تقرير
FNS: an event-driven spiking neural network simulator based on the LIFL neuron model
العنوان: | FNS: an event-driven spiking neural network simulator based on the LIFL neuron model |
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المؤلفون: | Susi, Gianluca, Garces, Pilar, Cristini, Alessandro, Paracone, Emanuele, Salerno, Mario, Maestu, Fernando, Pereda, Ernesto |
سنة النشر: | 2018 |
المجموعة: | Quantitative Biology |
مصطلحات موضوعية: | Quantitative Biology - Neurons and Cognition |
الوصف: | Limitations in processing capabilities and memory of today's computers make spiking neuron-based (human) whole-brain simulations inevitably characterized by a compromise between bio-plausibility and computational cost. It translates into brain models composed of a reduced number of neurons and a simplified neuron's mathematical model, leading to the search for new simulation strategies. Taking advantage of the sparse character of brain-like computation, the event-driven technique could represent a way to carry out efficient simulation of large-scale Spiking Neural Networks (SNN). The recent Leaky Integrate-and-Fire with Latency (LIFL) spiking neuron model is event-driven compatible and exhibits some realistic neuronal features, opening new avenues for brain modelling. In this paper we introduce FNS, the first LIFL-based spiking neural network framework, which combines spiking/synaptic neural modelling with the event-driven approach, allowing us to define heterogeneous neuron modules and multi-scale connectivity with delayed connections and plastic synapses. In order to allow multi-thread implementations a novel parallelization strategy is also introduced. This paper presents mathematical models, software implementation and simulation routines on which FNS is based. Finally, a brain subnetwork is modeled on the basis of real brain structural data, and the resulting simulated activity is compared with associated brain functional (source-space MEG) data, demonstrating a good matching between the activity of the model and that of the experimetal data. This work aims to lay the groundwork for future event-driven based personalised brain models. Comment: Changed title, added references, corrected typos |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/1801.00864 |
رقم الأكسشن: | edsarx.1801.00864 |
قاعدة البيانات: | arXiv |
الوصف غير متاح. |