We study the combination of learning control and adaptive pinning control leading to the asymptotic synchronization adaptive system in the presence of unknown time-varying parameters.
More spike-LFP theta synchronization is correlated with higher learning performance, while high-frequency synchronization is unrelated with changes in performance, but these changes were absent once learning had stabilized and stimuli became familiar, or in the absence of learning.
The spike-LFP synchronization associated with learning occurred in the theta band, while higher frequency synchronization was uncorrelated with changes in behavioral performance.
The changes to the level of synchronization were abolished once learning had stabilized and stimuli had become familiar.
As Fig. 2 shows, after self-learning, the synchronization of the sender and its receiver is completed, so when sender A transmits data, one of its candidate receiver is also in the awake state, and then, the delay is reduced.
These findings indicate that plasticity in visual cortex during the time course of learning is accompanied by elevated low-frequency synchronization between individual neuron responses and local population activity.
Based on the learning control techniques in references [36 40], we study the pinning synchronization of linearly coupled delayed RDNNs with general coupling matrices.
The three main learning rules that aid into the synchronization of weights in the adaptation step are Hebbian, anti-Hebbian, and Random Walk.
It will be interesting to assess whether or not declarative learning exerts some effect on such synchronization of hippocampal SEEG activity.
In this paper, using adaptive learning method on periodic coupling strengths, the synchronization of stochastic delayed RDNNs will be considered.
Singers learn to produce well-controlled tone onsets by accurate synchronization of glottal adduction and buildup of subglottal pressure.
