Mu 171K does more than sum up a window. Along the way it describes the window in pieces. Each electrode's four seconds are cut into slices of a fifth of a second, 100 samples each, and each slice becomes a token, a list of 76 numbers. The device can send those tokens out.
The documentation said that a reconstruction head, an open add-on, would turn a token back into the slice of signal it came from. When that was tested on the device's own tokens, it scored an R² of −0.12. R² measures how much of a signal's variation is recovered: 1 is all of it, 0 is no better than a flat line, and below 0 is worse than that. The head had been trained on the pieces hidden during the teacher's kind of training, not on the tokens the device actually sends. The claim in the documentation, which the AI had written, was false.
Kris Droste ruled that it would be fixed, and the brief for the next run records the ruling: "The open reconstruction head must do what the docs say it does: turn a token the device sends into the slice of signal it came from." His response to the findings was blunt: "my intuition is that you might be being lazy or drifting and that the correct thing has not yet been built."
The rebuilt reconstruction head is a decoder, a map from the model's numbers back to the signal, and it is linear, the simplest kind. It was scored on recordings from studies it never trained on, leaving out the windows with extreme amplitudes, about 4 percent of them. On the rest it recovers an R² of 0.660, and 0.668 on the studies kept aside only for final testing. It does best on slow rhythms and worst on fast ones: 0.87 from 1 to 4 cycles per second, 0.73 in the alpha range from 8 to 13, and 0.12 from 30 to 45.
The windows left out matter. They carry 92 percent of the signal's power, and with them included, the pooled R² falls to 0.058. The typical window, extreme ones included, is still recovered at a median R² of 0.68.