The Hard Case: Autism and Stimming: Stop Fighting It And Start Teaching!
Hand flapping, rocking and humming aren’t defiance. They’re a regulator doing its job, and the correction most schools use makes it worse.
A student flaps their hands every time they land a kick. Another rocks in line while the class waits, or hums through the bow. A parent in the lobby looks embarrassed, an instructor says “Hands still, please,” and the student who was finally getting it starts to come apart.
That correction is usually aimed at the wrong thing. The stim is most likely doing a job for that student, and if you stop it, the student still needs to settle, so it tends to show up as something else (often something bigger).
Put a prediction engine on the front of a control loop and you get a system with two dials. That’s the architecture of every serious control system built since 1960, and it’s where I spent my first career before I spent this one. I think it’s running in every one of us too, including every kid on your mat.
Autism is the hard case, and a framework has to hold up on the hard cases or it isn’t worth much. The behavior is common, the accounts of it conflict, the intervention history is ugly, and the people it describes are right there and can tell you whether the description fits.
What stimming is for
What is stimming, and what’s it for? Repetitive, usually rhythmic movement or sound a person generates for themselves… hand flapping, rocking, finger flicking, spinning, humming, watching moving light. Everybody does some version of it (cracked your knuckles in a meeting lately?). What makes autistic stimming different is how often, how intense, what form, and above all how the people nearby react to it. Autistic adults say it regulates them. Distress relief is the outsider’s guess.
When Kapp and colleagues sat down with 32 autistic adults and asked, the answer went in both directions (Kapp et al., 2019). Some stimmed when they were anxious. Some stimmed when they were THRILLED.
As Rebecca put it:
“[s]timming is just a release of any high emotion, so really anxious, really agitated, really happy, really excited, just any high emotion, that’s when I stim.”
The emotion changed from person to person. What stayed the same was how strong it was. Two participants even described happy flapping as a different movement from anxious flapping… hands open and arms out, where the anxious version is tight and close.
Sinead’s childhood spinning isn’t soothing anything, and she says so:
“I remember as a child spinning all the time and loving spinning and loving swinging and feeling that movement all the time, but then I also realised that there was a point where it wasn’t acceptable to be spinning anymore … so it actually still feels glorious if there’s nobody around and I can skip or I can spin and it’s like I’m breaking the rules.”
Two words get used for what stimming does, and they aren’t the same word. Self-soothing is an observer’s inference, what the behavior looks like it’s for, from outside, in a person who appears distressed. Self-regulation is closer to what autistic people report, and it’s a bigger idea.
I’ll own my share of that first one. I spent years describing this behavior with a word nobody had ever tested against what the person doing the behavior reported. The label traveled on how plausible it sounded from across the room.
A behavior that shows up as reliably in joy as in distress is doing something other than soothing. It’s bringing an aroused system back into a workable range, from whichever side it left.
Luke’s account stuck with me, because he’s describing the engineering and doesn’t know it. On rotating his wrist:
“it helps you talk to yourself at a rhythmical pace, so when I’m doing this I can sort of think in the rhythm that I’m moving my hand … which is very helpful because it means like when you’ve got your internal monologue it doesn’t all come in at once and you find yourself sort of shouting at yourself in your head to get everything done.”
The same motion, he said, calms the body “in time with the pendulum”… “it sort of metronomes everything in your body” (Kapp et al., 2019). That is a person imposing a timing signal they control on a system that’s running too many things at once.
“Self-stimulatory behaviour” came out of behavior-analytic research in the 1970s, where it named repetitive behavior that looked like it competed with teaching (Lovaas et al., 1971). Follow that logic and you get extinction. Generations of autistic kids were taught to sit on their hands.
“Stimming” is the community’s reclamation of that term, and the shortening isn’t cosmetic. It drops the pathologizing frame and keeps the descriptive content.
Labeling is where stigma starts: pick out a human difference, give it a label, then attach the stereotype (Link & Phelan, 2001). Sinead feels that from the inside – spinning “actually still feels glorious if there’s nobody around” (Kapp et al., 2019).
Put every regulation behavior on one ladder, sorted by cost. The low-cost end holds mantra, slow breathing, stimming, rocking, exercise, dancing and time inside a special interest. Autistic bloggers describe the same functions under lists, routines, stims, exercise and dancing: a sense of control, recharging, and a reliable way to head off overwhelm (Petty & Cantwell, 2025). Autistic adults interviewed about flow described stimming as one way in, because it creates predictable sensory input that blocks out the overwhelming kind (Wain et al., 2026).
The high-cost end holds behaviors that do the same regulating job and hurt the body doing it. Self-injury is one – the self-injury addendum covers it in clinical terms. Most stims don’t injure the body – a lot of the cost may come from how the people around the kid react.
