Well, I started on how to describe some of the behavior of the neurons on an individual level. Here's the current scoop.
Each neuron will have a list of variables for use in carrying out the propagation of an input signal.
where:
- is the weight of a neurotransmitter(t) of a specific neuron(n)
- is the interval that has be in for the neuron to trigger a specific function
- is the status of neuron(n) where one means it's active and zero means it's inactive
List of neurotransmitter(weights), initial intervals and functions | ||
Weight | Interval | Function taken by neuron |
t=1 | a=0, b=100 | Increases b of triggered interval |
t=2 | a=0, b=100 | Decreases b of triggered interval |
t=3 | a=0, b=100 | Increases a of triggered interval |
t=4 | a=0, b=100 | Decreases a of triggered interval |
t=5 | a=0, b=100 | Increases weight of highest interval |
t=6 | a=0, b=100 | Decreases weight of highest interval |
t=7 | a=0, b=100 | Increases weight of lowest interval |
t=8 | a=0, b=100 | Decreases weight of lowest interval |
A neuron will be active only if one or more of its intervals are triggered. When active, only the weights of that neuron can be read by the other neurons connected to it, the weights of other neurons that are connected are ignored. While the upper and lower bounds of an interval can take on negative values (i.e. -1,-100), the weights themselves cannot. This is to be more consistent with the notion that a neurotransmitter in biological organisms can be either present in a certain amount or not present at all. It can also help to properly model how certain neurons wouldn't activate even though there's a high amount of a particular neurotransmitter (medication that is ineffective in correcting chemical imbalances).
That's all I have for now. How the neuron determines the highest/lowest interval or evaluation function to match against the list of intervals hasn't been done yet, but hopefully it will be soon.
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