Shownotes
Everything in training assumes that cleaner is better. Cleaner mechanics, cleaner reps, cleaner video, cleaner data. For most of what we do, that is correct. For the visual system, it is sometimes exactly backward.
In this episode, Dr. Laby unpacks stochastic resonance, the phenomenon that in a nonlinear system, adding a precise amount of random noise makes a weak signal easier to detect rather than harder. He walks through Figure 10.1 from Chapter 10 of Eye of the Champion, where a greyscale flag invisible at low contrast emerges once the right amount of noise is added, then disappears again when too much is piled on. The explanation sits at the level of a single neuron: a go or no-go device that stays silent below its firing threshold, and that a little random fluctuation can push over the edge.
Then he brings it to the field. A hitter has roughly 100 milliseconds to identify a pitch, working from the orientation and rate of spinning seams on a three inch ball at 40 to 50 feet. That is a near-threshold signal, which is exactly the regime where stochastic resonance operates.
The turn in the episode is an honest one. The obvious question is who benefits, and the literature does not currently agree. A 2008 study in Tokyo found that the quieter an observer’s internal neural noise, the larger their gain. A 2025 study in Ankara, with 149 participants, found the opposite: the largest gains went to those with the lowest baseline sensitivity. A separate 2023 finding is harder still, showing that an individually optimized noise dose did not replicate when retested in a different session.
The conclusion is a dose, not a direction. More is not better. Optimal is better, and right now, nobody can reliably find the same optimum twice in the same athlete.
Episode Timestamps
- 0:00 The assumption that cleaner is always better, and where it breaks down
- 0:35 What stochastic resonance is, and why Chapter 10 of Eye of the Champion gives it a section
- 1:05 Figure 10.1: a greyscale flag, six levels of noise, and the dose in the middle
- 1:45 Why a single neuron behaves this way: firing thresholds and go or no-go
- 2:30 Noise carries no information, it lends the signal a push
- 2:55 The hitter’s 100 millisecond window, and why spinning seams are a near-threshold signal
- 3:25 Beyond vision: the Ross ankle instability trial and balance from noise too faint to feel
- 3:55 Who benefits? The 2008 Tokyo stereoscope study and internal neural noise
- 4:35 The 2025 Ankara study, 149 participants, and the opposite answer
- 5:05 The 2023 replication problem: Monday’s optimal dose is not Tuesday’s
- 5:35 The inverted U, and why overshooting degrades the athlete
- 6:00 Noise on a screen works as well as noise through electrodes
- 6:20 Nothing to report on the spin app yet, and the bottom line
In This Episode, You’ll Learn
- What stochastic resonance is, in plain language, and why noise can help rather than hurt
- Why the single neuron’s firing threshold is what makes the whole phenomenon possible
- Why a hitter’s pitch identification window is a textbook near-threshold signal detection problem
- That sub-sensory noise improved postural control in a randomized trial of people with unstable ankles
- Why two careful studies disagree about which athlete benefits, and what that means for prescribing
- Why an individually optimized noise dose may not survive to the next day
- That the dose-response curve is an inverted U, so overshooting actively degrades performance
- Why noise delivered through a display works about as well as noise delivered through electrodes
- What has not been studied at all: pitch recognition, spin discrimination, and any competitive outcome
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