کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1891325 1533640 2016 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
How single node dynamics enhances synchronization in neural networks with electrical coupling
ترجمه فارسی عنوان
چگونه دینامیک گره تک تقویت همزمان در شبکه های عصبی با اتصال الکتریکی
کلمات کلیدی
هماهنگ سازی، عملکرد ثبات استاد پایداری گراف اتصال شبکه عصبی
موضوعات مرتبط
مهندسی و علوم پایه فیزیک و نجوم فیزیک آماری و غیرخطی
چکیده انگلیسی

The stability of the completely synchronous state in neural networks with electrical coupling is analytically investigated applying both the Master Stability Function approach (MSF), developed by Pecora and Carroll (1998), and the Connection Graph Stability method (CGS) proposed by Belykh et al. (2004). The local dynamics is described by Morris–Lecar model for spiking neurons and by Hindmarsh–Rose model in spike, burst, irregular spike and irregular burst regimes. The combined application of both CGS and MSF methods provides an efficient estimate of the synchronization thresholds, namely bounds for the coupling strength ranges in which the synchronous state is stable. In all the considered cases, we observe that high values of coupling strength tend to synchronize the system. Furthermore, we observe a correlation between the single node attractor and the local stability properties given by MSF. The analytical results are compared with numerical simulations on a sample network, with excellent agreement.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chaos, Solitons & Fractals - Volume 85, April 2016, Pages 32–43
نویسندگان
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