If you have been working with me you should know there’s a rule: no wearing grid/strip patterns. This is a consequence of my rare, disabling yet fascinating neurological condition known as Visual Snow.

Needless to say I was anxious, extremely depressed, suicidal. I’d like to thank everyone who helped me through my darkest time.

After 3 years, I have largely come in terms with the disease. I regularly donates to its research, however since it is so rare, little result has been shown for it. There are things we do know, however, for example this recent research here:

The TLDR is that there are abnormal regions in visual snow subjects’ brains that are hyperactive. This explains a lot of symptoms, like seeing statics, could be just the brain amplifies random electrical noise that travels in our neurons that gets ignored in normal brains. Assuming this is true, I may have an explanation for our aversion to strips and grid patterns, and that originates from my amateur take from Computer Science.

I am a Machine Learning Engineer, leading a small but strong team developing machine learning algorithm to solve very complicated business cases. In the realm of machine learning, there is this thing called Artificial Neural Networks(ANNs), which are models that have achieved strong results in the realm of computer visions(CV). Neural Networks are inspired, and a very rough approximation of our brains. One of the most famed use for ANNs is Deepdreams, which are trippy images generated by increasing the strength of some of the neurons’ connectivity. Here are some examples:

A

B

What fascinates me the most about deep dream is that people who have had played with psychedelics claim that these images are familiar to their experience with LSD, magic mushrooms etc.

The article also mentions a point that I totally agrees with and I will use as one of the assumption for my hypothesis:

Brain visual systems is very similar to Artificial Neural Networks, and we can apply some things we learn from ANNs to our brains themselves.

One of the features of ANNs are its abilities to distill higher level features through its different layers.

The information is fed from the left, and goes under transformations at each layer, eventually arriving at some conclusion. With each layer, the information gets more abstract and higher level.

There are many technics computer scientists have employed to peek the inner working of ANNs. Here is an example of what it might look like

Assuming my earlier hypothesis, this will be how human recognize the world as well: start with simple edges, build up to small pieces, eventually the whole.

The low-level features are edges. What has the most edges?

Strips and Grids.

Conclusion: In our brains, the massive amount of edges in strips and grids triggers large amount of signals from our brains/visual cortex, and since they are already hyperactive, they overwhelm our senses and cause physical discomforts.

There are more evidence to this.

TLDR: Scientists injected electrodes into cat’s brain, and tries to understand when and how the neuron fires. They tried many different images to no luck, but notice that they fire when the slides shifts. turned out it was the clearly defined edges on the slide themselves that fired it!

Thanks for coming to the Ted talk. I am not a medical professional, and this information probably doesn’t help with research at all. The best I can hope for is for you readers to get a fraction of my joy from discovering this and trying to piece these together.

Trigger Warning: Grids/Strips that I can’t stand to look at attached