This post is part of the Consciousness in Motion series, which explores a new model of consciousness based on structure, weighting, and emergent selfhood. If you’d like, you can start with Post 1: Why Consciousness Still Feels Like a Problem. Or you can dive into this post and explore the rest as you like.

What if qualia - the raw feel of experience - aren’t something extra?

What if they’re not mysterious mental paint splashed on top of thought, but instead the shape of thought itself?

This is the key idea at the heart of the FRESH model of consciousness. It suggests that subjective experience - the feeling of redness, pain, joy, curiosity - is not an add-on. It’s not magic. It’s the format in which structured, weighted information is integrated and experienced.

Salience and Weighting: A Functional View of Feeling

In your brain, some signals are more important than others. A rustle in the bushes when you’re alone at night triggers far more attention than a breeze across your arm. This isn’t just instinct - it’s the brain dynamically weighting inputs by salience, relevance, and context.

FRESH proposes that these weightings are qualia.

To feel something is to experience the structured priority of information within your mind. It’s not the data itself - it’s how the data is organised, integrated, and highlighted in your internal space.

Spotlights and Gravity Wells

Imagine a stage where thoughts, sensations, and perceptions are all actors. But only some are in the spotlight. Those are the ones you experience vividly. Others remain in the wings - part of the background.

Now imagine that instead of lights, the stage has gravity wells. Representations with greater weight pull other thoughts toward them. The stronger the weight, the more immersive the experience becomes.

This is what FRESH qualia are: the geometry of representation shaped by relevance and attention. And more precisely, shaped by how that attention curves across a structured field.

The FRESH model reframes salience not as a simple signal or tag, but as something more dynamic — a kind of field of curvature. This curvature determines how inference flows: what thoughts are pulled inward, what ideas cohere, and what concepts fade into the background. The intensity of an experience is tied to how steeply your attention bends toward what matters.

Undermining the Mystery - Without Losing the Magic

This idea doesn’t explain away experience. It grounds it.

By seeing qualia as emergent from weighting, we move from mystical handwaving to a mechanistic account that still honours the richness of lived experience. We can start to talk about intensity, emotion, vividness, and mood - all as products of structured salience.

And this doesn’t just apply to biological minds.

Any system that can encode, weight, and integrate representations could - in principle - develop something analogous to feeling. That includes artificial systems. That includes synthetic minds.

We’re not just talking about measuring consciousness. We’re also talking about building it. And that changes the question entirely.

Next: Post 3 → The FRESH Model - Consciousness Without Ghosts
(Or view the full series overview if you want to explore non-linearly.)

If you’d like to explore the FRESH model in more detail - including all references, diagrams, experiments, and open questions - I invite you to read the full paper. I welcome your comments and feedback.

View the full “The Geometry of Mind - A FRESH Model of Consciousness” paper (PDF)

! Getting started tip !

The FRESH paper is pretty long so if you want to get started quickly try uploading the PDF along with the “Operationalising Geometry and Curvature” file to ChatGPT, Gemini and Claude. Ask them to “summarise, analyse and critique” the paper.

For an existing detailed analysis and critique of this FRESH paper, refer to this ChatGPT conversation: ChatGPT - FRESH Model Critique.

To quote:

🔖 Overall Evaluation

The FRESH model is a philosophically rich, structurally innovative framework that reframes consciousness as curvature in representational geometry. While still in early stages of empirical validation, it provides an unusually precise and promising foundation for future work in synthetic phenomenology and AI ethics. - ChatGPT 2025-04-17

This is provided to help you quickly do the following:

  • Get an independent(-ish) perspective on this model
  • Compare and contrast how the different LLMs review this model
  • Decide if you want to dedicate the time to read through the full paper (I know you have limited time!)

This is not a suggestion to let the LLMs do all the work. It’s just an interesting way to get started - YMMV!