Plasticity Neural Network Based on Astrocytic effects at Critical Period, Synaptic Competition and Rebalance by Current and Mnemonic Brain Plasticity and Synapse Formation

PNN to explore the Mechanism of the Brain-Besides weights of synaptic connections, Forward propagation and Back propagation also include weights of synaptic ranges [15,16,19-21]. PNN considers synaptic balance in dynamic of phagocytosing of synapses and static of constant sum of synapses length [15]. Synapse formation will inhibit dendrites generation to a certain extent in experiments, by simulations synapse formation will inhibit the function of dendrites [16]. Closing the critical period will cause neurological disorder in experiments, but worse results in PNN simulations [19]. The memory persistence gradient information of backward circuit similar to the Enforcing Resilience in a Spring Boot. The relatively good and inferior gradient information in synapse formation of backward circuit like the folds of the brain. Considering both negative and positive memories persistence help activate synapse length changes with iterations better than only considering positive memory. So using memory of fear learning because of improving of synaptic activity and observed obviously [20]. Memory persistence factor also inhibit local synaptic accumulation. And refers PNN can also introduce the relatively good and the relatively inferior solution to update the velocity of particle-4 parameters. Astrocytic phagocytosis will avoid the local accumulation of synapses by simulation (Lack of astrocytic phagocytosis causes excitatory synapses and functionally impaired synapses accumulate in experiments and lead to destruction of cognition, but local longer synapses and worse results in PNN simulations) [21]. The simple PNN in which only the synaptic phagocytosis effect is considered regardless of the gradient update. Therefore, is it possible to reduce the number of animal experiments and their suffering by simulating and planning the factors of biological experiments through Deep Learning?