Where do your own habits sit on that ladder (a pen clicked through a meeting, a knee bouncing under the desk, playing with a fidget spinner)?
The same complaint keeps coming up in the first-person research, and it isn’t about brightness or volume. The world is hard to predict, and it costs a lot to keep regulating something you can’t predict. Stimming, routines, deep focus, sitting in the car at lunch with the environment set the way you want it… every one of them buys predictability back, either by making a signal you control completely or by taking the variance out of what comes in. Take the strategy away and the load is still there.
One autistic teenager explained to Adams and colleagues why a heartbeat is readable and hunger isn’t (Adams et al., 2025):
“Because hunger and thirst or needing the toilet do not have a set order or schedule I often misread them . . . But because heart rate and breathing are consistently there when I do tune into them it is not confusing for me to interpret.”
A signal that shows up on a schedule is readable. One that shows up whenever it wants is hard to read. That’s a difference in inference, and sensitivity has nothing to do with it.
Stimming as a limit cycle
What does the control model say stimming is? A limit cycle, which is engineering for a loop that can’t sit still. Turn the gain up and the damping down on any control system and it overshoots the target, corrects, overshoots the other way, and settles into a steady rhythm instead of settling down. Rocking, flapping, pacing and vocal repetition all have that form… rhythmic, roughly periodic, and they stop on their own when the disturbance passes.
The model has two dials, and you need both to follow this. Observer gain is how much your senses move your estimate of what’s going on, against what you already expected (predictive processing calls it precision). Controller gain is how hard you act on the gap between that estimate and what’s coming in. The first dial is about what you believe is going on. The second is about how hard you push, and belief has nothing to do with it.
The autism literature has spent about fourteen years arguing about the first dial… whether autistic perception runs on weak priors or on over-precise senses. As far as I can find, nobody has modeled or measured the second one. That’s a strange gap, because the second dial is where repetitive behavior comes from.
The engineering is elementary. A loop with high gain and not enough damping doesn’t just respond too strongly. It oscillates. Repetitive behavior is what an oscillating loop produces.
The claim is stronger than “oscillation causes stereotypy.” Stereotypy IS oscillation, in the engineering sense of the word. If that’s right, it has frequency structure you can measure, and that structure tracks the loop’s settings rather than how unpleasant the environment is.
Two more features fall out for free.
Insistence on sameness. An under-damped loop is fine until something bumps it. Then it rings. If every disturbance costs you a long, expensive recovery, avoiding disturbances is the rational move, and “rigid” is the wrong word for it. One autistic adult told Todorova and colleagues what a small one costs (Todorova et al., 2024):
“Like one morning my light didn’t work, which objectively is not a big deal, but it made me very anxious because that is THE first thing I do in the morning so I ended up getting out of bed much later because it made me very anxious.”
That’s disturbance avoidance in a system where recovery is expensive, described from the inside.
Meltdown. Escalation is what an under-damped loop does when the disturbance won’t stop, or when every correction creates new error. A kid in Phung and colleagues’ interviews called a meltdown “a passenger on a ride of destruction… and it’s like hitting a bunch of stuff” (Phung et al., 2021). The kid isn’t the one driving. Another one explained why holding it in doesn’t work: “whenever I try to contain any sort of emotion or anything, it’ll just keep building up.”
That maps onto instability better than onto big feelings, and the two make different predictions. An intensity account says the size of the response scales with the size of the trigger. An instability account says past a threshold, the size of the trigger stops mattering. That’s testable, and cheaply.
Why more feedback can make it worse
Why would more feedback make performance worse? Because if a loop is already near its stability limit, turning the gain up pushes it over. That one inference is what separates a stability reading from a sensory-overload reading. Overload predicts that performance gets worse as the input gets more unpleasant. Instability predicts a specific kind of worse: more oscillation, more regular output, and steeper at the high-gain end.
Four findings from four independent groups already fit, and none of them were collected to test this. Each one was reported as a separate deficit. They lean toward stability.
The eyes-open result. Under overload, closing your eyes removes an input, so sway ought to get worse with the eyes closed, the way it does in nearly every other population (vision is stabilizing). Bloomer and colleagues found the group difference more apparent with the eyes open (Bloomer et al., 2025). Adding a feedback channel made it worse. That’s what raising loop gain does, and it isn’t what removing sensory burden does.
The dynamic-only result. Lidstone and colleagues found the deficit for moving targets and not static ones, with the same display in both (Lidstone et al., 2020). The intensity was the same, and the tracking demand wasn’t.
