Do OBEs and NDEs Really Cluster Differently? A Reddit Comment Made Us Find Out

Sometimes the best insights come from your community. This is the story of how a single Reddit comment led us to completely rethink how we visualize consciousness data — and build four different ways to explore it.

The Original Observation

When we launched the 3D consciousness map, we noticed something striking: OBE (out-of-body) experiences clustered separately from NDE (near-death) experiences. The separation was clean and consistent.

We thought this was a meaningful finding. OBEs and NDEs are different phenomena, right? It made intuitive sense that they'd cluster differently.

Then came the comment that changed everything.

The Reddit Comment That Made Us Think

After sharing Noetic Map on Reddit, user u/tekblack from r/AstralProjection asked a question we couldn't ignore:

"Interesting! I see OBEs and NDEs cluster separately. Could this be an artifact from using different questionnaires for OBEs and NDEs?"

This was a brilliant observation. Our data comes from two main sources:

• NDERF (Near-Death Experience Research Foundation) — 5,000+ NDEs
• OBERF (Out-of-Body Experience Research Foundation) — 1,600+ OBEs

Each site has different questionnaires. Different prompts. Different questions that shape how people describe their experiences.

What if the clustering reflected how people were asked to write, not what they actually experienced?

Testing the Hypothesis

We added a "Color by Data Source" option to the map. The result was eye-opening:

The clustering aligned almost perfectly with data source. This meant one of three things:

We needed a way to figure out which interpretation was correct.

Solution #1: Feature-Based Clustering

Here's the insight: if the separation is caused by writing style, we can remove it by clustering on what actually happened instead of the raw text.

We already analyze every experience to extract structured information:

• Greyson Scale scores — 16 standardized measurements of NDE depth
• Element presence — tunnel, light, beings, life review, out-of-body, etc.
• Emotional profile — peace, fear, and love scores

What if we clustered experiences based on these extracted features rather than the words people used?

The result? Feature-Based clustering — a view where writing style doesn't matter, only what people experienced.

Solution #2: Emotional Clustering

We took the same approach with emotional content.

Every experience is analyzed for its emotional quality: how much peace, fear, and love does it express? We cluster by these emotional profiles alone.

In this view, you can see distinct regions of consciousness space:

• Green clusters — Experiences dominated by peace
• Red clusters — Fear-dominant experiences (often distressing NDEs)
• Pink clusters — Experiences centered on love and connection

This view reveals emotional patterns that were hidden in the text-based clustering.

Solution #3: Narrative Only (The Newest View)

But we weren't done. We realized there was another source of potential bias: the questionnaire answers themselves.

When someone submits their experience to NDERF or OBERF, they answer dozens of questions after writing their narrative. Things like "Did you see a light?" or "Did you feel peace?"

Our original text embedding included all of this — the narrative plus the Q&A responses. That meant NDERF's specific questions were literally embedded in the clustering.

So we built a fourth view: Narrative Only.

This view uses only the core story — the person's own description of what happened — with all questionnaire data stripped out. No prompts. No guided responses. Just the raw narrative.

What We Found

With four different views, we can now see which patterns are robust and which might be artifacts:

Patterns that persist across views (probably real):

• Distressing NDEs cluster separately from peaceful ones
• Life review experiences group together
• Entity encounters form their own region

Patterns that change between views (possibly artifacts):

• The sharp OBE/NDE separation is less pronounced in Feature-Based view
• Source-based clustering diminishes in Narrative Only view

This doesn't mean text-based clustering is "wrong" — it just captures different information. The writing style is part of the experience, in a sense. But for research questions like "Are OBEs fundamentally different from NDEs?", we need views that control for how data was collected.

Try It Yourself

The multi-view system is now live. Use the View Mode dropdown on the map to switch between:

Each view has color options that make sense for that clustering:

• Feature-Based → Color by Greyson Category (cognitive, affective, paranormal, transcendental)
• Emotional → Color by Dominant Emotion (peace, fear, love)
• Text/Narrative → Color by Experience Type, Source, or Greyson Score

→ Explore the Multi-View 3D Map

Thank You, Reddit

This feature exists because someone in the community asked a thoughtful question. That's exactly the kind of intellectual honesty we want to enable.

To u/tekblack and the r/AstralProjection community: thank you for pushing us to build something more rigorous.

"What if the clustering reflected how people write, not what they experienced?"

That question made this project better. Keep asking them.

Have a question about our methodology? Find something that doesn't look right? Let us know. The best insights come from the community.