A convolutional neural network for estimating synaptic connectivity from spike trains
Abstract The recent increase in reliable, simultaneous high channel count extracellular recordings is exciting for physiologists and theoreticians because it offers the possibility of reconstructing the underlying neuronal circuits. We recently presented a method of inferring this circuit connectivi...
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Autores principales: | Daisuke Endo, Ryota Kobayashi, Ramon Bartolo, Bruno B. Averbeck, Yasuko Sugase-Miyamoto, Kazuko Hayashi, Kenji Kawano, Barry J. Richmond, Shigeru Shinomoto |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/ff1bac4996b740f18282822bf171d347 |
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