A New Step Forward: What Our EEG Study Is Teaching Us About SLC6A1 — And Where It’s Leading Next
By Hamza Dahshi
Grab a mug of coffee (or a sippy cup if you’re five) and let’s talk brainwaves, biomarkers, and what they could mean for every family living with SLC6A1-NDD.
Before We Dive In: Why This Study Matters
If you’re a parent in the SLC6A1 community, you know EEGs are part of the routine — sometimes too big a part. Sticky wires, long recordings, strange terminology, and unclear answers. It’s one of the most familiar tools in our toolbox, but also one of the most frustrating.
What’s been missing all this time is something many families have asked for:
- A way to measure brain activity objectively
- A number we can track over time
- Something that reflects what’s happening in your child’s brain
- …not just whether a spike appeared on the screen
That’s why we began this project. Not to replace neurologists. Not to overcomplicate EEGs. But to simplify the most complex part: turning the squiggles into something meaningful, measurable, and shareable.
What We Wanted to Know
At the heart of this study was one question:
Can we turn EEG slowing — something neurologists see all the time in SLC6A1 — into a real, reliable number?
We focused on one type of slow brainwave called delta power. It’s just one small piece of the EEG, but we had reasons to believe it could tell us something important about the SLC6A1 brain.
So… What Is Delta Power, Really?
Every EEG is made of waves. Some fast, some slow.
Delta waves (1–3 Hz) are the slowest.
In healthy children:
- Delta power is high in babies
- And decreases as kids grow older
This decrease is one of the clearest signs of normal brain maturation.
But in SLC6A1, doctors noticed something different:
- Delta activity stays higher than expected.
- Sometimes it increases with age rather than decreasing.
That unusual pattern — stable, recognizable, and consistently seen across children — is exactly what makes delta power a strong candidate for a biomarker.
A biomarker is something objective you can measure, track, and use to support diagnosis or understand treatment response. Other rare disorders (Angelman, STXBP1, SYNGAP1) have EEG biomarkers too. This study is the first step toward one for SLC6A1.
How We Actually Did the Study
Families deserve to know the real process — not a black box.
- Who participated?
We studied:
- 20 children with SLC6A1-NDD
- 20 neurotypical controls matched by age and sex
These were 4-hour video EEGs with awake time marked and reviewed by pediatric epileptologists. This is the “Phase 1” of biomarker development — the stage where you compare SLC6A1 to typical development to find a clear signal. Later phases (which are already being designed) compare:
- SLC6A1 vs. other DEEs
- SLC6A1 at baseline vs. SLC6A1 after treatment
- SLC6A1 over months and years, which is already underway
But step one is always: Can we detect a difference from healthy development?
And we did.
- How delta power was actually measured
We used two completely different tools to ensure the results weren’t dependent on one program’s quirks:
EEGLAB (research tool)
- Open-source
- Transparent
- Scriptable (you can see every step)
- Used in academic EEG labs
Here, we:
- Cleaned artifacts
- Broke the EEG into frequency bands
- Measured the energy in the 1–3 Hz delta range
- Averaged those values across channels
Figure 1. Sample output from EEGLAB’s spectral analysis function (delta band highlighted).
Persyst (clinical tool)
- FDA-cleared
- Used in many U.S. hospitals
- Automates artifact removal and power trends
- More “plug-and-play,” closer to real-world practice
Here, we:
- Exported delta-power data in 8 seconds chunks (aka, epochs)
- Used threshold-based metrics (how often delta rises above a certain level)
- Calculated several delta-derived measures
- Mean delta power
- Frequency of delta bursts
- Percent of time above threshold
- Delta activity rate per hour
Even though their internal methods differ, both systems showed the same overall pattern — reinforcing delta power as a robust signal.
What We Found
- Delta power is higher in almost all children with SLC6A1.
19 out of 20 children showed elevated delta power. The difference wasn’t small — it was strong and consistent.
- The trend with age is the opposite of typical brain development.
In healthy kids, delta declines steadily. In SLC6A1, delta stays high or increases.
This “crossing trajectory” is meaningful. It suggests that delta power reflects the underlying developmental differences in the condition.
- Just two numbers — age + delta power — could nearly separate SLC6A1 from controls.
This simple model achieved an AUC near 0.99. This does not diagnose SLC6A1. But it tells us that the EEG carries more information than we’ve been using.
And that’s extremely encouraging.
A Quiet but Powerful Finding We Haven’t Talked About Before
There is one additional finding we want to share openly with families — not as a conclusion, but as a meaningful early observation that shaped the direction of our next steps.
As part of the SLC6A1 Natural History Study, many children return each year for follow-up EEGs. These repeated recordings help us understand how brain activity changes over time. During these visits, a few children happened to begin treatment with Ravicti as part of a separate clinical trial.
When these children came back for their next yearly EEG, something caught our attention: Their delta power had noticeably decreased compared to their baseline recordings.
To be very clear:
- This was a small group of children
- This was not part of a controlled analysis
- The study was not designed to measure treatment effects
But even with those limitations, the difference stood out. It did not look like typical day-to-day EEG variation. It was stronger than the small fluctuations we normally see between yearly visits.
The research team paused and asked the natural next question: “If delta power changes this noticeably in even a few children after treatment, could it one day help us measure treatment response more systematically?”
This observation does not prove that Ravicti or any therapy changes delta power. But it provides an important signal — the kind that tells researchers:
- There may be more information in the EEG than we are currently using
- Delta power might reflect something about how the brain responds to interventions
- We urgently need larger, more controlled studies to explore this further
These early hints helped shape the next phase of our quantitative EEG efforts: expanding sample sizes, refining methods, and building tools that can evaluate these changes objectively and consistently.
What This Means for the Future
This isn’t about Ravicti specifically. It’s about something bigger: Delta power might not just reflect diagnosis — it might reflect response to treatment.
Imagine a world where:
- A therapy starts working
- Your child doesn’t need to wait months to see developmental changes
- And the EEG gives an early sign that the brain is responding
That is the long-term vision. This is why your participation matters so deeply. This is why these small “clues” matter. This is why expanding the quantitative EEG program became a priority.
A Final Thank You — From All of Us
Every parent who drove to an EEG appointment… Every child who sat through the leads and the gel and the wires… Every family who agreed to yearly follow-ups…You made this possible.
This was the first step — and because of you, we already see the path toward the next.
We are honored to walk this journey with you, and we promise to keep sharing each new discovery with the openness, transparency, and hope you deserve.