I know current learning models work a little like neurons but why not just make a sim that works exactly like how we understand neurons work
I know current learning models work a little like neurons but why not just make a sim that works exactly like how we understand neurons work
We’ve got some really good theories, though. Neurons make new connections and prune them over time. We know about two types of ion channels within the synapse - AMPA and NMDA. AMPA channels open within the post-synapse neuron when glutamate is released by the pre-synapse neuron. And the AMPA receptor allows sodium ions into the dell, causing it to activate.
If the post-synapse cell fires for a long enough time, i.e. recieves strong enough input from another cells/enough AMPA receptors open, the NMDA receptor opens and calcium enters the cell. Typically an ion of magnesium keeps it closed. Once opened, it triggers a series of cellular mechanisms that cause the connection between the neurons to get stronger.
This is how Donald Hebb’s theory of learning works. https://en.wikipedia.org/wiki/Hebbian_theory?wprov=sfla1
Cells that fire together, wire together.
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