Hey guys. I’m back in America and I have been pounding out my own code based on the papers for spatial pooling and BAMI.
I’m at the inihibition phase of the spatial pooling algorithm which is pretty straight forward but I’m just wondering if anyone has any insight to its purpose. Implementing it is fine and all, but If I don’t know what it’s purpose is and why I’m doing it, it’s not going to do me any good in terms of contributing extra ideas or thinking about how the whole system is working.
I was wondering if anyone knows if it is inhibiting like signals or if its inhibiting unlike signals. I’m asking because there is a machine learning method I can use, or I could even just use euclidean distance really, to reorganize the neuron arrangement but only if I know the purpose of the inhibition.
Also is radius a biological thing? I know older machine learning methods like kohnen networks and hopfield to an extent use a radius to help organize the neurons, and I suppose cnn’s are sort of relate to radius w.r.t any given signal. But in the brain I was under the impression that the inhibitory effects were based on neurons that an inhibitory neuron is connected, in which case wouldn’t it be best to randomize inhibitory neurons as well.
Just some ponderings I’m having as I program this out. I mainly just need to know if anyone knows the purpose of inhibition and if I am inhibiting like or unlike signals. Any theories and general thoughts are welcome.