To understand one brain, you need to map thousands.

That’s why we built the Myndlift qEEG Reference Database, grounded in tens of thousands of EEG assessments, with about 6,000 meeting strict criteria to serve as the baseline for our individualized brain maps.

Our latest white paper takes you inside the science and methodology behind the baseline, giving clinicians a clear view of how we build a reliable normative dataset and helping individuals understand what goes into creating their brain maps.

But before we dig deeper into the white paper, let’s look at what qEEG is and how it forms the basis of our mapping process.

What is qEEG?

At Myndlift, we use qEEG (quantitative electroencephalography) to measure and analyze the brain’s electrical activity (brainwaves). 

This is made possible by EEG, which captures brain activity in real time, down to the millisecond. 

Visual Guide to Brainwaves: What we've learned about the brain from 1M neurotherapy sessions →

For qEEG, these recordings are then processed using advanced mathematical and statistical methods and compared to brain performance markers in our database.

The markers factor in variables such as age, sex, whether the eyes were open or closed during measurement, and electrode placement. 

These results are visualized as brain maps, allowing clinicians to see where brain activity is within the typical range and where it varies in ways that may benefit from targeted neurofeedback training.

Our white paper explores how we built the benchmark and why it marks a major step toward more personalized, reliable, and effective neurofeedback.

An example of a brain map showing theta wave activity (4–8 Hz) from a qEEG recording.

What’s in the Myndlift database 

The Myndlift qEEG database is structured to ensure accuracy, diversity, and clinical relevance. That begins with filtering for “healthy” baselines.

Strict inclusion criteria 

To ensure the integrity of the reference, only individuals who met strict criteria were included: a General Health Questionnaire (GHQ-12) score of 15 or below, full EEG coverage across 9 electrode sites, and recordings that were free from non-brain signals like muscle movements, eye blinks, or electrical interference.

Large and age-diverse sample

As of September 2024, the database included EEGs from 5,881 individuals, aged 10 to 65, with a balanced representation across the sample.

Organizing the data into 5-year age bands makes it possible to spot patterns and differences that might otherwise be lost in broader age groups.

Designed for clinical relevance

The database supports comparisons using z‑scores, a way of showing how far someone’s brain activity is from the average for their age group, across key brainwave frequencies. 

These results are visualized through detailed brain maps that help clinicians identify areas of excessive or reduced activity, providing a foundation for targeted, individualized neurofeedback.

Read the full white paper here →

Limitations we’re addressing

No dataset is perfect, and we’re transparent about that. 

One area we’re actively working to improve is the age range: while the current database covers individuals aged 10 to 65, we aim to expand it to include younger children and older adults. 

We're also working to increase demographic diversity by including broader representation across ethnic and socioeconomic backgrounds. 

In addition, we’re looking at ways to go beyond self-reports by adding more objective mental health checks, so we can make the database even more reliable.

Why the database matters

The Myndlift qEEG database is grounded in tens of thousands of EEG assessments across a broad population, and provides a reliable, real-world baseline for interpreting brain activity.

Whether you're using brain mapping to guide care or receiving a personalized protocol, this foundation matters. 

It helps ensure that brain activity is being compared to something meaningful: a continuously updated, diverse reference, not static or idealized lab data.

As a result, there’s greater clarity, more confidence in what the data shows, and more tailored neurofeedback.

Adding neurofeedback to your practice? See how Myndlift supports thousands of clinicians with flexible, data‑driven care.

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