Do we think about the brain correctly?

I’ve been thinking about the brain architecture in The Bibites and whether the current node-graph structure might be too rigid for a messy, quasi-biological environment.

In biological systems, information processing is often spatial, continuous, and diffuse rather than discrete nodes connected by fixed edges. Because of that, I wonder if an intermediate visual field representation could work better.

Conceptually:

Sensors → internal pixel field → readout → motors

(motors can also paint/update the field)

Instead of nodes holding values, the brain would maintain a small 2D image/grid. Information would be encoded through color and brightness gradients, for example:

• Hue (color on a circular spectrum: red → orange → yellow → green → blue → violet → red) = signal type
• Brightness = signal strength
• Saturation = confidence or activity

Processing could happen through local interactions between neighboring pixels (diffusion, filtering, simple update rules), somewhat similar to reaction–diffusion systems or neural cellular automata.

Potential advantages:

• more continuous and flexible information representation
• easier interaction with environmental gradients or noise
• evolution can modify local rules instead of rewiring node graphs
• the internal state becomes visually interpretable for observers (you could literally watch patterns of activity form)

In other words, the brain would “paint” its internal state and then read from it.

This picture would be part of genes.