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Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Сортировка спайков× | Локализация источников в МЭГ× | |
|---|---|---|
| Область | Нейровизуализация | Нейровизуализация |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2000 | 1972 |
| Автор метода≠ | Kenneth Harris | David Cohen |
| Тип≠ | Neuronal activity classification pipeline | MEG neuroimaging analysis pipeline |
| Основополагающий источник≠ | 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 ↗ | Hauk, O., Friston, K. J., & Leff, A. (2019). Functional neuroimaging of language: understanding the complex relationships between localization and function. Journal of Neurolinguistics, 50, 236–250. link ↗ |
| Другие названия | unit isolation, single-unit recording, electrophysiology clustering | MEG localization, magnetic source imaging, MSI |
| Связанные | 3 | 3 |
| Сводка≠ | 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. | Magnetoencephalography (MEG) source localization is the inverse problem of estimating where in the brain neural currents originate from magnetic field measurements at the scalp. Introduced by David Cohen in 1972, MEG offers superior temporal resolution (milliseconds) and spatial specificity compared to EEG, as magnetic fields are less distorted by tissue conductivity, enabling researchers to pinpoint neural activity with high precision. |
| ScholarGateНабор данных ↗ |
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