English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In addition to the shared weights of the synaptic connections, our new neuralnetwork includes the synaptic effective range weights for both the forward andback propagation. We try to simulate the functions of prefrontal lobe,amygdala, and hippocampus by the Deep learning model of upstream and downstreambrain regions(DLMOUADBR). Along the forward propagation, the negative memorygradually increases. Along the back propagation, the optimization order willincrease. Memory flow may be considered to be the transmission of the rate ofchange of the architecture, then the nth cortex is the nth derivative of brainplasticity. Astrocytic cortex memory persistence factor and astrocytesphagocytose synapses inhibit local synaptic accumulation, and the modelinspires experiments. The memory Generation-Consolidation-Loss model tries toexplain 15 phenomena of Alzheimer's disease based on the DLMOUADBR and reverseturbulence. We consider the Heart-Brain model to reference to non-classicalquantum entanglement experiments. And turbulent movement of brain regionsthrough mnemonic spiral. The study first showed that mnemonic architectureformula-logarithmic spiral, turbulent movement in brain regions is only energyloss and memory engrams are approximate. This explains the dynamics cause ofshaping in the geometry of the brain, related to the turbulent movement of thelogarithmic spiral of the brain. In simulation, it is possible that thickercortices and more diverse individuals within the brain could have high IQ, butthickest cortices and most diverse individuals may have low IQ in simulationand tries to give the mechanism of Cognitive impairment.

The Deep learning model of upstream and downstream brain regions Based  on Memory Generation-Consolidation-Loss, Synaptic Strength Rebalance and  mnemonic spiral