Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Clasificación de espigas× | eLORETA× | |
|---|---|---|
| Campo | Neuroimagen | Neuroimagen |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 2000 | 2002 |
| Autor original≠ | Kenneth Harris | Roberto D. Pascual-Marqui |
| Tipo≠ | Neuronal activity classification pipeline | EEG/MEG source localization algorithm |
| Fuente seminal≠ | Harris, K. D., Csicsvari, J., Hirase, H., et al. (2016). Accuracy of tetrode spike separation as determined by simultaneous intracellular and extracellular recordings. Journal of Neurophysiology, 84(1), 401–414. link ↗ | Pascual-Marqui, R. D. (2002). Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. Methods & Findings in Experimental & Clinical Pharmacology, 24(S-D), 5–12. link ↗ |
| Alias≠ | unit isolation, single-unit recording, electrophysiology clustering | Exact LORETA, eLORETA source reconstruction |
| Relacionados≠ | 3 | 2 |
| Resumen≠ | Spike sorting is an electrophysiological technique for identifying and isolating action potentials of individual neurons from extracellular electrical recordings. Central to single-unit neurophysiology, spike sorting assigns spikes recorded on electrode arrays to their neuron of origin, enabling study of individual neuron firing patterns, timing, and network interactions with single-cell resolution. | Exact Low-Resolution Electromagnetic Tomography (eLORETA) is a non-parametric solution to the inverse problem in EEG and MEG source localization. Developed by Roberto D. Pascual-Marqui in 2002, eLORETA reconstructs three-dimensional maps of electrical brain activity from scalp electrode recordings, offering zero localization error under ideal noise-free conditions. |
| ScholarGateConjunto de datos ↗ |
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