| First Author | Ma X | Year | 2024 |
| Journal | Cell Rep Methods | Volume | 4 |
| Issue | 6 | Pages | 100791 |
| PubMed ID | 38848714 | Mgi Jnum | J:359254 |
| Mgi Id | MGI:7785641 | Doi | 10.1016/j.crmeth.2024.100791 |
| Citation | Ma X, et al. (2024) ElecFeX is a user-friendly toolbox for efficient feature extraction from single-cell electrophysiological recordings. Cell Rep Methods 4(6):100791 |
| abstractText | Characterizing neurons by their electrophysiological phenotypes is essential for understanding the neural basis of behavioral and cognitive functions. Technological developments have enabled the collection of hundreds of neural recordings; this calls for new tools capable of performing feature extraction efficiently. To address the urgent need for a powerful and accessible tool, we developed ElecFeX, an open-source MATLAB-based toolbox that (1) has an intuitive graphical user interface, (2) provides customizable measurements for a wide range of electrophysiological features, (3) processes large-size datasets effortlessly via batch analysis, and (4) yields formatted output for further analysis. We implemented ElecFeX on a diverse set of neural recordings; demonstrated its functionality, versatility, and efficiency in capturing electrical features; and established its significance in distinguishing neuronal subgroups across brain regions and species. ElecFeX is thus presented as a user-friendly toolbox to benefit the neuroscience community by minimizing the time required for extracting features from their electrophysiological datasets. |
