Part 1 · For drug development
We used the Foundational Brain Model to identify clinically relevant subgroups and clarify responder and placebo effects. These are retrospective analyses of completed studies, so they support development decisions and prospective study design rather than claiming prospective clinical validation.
+11.1 percentage points
CAN-BIND-1 · response rate, N=181 → 70
The Foundational Brain Model identified a model-positive subgroup. Its observed response rate was 58.6%, compared with 47.5% in the full dataset. Mean MADRS improvement changed from −13.7 to −16.2 points.
NCT01655706 · Ontario Brain Institute · 6 Canadian sites · escitalopram
p = 0.01
EMBARC · from p = 0.14, N=199 → 145
The model stratified participants by predicted placebo-response risk. In the lower-risk subset, the observed sertraline-versus-placebo difference changed from −1.33 (p = 0.14) to −2.63 (p = 0.01). The response-rate gap increased from 11.4 to 16.1 percentage points.
NCT01407094 · NIMH-funded · 4 US sites · MDD, HAM-D at week 8
86% / 79%
Alzheimer's · sensitivity / specificity
>800 subjects with primary diagnosis and EEG; >1,000 with secondary diagnosis; >500 with EEG recorded prior to diagnosis. Brain age delta carries independent predictive power for neurodegenerative condition.
Early result · retrospective, internally validated
All three are retrospective re-analyses of completed studies, not prospective results.
Phase 1 generalized anxiety disorder (GAD) program: reference distributions for 14 QEEG biomarkers from 859 GAD-diagnosed patients and ~103,000 clinically referred comparator subjects.
“Theta power, alpha asymmetry, connectivity and network features showed negligible population-level separation (d < 0.2). We publish what doesn’t work.”
| Task | Result | Status |
|---|---|---|
| Placebo response prediction | ~70% accuracy · 69% balanced accuracy across 3 independent datasets | Peer-reviewed, Neuroinformatics 2025 |
| Alzheimer's detection | Sensitivity 86% · specificity 79% | Early result |
| Seizure detection | ~92% accuracy | Early result |
| Sex prediction | ~84% accuracy | NeuroImage 2024 |
| Brain age | MAE ~5 years | Front. Aging Neurosci. 2022 / 2024 |
Predicting Placebo Responses Using EEG and Deep Convolutional Neural Networks
Neuroinformatics, Vol 23, art. 32 (2025) · DOI: 10.1007/s12021-025-09725-6
Predicting age from resting-state scalp EEG signals with deep convolutional neural networks
Front. Aging Neurosci. 14:1019869 (2022) · DOI: 10.3389/fnagi.2022.1019869
Prediction of brain sex from EEG using a large-scale heterogeneous dataset
NeuroImage 2024 Jan;285:120495 · DOI: 10.1016/j.neuroimage.2023.120495
Optimization of the Deep Neural Networks for Seizure Detection
ICASSP 2023, Rhodes Island · DOI: 10.1109/ICASSP49357.2023.10094645
Data Leakage Problem in Large Multi-site EEG Datasets
ISBI 2023, IEEE, Colombia
We test whether the model is learning clinically relevant biology, rather than shortcuts such as the hospital or recording device used to collect the data. The main limitation today is that these trial results come from retrospective re-analysis. Prospective validation is still required, and no Brainify.AI biomarker has been qualified by FDA or EMA.
Multi-site EEG can leak recording-site information into a model. We published this failure mode (IEEE ISBI, 2023) and use leakage-aware validation splits so performance is less likely to reflect which hospital collected the signal.
The trial results above are retrospective re-analyses, not prospective results. Prospective validation is in progress; regulatory qualification has not yet been obtained.
Part 2 · For wellness partners
Plainer, shorter, no p-values. Written for a medical director deciding whether to put this on their menu.
Scores are compared against age- and sex-adjusted reference distributions built from 500,000+ brain scans. This is a clinical-population reference, not a screened healthy-control cohort — a score in the typical range means typical relative to that population.
Our EEG brain-age model has a mean absolute error of approximately 5 years. Brain age reflects current brain state — including sleep, arousal and time of day — and is not a measure of neurological health or cognitive ability.
Research collaborations with Harvard Medical School, Weill Cornell Medicine and UC Irvine. Scientific advisory board: Pizzagalli (UC Irvine), Liston (Weill Cornell), Fava (MGH), Deligiannidis (Northwell), Freeman (Harvard Medical School), Doherty (Acumen, ex-Sage, ex-AstraZeneca), Kelly (ex-Novartis).
Professional-grade 19-channel array. Medical-grade components — Swiss-made sensors, Japanese cap materials, biocompatible. EMC and electrical-safety tested. Passive recording: no current, no stimulation.
For general wellness use only. Not a medical device. Not intended to diagnose, treat, cure, mitigate, or prevent any disease or condition. Does not constitute medical advice.
Not a diagnostic. Not a screening test. It does not detect, rule out, or monitor any medical condition. If a recording cannot be scored or shows an atypical pattern, the report is withheld and your center advises the client to consult a physician.