Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Hebbian plasticity requires compensatory processes on multiple timescales
We review a body of theoretical and experimental research on Hebbian and homeostatic
plasticity, starting from a puzzling observation: while homeostasis of synapses found in …
plasticity, starting from a puzzling observation: while homeostasis of synapses found in …
A triplet spike-timing–dependent plasticity model generalizes the Bienenstock–Cooper–Munro rule to higher-order spatiotemporal correlations
Synaptic strength depresses for low and potentiates for high activation of the postsynaptic
neuron. This feature is a key property of the Bienenstock–Cooper–Munro (BCM) synaptic …
neuron. This feature is a key property of the Bienenstock–Cooper–Munro (BCM) synaptic …
Synaptic plasticity in neural networks needs homeostasis with a fast rate detector
Hebbian changes of excitatory synapses are driven by and further enhance correlations
between pre-and postsynaptic activities. Hence, Hebbian plasticity forms a positive feedback …
between pre-and postsynaptic activities. Hence, Hebbian plasticity forms a positive feedback …
Bidirectional coupling between astrocytes and neurons mediates learning and dynamic coordination in the brain: a multiple modeling approach
In recent years research suggests that astrocyte networks, in addition to nutrient and waste
processing functions, regulate both structural and synaptic plasticity. To understand the …
processing functions, regulate both structural and synaptic plasticity. To understand the …
Computational modeling of neural plasticity for self-organization of neural networks
J Chrol-Cannon, Y ** - Biosystems, 2014 - Elsevier
Self-organization in biological nervous systems during the lifetime is known to largely occur
through a process of plasticity that is dependent upon the spike-timing activity in connected …
through a process of plasticity that is dependent upon the spike-timing activity in connected …
Stability versus neuronal specialization for STDP: long-tail weight distributions solve the dilemma
M Gilson, T Fukai - PloS one, 2011 - journals.plos.org
Spike-timing-dependent plasticity (STDP) modifies the weight (or strength) of synaptic
connections between neurons and is considered to be crucial for generating network …
connections between neurons and is considered to be crucial for generating network …
Non-linear memristive synaptic dynamics for efficient unsupervised learning in spiking neural networks
Spiking neural networks (SNNs) are a computational tool in which the information is coded
into spikes, as in some parts of the brain, differently from conventional neural networks …
into spikes, as in some parts of the brain, differently from conventional neural networks …
When long-range zero-lag synchronization is feasible in cortical networks
A Viriyopase, I Bojak, M Zeitler… - Frontiers in computational …, 2012 - frontiersin.org
Many studies have reported long-range synchronization of neuronal activity between brain
areas, in particular in the beta and gamma bands with frequencies in the range of 14–30 …
areas, in particular in the beta and gamma bands with frequencies in the range of 14–30 …
Limits to the development of feed-forward structures in large recurrent neuronal networks
Spike-timing dependent plasticity (STDP) has traditionally been of great interest to
theoreticians, as it seems to provide an answer to the question of how the brain can develop …
theoreticians, as it seems to provide an answer to the question of how the brain can develop …
Changing the responses of cortical neurons from sub-to suprathreshold using single spikes in vivo
Action Potential (APs) patterns of sensory cortex neurons encode a variety of stimulus
features, but how can a neuron change the feature to which it responds? Here, we show that …
features, but how can a neuron change the feature to which it responds? Here, we show that …