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Neural Interface: Precision & Jitter Control (2D)

A Canvas2D neural cursor-decoder: an Ornstein–Uhlenbeck jitter process and a latency buffer corrupt the command toward a target, an exponential moving-average filter smooths it back out — trade off gain, precision and delay live.

Perception & Optical Illusions2DModerate60 FPS⇄ 3D version

The 3D original renders decorative rotating geometry with sliders that only change spin speed — no real neural-decoding math behind it. This 2D companion builds the actual mechanic its title implies: a noisy motor-command signal, generated as an Ornstein–Uhlenbeck jitter process layered on the ideal direction toward a target, passed through a latency buffer and an exponential-moving-average filter before it drives the cursor. Watch RMS error, hit rate and signal-to-noise ratio respond as you trade gain, precision and delay against each other — the same trade-off real EEG/BCI cursor decoders face.

⚙ Under the hood

Ornstein–Uhlenbeck jitter, an EMA low-pass filter and a latency ring buffer drive a decoded cursor toward randomly-placed targets, with live RMS error, hit-rate and SNR readouts.

neural interfacesignal filteringornstein-uhlenbecksignal-to-noise ratio

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install