Dynamical behaviors in discrete memristor-coupled small-world neuronal networks

The brain is a complex network system in which a large number of neurons are widely connected to each other and transmit signals to each other.The memory characteristic of memristors makes them suitable for simulating neuronal synapses with plasticity.In this paper,a memristor is used to simulate a synapse,a discrete small-world neuronal network is constructed based on Rulkov neurons and its dynamical behavior is explored.We explore the influence of system parameters on the dynamical behaviors of the discrete small-world network,and the system shows a variety of firing patterns such as spiking firing and triangular burst firing when the neuronal parameterαis changed.The results of a numerical simulation based on Matlab show that the network topology can affect the synchronous firing behavior of the neuronal network,and the higher the reconnection probability and number of the nearest neurons,the more significant the synchronization state of the neurons.In addition,by increasing the coupling strength of memristor synapses,synchronization performance is promoted.The results of this paper can boost research into complex neuronal networks coupled with memristor synapses and further promote the development of neuroscience.

Constructing dataset of classified drainage areas based on surface water-supply patterns in High Mountain Asia

The High Mountain Asia(HMA)region,ranging from the Hindu Kush and Tien Shan in thewest totheHimalaya inthe southwith an altitude between 2000 and 8844 m,holds the largest reservoir of glaciers and snow outside Earth Polar Regions.In the last decades,numerous glaciers and lake areas there have undergone tremendous changes with water redistribution.In order to increase understanding of the pattern of distribution of water resources,and their dynamic changes at the basin scale,a watershed classification based on the water replenishment patterns dataset was constructed.The input dataset are from the Randolph Glacier Inventory V.6.0 and the vector data of rivers and streams.Four datasets were thus obtained:Glacier-fed and Runoff-fed Drainage Area(GRDA),Glacier-fed and Runoff-free Drainage Area(GDA),Glacier-free and Runoff-fed Drainage Area(RDA),and the Glacier-free and Runoff-free Drainage Area(NGRDA),and the numbers of these four types of basins are 87,107,32,and 448 separately.The statistical results show GRDA has the largest surface area,accounting for 82.2%of the total basin area in HMA,mainly in the region of the basin with outflow rivers or streams.Dominated by small basins,the GDA area accounts for the smallest area,only 3.86%and the RDA accounts for 5.62%.For NGRDA,most are with small areas,accounting for 8.32%,and mainly distributes in the closed basin of the Qiangtang Plateau.This dataset provides a fundamental classified data source for research on water resources,climate,ecology,and environment in HMA.The published data are available at https://data.4tu.nl/download/uuid:d07d748f-d10b-4308-9626-199ef05cc9af/and http://www.dx.doi.org/10.11922/sciencedb.923.