Neuronal oscillations in the hippocampus are critical for many brain functions including learning and memory.The underlying mechanism of oscillation generation has been extensively investigated in terms of chemical sy...Neuronal oscillations in the hippocampus are critical for many brain functions including learning and memory.The underlying mechanism of oscillation generation has been extensively investigated in terms of chemical synapses and ion channels.Recently,electrical synapses have also been indicated to play important roles,as reported in various brain areas in vivo and in brain slices.However,this issue remains to be further clarified,including in hippocampal networks.Here,using the completely isolated hippocampus,we investigated in vitro the effect of electrical synapses on slow CA1 oscillations(0.5 Hz-1.5 Hz)generated intrinsically by the hippocampus.We found that these oscillations were totally abolished by bath application of a general blocker of gap junctions(carbenoxolone)or a specific blocker of electrical synapses(mefloquine),as determined by whole-cell recordings in both CA1 pyramidal cells and fast-spiking cells.Our findings indicate that electrical synapses are required for the hippocampal generation of slow CA1 oscillations.展开更多
Neuromorphic computing simulates the operation of biological brain function for information processing and can potentially solve the bottleneck of the Von Neumann architecture.Inspired by the real characteristics of p...Neuromorphic computing simulates the operation of biological brain function for information processing and can potentially solve the bottleneck of the Von Neumann architecture.Inspired by the real characteristics of physical memristive devices,we propose a threshold-type nonlinear voltage-controlled memristor mathematical model which is used to design a novel memristor-based crossbar array.The presented crossbar array can simulate the synaptic weight in real number field rather than only positive number field.Theoretical analysis and simulation results of a 2×2 image inversion operation validate the feasibility of the proposed crossbar array and the necessary training and inference functions.Finally,the presented crossbar array is used to construct the neural network and then applied in the handwritten digit recognition.The Mixed National Institute of Standards and Technology(MNIST)database is adopted to train this neural network and it achieves a satisfactory accuracy.展开更多
In this paper, we study delay-induced firing behavior and transitions in adaptive Newman-Watts networks of thermosensitive neurons with electrical or chemical synapses. It is found that electrical and chemical synapse...In this paper, we study delay-induced firing behavior and transitions in adaptive Newman-Watts networks of thermosensitive neurons with electrical or chemical synapses. It is found that electrical and chemical synapse time delay-induced firing behavior and transitions differ significantly. In the case of electrical synapses, the bursts for a fixed delay involve equal number of spikes in each burst, and for certain time delays the firing can be inhibited. However, in the case of chemical synapses the bursts for a fixed delay involve different numbers of spikes in each burst, and no firing inhibition is observed. It is also shown that larger growth rates of adaptive coupling strength or larger network randomness can enhance the synchronization of bursting in the case of electrical synapses but reduce it in the case of chemical synapses. These results show that electrical and chemical synapses have different effects on delay-induced firing behavior and dynamical evolution. Compared to electrical synapses, chemical synapses might be more beneficial to the generation of firing and abundant firing transitions in adaptive and delayed neuronal networks. These findings can help to better understand different firing behaviors in neuronal networks with electrical and chemical synapses.展开更多
基金This work was supported by grants from the National Natural Science Foundation of China(3147107,91132711,30970960)a Key Project of Shanghai Science and Technology Commission(15JC1400102,19ZR1416600).
文摘Neuronal oscillations in the hippocampus are critical for many brain functions including learning and memory.The underlying mechanism of oscillation generation has been extensively investigated in terms of chemical synapses and ion channels.Recently,electrical synapses have also been indicated to play important roles,as reported in various brain areas in vivo and in brain slices.However,this issue remains to be further clarified,including in hippocampal networks.Here,using the completely isolated hippocampus,we investigated in vitro the effect of electrical synapses on slow CA1 oscillations(0.5 Hz-1.5 Hz)generated intrinsically by the hippocampus.We found that these oscillations were totally abolished by bath application of a general blocker of gap junctions(carbenoxolone)or a specific blocker of electrical synapses(mefloquine),as determined by whole-cell recordings in both CA1 pyramidal cells and fast-spiking cells.Our findings indicate that electrical synapses are required for the hippocampal generation of slow CA1 oscillations.
基金supported by the National Natural Science Foundation of China(61801154,61771176)the Zhejiang Provincial Natural Science Foundation of China(LY20F010008).
文摘Neuromorphic computing simulates the operation of biological brain function for information processing and can potentially solve the bottleneck of the Von Neumann architecture.Inspired by the real characteristics of physical memristive devices,we propose a threshold-type nonlinear voltage-controlled memristor mathematical model which is used to design a novel memristor-based crossbar array.The presented crossbar array can simulate the synaptic weight in real number field rather than only positive number field.Theoretical analysis and simulation results of a 2×2 image inversion operation validate the feasibility of the proposed crossbar array and the necessary training and inference functions.Finally,the presented crossbar array is used to construct the neural network and then applied in the handwritten digit recognition.The Mixed National Institute of Standards and Technology(MNIST)database is adopted to train this neural network and it achieves a satisfactory accuracy.
文摘In this paper, we study delay-induced firing behavior and transitions in adaptive Newman-Watts networks of thermosensitive neurons with electrical or chemical synapses. It is found that electrical and chemical synapse time delay-induced firing behavior and transitions differ significantly. In the case of electrical synapses, the bursts for a fixed delay involve equal number of spikes in each burst, and for certain time delays the firing can be inhibited. However, in the case of chemical synapses the bursts for a fixed delay involve different numbers of spikes in each burst, and no firing inhibition is observed. It is also shown that larger growth rates of adaptive coupling strength or larger network randomness can enhance the synchronization of bursting in the case of electrical synapses but reduce it in the case of chemical synapses. These results show that electrical and chemical synapses have different effects on delay-induced firing behavior and dynamical evolution. Compared to electrical synapses, chemical synapses might be more beneficial to the generation of firing and abundant firing transitions in adaptive and delayed neuronal networks. These findings can help to better understand different firing behaviors in neuronal networks with electrical and chemical synapses.