The form of the degradation. Excess power below 0.25 Hz (Lidstone et al., 2020), more periodic reactive adjustments (Mosconi et al., 2015), and reduced entropy with increased regularity (Pettinato et al., 2024; Unruh et al., 2021) all describe output getting more rhythmic. Overload and distraction make output noisier. Instability makes it more regular, because a limit cycle is highly regular.
Degradation at both extremes. Mosconi and colleagues found worse performance at highly amplified and highly degraded feedback gain (Mosconi et al., 2015). Too much loop gain destabilizes. Too little leaves error uncorrected. An intensity account has no reason to expect that turning the feedback DOWN also hurts.
Where the model stands
Where does this stand? Untested, which is a different thing than wrong. Every finding above was collected to answer some other question, and all four lean the same way. That’s a reason to run the experiment. Nobody has turned observer gain and controller gain separately in autistic participants, measured damping directly, or predicted a treatment response from loop settings and then checked. The test I’d run first is cheap.
My position: I am not an autism researcher. I’m an engineer and a therapist looking at other people’s data to see if the model fits.
The thing to watch with a model like this one is the dials. It has four (plus delay, plus arbitration), and with that many dials you can explain anything after the fact. Sensory therapy helped? Must be observer gain. It didn’t? Wrong dial. That’s rationalization running out ahead of logic, which is the normal human order of operations, and it’s the reason the model needs a test it can lose, decided before the data comes in.
What I’d do if I had a lab is simple. Turn the display gain up and watch whether the kid’s repetitive behavior goes up with it, in the same session. The equipment exists. If the behavior doesn’t move, the model is wrong about autism and we go back to the whiteboard.
There are six more tests like it in the full document, and my article How to Prove This Wrong goes through each one as a commitment.
What a clinician can do with this
What does a clinician do with this? Ask what the stim regulates before anybody asks how to stop it. When a stim hurts the kid (or someone else), find a lower-cost one that does the same job. Tell the family why predictability helps, and say out loud that the trial evidence for it is thin. DON’T pick a treatment because of this model… every treatment in the table below stands or falls on its own evidence, and most of that evidence is weak.
Start with what the people running the system say. Kapp’s participants objected to treatment aimed at wiping out stimming, tried on their own to suppress the stims that hurt them, and the ones who could hold a stim back described it as draining work (Kapp et al., 2019). Masking, the work of hiding autistic traits, is the reason autistic adults give most often for autistic burnout (Raymaker et al., 2020; Mantzalas, Richdale, Adikari, et al., 2022), and a model of burnout risk lists stimming as protective (Mantzalas, Richdale, & Dissanayake, 2022).
One warning. Autistic burnout is not depression. Treat it as depression and prescribe behavioral activation (more people, more activity, sit still and be calm) and you will make it WORSE. The autistic adults in Raymaker’s study named those exact recommendations as the things that made it worse (Raymaker et al., 2020).
One more thing to check before any emotion-focused work. Roughly half of autistic people have alexithymia, trouble naming their own feelings, against about 5% of everybody else (Kinnaird et al., 2019). A kid who can’t name a feeling may need help reading their own body (remember the heartbeat and the hunger) before any technique that starts with “what are you feeling?” can land.
Then the model, which gives you a reason behind the first-person reports. If a stim is the visible output of a loop correcting error, suppressing the stim removes the output. The error stays. The model predicts displacement: the error finds another output, or it piles up until it produces a bigger event. That’s a mechanical reason for the concern autistic adults keep raising, and it deserves to be treated as one instead of filed under values.
The table puts what the model says next to what the evidence says, for the treatments a family will ask you about. Keep the two columns separate. A treatment fitting the model is no evidence that it works, and a treatment working is no evidence for the model.
