Human vision works this way. To fix the latency problem (actual event hff happening vs signal transmitted to your brain) human vision is constantly predicting what you should see, your brain tells you that is what you saw (the prediction), and then the brain does reconciliation after the fact. Your brain will scramble for coherency when prediction and reality do not match. This trickery is why it seems like you see events in real time, when there is actually a significant delay between event and perception.
Though, there are error correction mechanisms, systems for validation, and a coherent underlying model of the world that is used by tthee brain.
FWIW, it is likely the most used set of neuron connections, sets of millions in play and their interconnections being the important part. That subset being one of billions of others with thousands of connections between each neuron - keep in mind it is not the set of neurons firing that matters, but the set of connections firing. The set of connections is a vastly large number.
Like, if you have three neurons, your brain can encode 10 data points. Let's call these A, B,C. A firing and terminating is one (so three for each), each edge, eg A to B is another three, each set of two edges, eg A to B to C (three more), and all three edges for one more. Then keep in mind you have billions of neurons and they are each interconnected by the thousands.
