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Evaluation Performance of Spike Sorting Algorithms
| Content Provider | Semantic Scholar |
|---|---|
| Author | Vu, Philip P. |
| Copyright Year | 2014 |
| Abstract | Many questions in Neuroscience are dependent on analyzing neuronal spike activity recorded during certain behavior tasks. In other words, neural spike activity is the electrical activity that occurs in brain cells when active. For this reason data acquired from numerous neurons are essential in elucidating the underlying principle of neural information processing. Recently, commercially available electrode arrays have been developed to detect multiunit neural activity within the brain. However, development of efficient and reliable computational methods on classifying multiunit data lags behind the capabilities of current hardware. In practice, supervised spike sorting is tedious and time-consuming. Here, I compare and contrast two common spike sorting algorithms, list their positive and negative characteristics, and evaluate how well each method can reconstruct a spike waveform with a minimal amount of coefficients. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://web.eecs.umich.edu/~girasole/teaching/451/2014fall/gradprojects/Project_Report__Final_Vu.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
