I am trying to simulate the below Autism simulation's video by AI models, the scenario could be seen in the below sense of the video: enter image description here

In my hypothesis the visual part of the brain is bombarded by the speech functional part of Brian, and the speech part of the Brian is acting like one hopfiled AI model to clustering the input date and trying to connect to others neighborhood functional part of the Brian, so it is changed to the visual function of the brain.

So I am trying to find some connection between the AI models used in Pix2Pix model ( U-Net and PatchGAN Models) with the Autism brain functionality of having some noise on the visual functionality with sound brain functions, as you can see below:

enter image description here

I guess according to AI Hopfield models when the brain needs to calculate the meaning of the input signals and have some others huge input data, brain try to do tasks by the priority.

So in different scenarios with stimulated part of the brain, and based of the new connected network, there must have different feeling which is these brains have had some map patterns for better predicts their activities and limitation they could improve their weakness by looking what AI Engineering do in AI.

So I have asked one question in the Psychology SE site (here), and if possible, I like to have some comment or answer about the below part of this research:

Finding some equal version of this situation in the AI models like pix2pix model, which give some mathematical model for the way of brain working with autism in a specific scenario.

Also, if possible, I like to know about the way of finding some team working for faster doing this research?




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