Brain consist of neural network. How can a baby say "Cat" when baby look at cat? How network learn about family, animals, daily tasks & nature. How brain differentiate sounds and music?
When a baby look at cat, how baby spoke cat at same time?
Ali Parents say cat, when they see cat in front of them. This event occur as a trigger in ali mind and activate some pattern in his mind. Visual and sound pattern in different networks, at the same time. When a network receive same event as a trigger, over and over it'll strength the network weight. That's cause , when ali see a cat at the door and he shout "cat".
This solve data traversal or information processing problem in network. Network store some event information. Information distribute over the network. Each object represent some pattern in our mind fig -2. Let's say I'm wake up early in the morning but yesterday I had woke up late morning, again neural network produce some pattern, which will be store in memory called episodic memory.
Let's say
Initially: [0,0,0,0]
Object : cat
output: o[0.1,0.2, 0,-1]
o[0.1 > 0.05 ] = [0.1] // associate
o[0.2 > 0.05] = [0.2]
o[0 > 0.05] = [0] // inhibit
o[-1 > 0.05] = [0]
Pattern follow associate and inhibit. Associate (+) , Inhibit (-). This pattern 10 billion long bits.
When a brain stroke or something happen , in most cases, suffer forget most of the information due to accident. Neural network remove various links, during the event but after sometime neurons regenerate neurons. According to connectist theory everything , you see, remember, taste, smell or touch is just a pattern of neurons or array of signals. If this is the case then, why our deep model, is intelligent like us? How bits understand cognition problem? Is artificial cognition solve through this proposed theory?
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