Name
Abstract | ||
|---|---|---|
Inferring directional couplings from the spike data of networks is desired in various scientific fields such as neuroscience. Here, we apply a recently proposed objective procedure to the spike data obtained from the Hodgkin-Huxley type models and in vitro neuronal networks cultured in a circular structure. As a result, we succeed in reconstructing synaptic connections accurately from the evoked activity as well as the spontaneous one. To obtain the results, we invent an analytic formula approximately implementing a method of screening relevant couplings. This significantly reduces the computational cost of the screening method employed in the proposed objective procedure, making it possible to treat large-size systems as in this study. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1088/1742-5468/ab3219 | ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018) |
Keywords | Field | DocType |
computational cost,scientific fields,neuronal networks,evoked activity,analytic formula | Coupling,Inference,Artificial intelligence,Machine learning,Evoked activity,Mathematics | Conference |
Volume | Issue | ISSN |
31 | 12 | 1049-5258 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu Terada | 1 | 0 | 1.01 |
| Tomoyuki Obuchi | 2 | 11 | 5.65 |
| Takuya Isomura | 3 | 0 | 3.04 |
| Yoshiyuki Kabashima | 4 | 136 | 27.83 |