstein, 1977; Lewicki, 1994; Fee et al., 1996b; Nguyen et al., 2003; Quiroga et al., 2004; Delescluse and Pouzat, 2006).”
Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition (2014, methodology): “We sorted single-units from the multi-unit IT and V4 data by using affinity propagation [63] together with the method described in [64].”
Revealing neuronal function through microelectrode array recordings (2015, positive): “In the presence of many spikes, the threshold can be estimated using a measure based on the median, which is less sensitive to outliers and therefore more robust with regard to spike frequency (Quian Quiroga et al., 2004).”
Explicit encoding of multimodal percepts by single neurons in the human brain. (2009, positive): “From the continuous wide-band data, spike detection and sorting was carried out with Wave_Clus, an adaptive and stochastic algorithm [ 39 ] (see Supplemental Data).”
Automated long-term recording and analysis of neural activity in behaving animals (2016, methodology): “Spike clustering is then performed on blocks of 1000 consecutive spike ‘snippets’ by means of an automated superparamagnetic clustering routine, a step we call ‘local clustering’ (Blatt et al., 1996; Quiroga et al., 2004) (Supplemental Experimental Procedures, Figure 1C and S2).”
Broadband shifts in LFP power spectra are correlated with single-neuron spiking in humans (2009, methodology): “Using the WaveClus software package (Quiroga et al., 2004), we identified the action potentials of 0 –3 neurons per microwire, for a total of 2030 neurons across 20 subjects.”