dependent plasticity
Recently Published Documents


TOTAL DOCUMENTS

1487
(FIVE YEARS 249)

H-INDEX

93
(FIVE YEARS 11)

Author(s):  
Hao Huang ◽  
Lu Liu ◽  
chengpeng jiang ◽  
Jiangdong Gong ◽  
Yao Ni ◽  
...  

Abstract This paper reports the fabrication of an artificial synapse (AS) based on two-dimensional molybdenum disulfide (MoS2) film. The AS emulates important synaptic functions such as paired-pulse facilitation, spike-rate dependent plasticity, spike-duration dependent plasticity and spike-number dependent plasticity. The spike voltage can mediate ion migration in the ion gel to regulate the MoS2 conductive channel, thereby realizing the emulation of synaptic plasticity. More importantly, benefiting from the atomically-flat surface of MoS2 film, the device has a high sensitivity to external stimuli. It can effectively respond to presynaptic spikes that have an amplitude of 100 mV. The development of this device provides a new idea for constructing a highly-sensitive and multifunctional neuromorphic system.


2021 ◽  
pp. 1-22
Author(s):  
Eric C. Wong

The brain is thought to represent information in the form of activity in distributed groups of neurons known as attractors. We show here that in a randomly connected network of simulated spiking neurons, periodic stimulation of neurons with distributed phase offsets, along with standard spike-timing-dependent plasticity (STDP), efficiently creates distributed attractors. These attractors may have a consistent ordered firing pattern or become irregular, depending on the conditions. We also show that when two such attractors are stimulated in sequence, the same STDP mechanism can create a directed association between them, forming the basis of an associative network. We find that for an STDP time constant of 20 ms, the dependence of the efficiency of attractor creation on the driving frequency has a broad peak centered around 8 Hz. Upon restimulation, the attractors self-oscillate, but with an oscillation frequency that is higher than the driving frequency, ranging from 10 to 100 Hz.


2021 ◽  
Author(s):  
Danying Wang ◽  
George Michael Parish ◽  
Kimron L Shapiro ◽  
Simon Hanslmayr

Rodent studies suggest that spike timing relative to hippocampal theta activity determines whether potentiation or depression of synapses arise. Such changes also depend on spike timing between pre- and post-synaptic neurons, known as spike-timing-dependent plasticity (STDP). STDP, together with theta-phase-dependent learning, has inspired several computational models of learning and memory. However, evidence to elucidate how these mechanisms directly link to human episodic memory is lacking. In a computational model, we modulate long-term potentiation (LTP) and long-term depression (LTD) of STDP, by opposing phases of a simulated theta rhythm. We fit parameters to a hippocampal cell culture study in which LTP and LTD were observed to occur in opposing phases of a theta rhythm. Further, we modulated two inputs by cosine waves with synchronous and asynchronous phase offsets and replicate key findings in human episodic memory. Learning advantage was found for the synchronous condition, as compared to the asynchronous conditions, and was specific to theta modulated inputs. Importantly, simulations with and without each mechanism suggest that both STDP and theta-phase-dependent plasticity are necessary to replicate the findings. Together, the results indicate a role for circuit-level mechanisms, which bridges the gap between slice preparation studies and human memory.


Laser Physics ◽  
2021 ◽  
Vol 32 (1) ◽  
pp. 016201
Author(s):  
Tao Tian ◽  
Zhengmao Wu ◽  
Xiaodong Lin ◽  
Xi Tang ◽  
Ziye Gao ◽  
...  

Abstract Based on the well-known Fabry–Pérot approach, after taking into account the variation of bias current of the vertical-cavity semiconductor optical amplifier (VCSOA) according to the present synapse weight, we implement the optical spike timing dependent plasticity (STDP) with weight-dependent learning window in a VCSOA with double optical spike injections, and numerically investigate the corresponding weight-dependent STDP characteristics. The simulation results show that, the bias current of VCSOA has significant effect on the optical STDP curve. After introducing an adaptive variation of the bias current according to the present synapse weight, the optical weight-dependent STDP based on VCSOA can be realized. Moreover, the weight training based on the optical weight-dependent STDP can be effectively controlled by adjusting some typical external or intrinsic parameters and the excessive adjusting of synaptic weight is avoided, which can be used to balance the stability and competition among synapses and pave a way for the future large-scale energy efficient optical spiking neural networks based on the weight-dependent STDP learning mechanism.


Sign in / Sign up

Export Citation Format

Share Document