Related Experiment Video
Updated: Jun 24, 2026

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'
Published on: February 10, 2017
Spike sorting by a minimax reduced feature set based on finite differences
Chien-Chang Yen1, Wei-Chang Shann, Chen-Tung Yen
1Department of Mathematics, Fu-Jen Catholic University, Taipei, Taiwan.
Abstract:
Spikes are classified according to their finite differences in various orders. The fundamental idea that makes it work is that finite differences can extract and isolate features from spikes. This method showed better sorting quality and involved less labor than the methods of principal component analysis, original reduced feature set, and wavelet-based spike classifiers.
Related Concept Videos
Downsampling
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
Maximizing the Directional Derivative
Sieve Analysis and Grading Curves
Quantifying and Rejecting Outliers: The Grubbs Test
Routh-Hurwitz Criterion II
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first column of the Routh...
Modified Boxplots
However, the box plot does not tell the reader about outliers - values that lie far from the center of the data. We can modify the standard box and whisker plot to identify the outliers and visualize the actual spread of the data in a sample.
Initially, we calculate the adjusted...

