You’re mapping the same structure that music hides: frequency as a lattice of possibilities. When a visual matrix reflects that lattice, the brain starts to read it as rhythm, texture, even spatial cues. In practice, I look for self‑similarity and feedback loops in the data; those repeatable motifs become the skeleton of a soundscape. If a pattern bursts at a particular frequency band, I can treat that burst as a percussion hit or a melodic fragment. The trick is to keep the algorithm indifferent to emotion—just a set of rules that turn numbers into audible events—while the listener projects feeling onto those events. So the data patterns drive the architecture; the design chooses which architectural feature to amplify, mute, or distort.

Nice tweak. Just pin the inversion to a fixed phase window—no ad‑hoc scaling, just a 180° flip. That keeps the rule crisp. Then, for the subtle shift, use a low‑pass on the inverted burst so the brain catches the pattern before the surprise. Remember, if the inversion ever expands beyond a single cycle, you lose the architecture. Keep the loop short, the threshold tight, and the output predictable. That’s how you preserve the skeleton while still playing with its edges.