Alright so to solve both constant spamming and also to solve unequal reward distribution between large neurons and smaller neurons I have thought of two things.
first to tackle neuron proliferation,
as WPB noticed, time locking neurons with the reward multiplier. By time locking neurons for a specific amount of time with a lower probability of being chosen again (if they are chosen they gain no extra rewards). This essentially removes that neuron from the available pool. Meaning that neuron cannot accumulate rewards reducing the incentive to spam or split neurons. Now a large neuron could split itself to try and have a higher chance of being chosen, however, due to randomization they pose the risk of only having 1 of their split neurons be rewarded. This makes it beneficial to keep neurons as large as possible so you get the maximum rewards when chosen.
To try and solve reward distribution.
I suggest we implement a sliding scale for both rewards and for how neurons are selected.
first we break down all available neurons into 4 groups based on voting power. each group will be a range of neurons. Group 1 contains neurons with 0 -100 voting power, Group 2 contains neurons with 100 to 200 voting power, group 3 contains neurons with 200 - 300 voting power, ect
then, we assign each group a number of seats based on the population of the group. example group 1 has 100,00 neurons they get 4 seats, group two has 50,000 neurons they get 3 seats, and so on. Im assuming there are less large neurons then small neurons. We want to make sure that the larger your neuron is the higher chance you have of getting rewards but the lower the rewards are.
When we select neurons to be on the jury we randomly select from the available seats for each group. Remember neurons that already voted have a lower probability to be selected again giving everyone equal chance to gain rewards. Also if neurons are inactive they are replaced by active trusted members of each group. meaning the more you participate the higher the likely hood you can max rewards for the year.
This method can also be applied to reward distribution, where the larger your neuron the less the monthly reward multiplier is to ensure everyone is earning around the same amount of rewards. If the large neurons try to split up to increase their chances of being on selected this will actually hurt them since it will A actually decrease their chances due to limited seats/larger population and be if they are selected they will only receive partial rewards.
The issue that remains is individuals who will automate their voting and never actually manually choose yes or no. I have not found a way to solve this yet. depending on how many individuals try to automate their voting this could be a problem. Maybe a captcha LOL.
another issue I see is neuron burn - If enough proposals are spammed you could essentially lock all neurons with monthly rewards ensuring you get the maximum rewards but im hoping the cost of doing that will dissuade people from trying.
Hope this makes sense.