| What families ask about | What the model says it does | What the evidence says | What I’d tell the family |
|---|---|---|---|
| Predictability: routines, advance notice, visual schedules | Fewer disturbances for a loop that rings after every one | Thin. Mostly practice wisdom and single-case designs; a 2026 meta-analysis of transition signaling found no significant overall effect (Kim et al., 2026) | Do it anyway. Low cost, low risk, and it’s what autistic people say they want. Don’t claim a trial base that isn’t there. |
| Sensory integration / OT | Turns observer gain down | Low. The better-designed studies produce the weaker results; OT and ABA came out comparable, and neither beat no treatment on a standardized daily-living measure (Schaaf et al., 2025) | Fine for individualized goals. Not a reason to expect the loop to change. |
| Weighted blankets, deep pressure | Adds a steady, high-precision reference signal | Null on every objective sleep measure in a 73-child placebo-controlled crossover; kids and parents preferred it anyway (Gringras et al., 2014) | Let them have it because they like it. Don’t present it as a treatment. |
| Exercise | One of the few things that acts on the controller: discharges error, may add damping | Moderate quantity, weak quality. Ranks first for irritability and behind medication for stereotypy (Liu et al., 2026) | Worth doing. Untested on the loop itself. |
| SSRIs for repetitive behavior | Would have to lower controller gain | Good quality and negative. Citalopram did no better than placebo and was linked to MORE stereotypy (King et al., 2009); the Cochrane review found no evidence of effect in children (Williams et al., 2013) | No. The extra stereotypy is what a loop model predicts from a drug that raises drive without adding damping. |
| Melatonin and sleep | Sleep loss degrades the prediction and raises gain | Good for sleep: 44 minutes more sleep and 39 minutes faster onset against placebo (Rossignol & Frye, 2011) | Yes, for sleep. After a bad night watch for a specific pattern: more stimming, more reactivity, faster escalation. |
| Communication access (AAC) | Doesn’t tune the loop. Removes the disturbance the loop keeps trying to correct | Moderate for requesting (Huang et al., 2026); thin on everything else | First on the list. If the model is right, working AAC lowers stimming and distress too… nobody has measured that yet. |
The practical position the evidence and the model both support: treatments that add capability (communication first) have a reason behind them and, for AAC, some evidence. Treatments whose main goal is making visible repetitive behavior go away have no good evidence of benefit, a mechanical reason to expect displacement, and clear first-person testimony against them. That’s enough to guide practice without settling the larger argument about ABA.
Two cautions, and they outrank the model.
Autism research has moved, unevenly, from a deficit model toward a difference model, where most of the disability sits in the mismatch between the person and the environment (Pellicano & den Houting, 2022). Under a deficit model the target of treatment is the person’s behavior. Under a difference model the target is the fit. Same assessment, two different plans, and a mechanical model of stimming can be used to argue for either one. I intend it for the second, because most of what presents as dysregulation looks to me like a correctly learned setting running in the wrong environment.
The other is Milton’s double empathy problem: the breakdown in understanding between autistic and non-autistic people runs in both directions, and the clinician is one of the two parties (Milton, 2012).
Any sentence beginning “autistic people are” is a hypothesis to check with the person in front of you. (For parents, the practical version of all of this is in my book Parent Action Plan: Autism.)
What this means on your floor
You don’t need to diagnose anybody to use this. You need to stop treating every stim as a discipline problem.
- Leave a stim alone if it isn’t hurting anyone and isn’t stopping the class. It’s usually regulation, and it shows up with joy as often as with stress.
- Swap a stim that hurts for one that doesn’t. Head banging or biting gets a lower-cost movement that does the same job: squeezing a pad, pressing palms together, a lap around the mat.
- Make class predictable. Same order, same signal before a transition, a heads-up before anything loud. The trial evidence is thin and the cost is close to zero.
- Expect more stimming after a bad night. Sleep loss may turn the gain up (that’s the model, and it hasn’t been tested yet). Either way, it’s a cue to lower demands for the day, not raise them.
DON’T say: “Hands still. Everybody’s looking.”
SAY: “I can see you’re excited. Put that in your next kick.”
When a parent apologizes for it, tell them: “That’s not bad parenting and it’s not your fault. It’s how your child settles. We work with it here.”
This week: pick the one student whose stims you correct the most. For the next four classes, correct nothing that isn’t hurting anyone, and count how many times that student loses focus in class one and in class four. If that number holds steady or drops, you’re on the right track… and if you try this, I’d like to hear what you see.
Common questions
Is stimming a behavior problem?
Autistic adults describe stimming as regulation, and it shows up with strong positive emotion as often as with distress. In one interview study of 32 autistic adults, participants stimmed when anxious and when thrilled (Kapp et al., 2019).
Do instructors need to stop a student from stimming?
Not when it isn’t hurting anyone or stopping the class. When a stim does cause harm, the better move is a lower-cost substitute that does the same regulating job, because suppressing the output leaves the underlying load in place.
Why does a student stim more after a bad night?
Sleep loss degrades prediction and raises gain. More stimming, more reactivity and faster escalation the day after poor sleep fit that pattern, and lowering demands that day is reasonable.
What helps an autistic student in a martial arts class?
Predictable structure, advance notice before transitions, and communication access. The trial evidence for predictability is thin, but it is low cost and it is what autistic people say they want.
Is autistic burnout the same as depression?
No. Treating it as depression with more activity and more social contact can make it worse, which autistic adults named directly in research on burnout (Raymaker et al., 2020).
References
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A version of this article first appeared at mastermoody.com. For the school-owner companion, see Autism in Your School.
