Izhikevichモデルを用いた培養神経回路網の結合強度推定

抄録

Recently, a lot of research using multi-neuron recording has been done, however, there are many problems with extracting the features from obtained spike time series which is huge amount and complex. Here we introduce a new method to estimate synaptic connection strengths between neurons by fitting for Izhikevich model using maximum likelihood estimation. We demonstrate that our method is able to estimate connection strengths from spike time series given by simulated neural ensemble and able to estimate non-connectivity between two independent cultured neuronal networks. These results suggest that our method can apply for network and plasticity analysis of neuronal networks.