2016年7月
Input Response of Neural Network Model with Lognormally Distributed Synaptic Weights
JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN
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- 巻
- 85
- 号
- 7
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.7566/JPSJ.85.074001
- 出版者・発行元
- PHYSICAL SOC JAPAN
Neural assemblies in the cortical microcircuit can sustain irregular spiking activity without external inputs. On the other hand, neurons exhibit rich evoked activities driven by sensory stimulus, and both activities are reported to contribute to cognitive functions. We studied the external input response of the neural network model with lognormally distributed synaptic weights. We show that the model can achieve irregular spontaneous activity and population oscillation depending on the presence of external input. The firing rate distribution was maintained for the external input, and the order of firing rates in evoked activity reflected that in spontaneous activity. Moreover, there were bistable regions in the inhibitory input parameter space. The bimodal membrane potential distribution, which is a characteristic feature of the up-down state, was obtained under such conditions. From these results, we can conclude that the model displays various evoked activities due to the external input and is biologically plausible.
- リンク情報
- ID情報
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- DOI : 10.7566/JPSJ.85.074001
- ISSN : 0031-9015
- Web of Science ID : WOS:000378729500015