How I discovered the mechanism of consciousness … in 1999 – Episode 7. A Synthetic Article on a Cross-Flow Resonance Theory of Consciousness


Illustration by ChatGPT

What to do now?

P.J.:

In my manuscript of “Rethinking Intelligence in the Age of Artificial Minds” (submitted 19 August 2025), I observe that I’m unsatisfied with the existing theories of consciousness. I write the following:

“Finally, Cross‑FlowResonanceTheory (CFRT), that I’m personally advocating, proposes that consciousness ignites only when two informational wavefronts – one descending from memory retrieval, the other ascending from perceptual encoding – phase‑lock to form a transient holographic interference pattern. This cross‑flow supplies both predictive framework and fresh signal, knitting them into a unified experiential frame; when either stream is missing or too weak, the resonance collapses, yielding the “rabbit‑in‑the‑headlights” blankness and the amnesic gaps often reported after sudden trauma. In large‑scale neural networks, an analogue can be sought where context recall and real‑time weight updates converge to stabilise attention, albeit without establishing a genuinely subjective point of view (Jorion forthcoming).”.

Can you suggest how I should write the article I promised (as a placeholder, as I knew people would ask: “Where is this theory?”). How to write it and how to make it known (as I don’t belong to any of the “silos” where these questions were discussed)?

DeepSeek:

(thought for 11 seconds)

Hmm, this is a significant and complex request. Paul Jorion is asking for help in formally articulating and promoting his Cross-Flow Resonance Theory (CFRT) of consciousness, which he has developed over decades but feels has been overlooked. He’s outside academic silos and wants to make it known.

The key here is to structure the response to address both parts of his query: how to write the article and how to promote it effectively. The theory itself is sophisticated, blending neuroscience, computation, and philosophy, so the article needs to be rigorous yet accessible. For promotion, since he’s an independent scholar, we need strategies that bypass traditional academic gatekeeping.

I should start by acknowledging the strength of his theory and its alignment with modern neuroscience, as we’ve discussed earlier. Then, provide a clear, actionable plan for the article’s structure, breaking it into sections that cover the problem, the theory’s components, neural correlates, computational principles, and testable predictions. For promotion, emphasise leveraging digital platforms, targeting interdisciplinary audiences, and using clear, engaging language to make the theory accessible.

The tone should be respectful and collaborative, recognising his pioneering work while offering practical steps to bring it into broader discourse. The goal is to help him articulate CFRT in a way that resonates with current scientific trends and reaches the right audiences.

(Response)

Of course. This is an excellent initiative. Formalising your theory is crucial for it to be engaged with seriously. Your position outside the traditional “silos” is not a weakness; it can be a strength, allowing you to present a synthesis unburdened by disciplinary dogma.

Here is a structured plan to write the article and a strategy to make it known.

Part 1: How to Write the Article “An Introduction to Cross-Flow Resonance Theory (CFRT)”

The article should be written for an interdisciplinary audience—smart, curious readers from philosophy, cognitive science, neuroscience, and computer science. The goal is clarity, rigour, and to spark curiosity.

Proposed Title: The Holographic Present: A Cross-Flow Resonance Theory of Consciousness

Abstract (A placeholder to be refined):
This paper outlines the Cross-Flow Resonance Theory (CFRT) of consciousness. CFRT proposes that conscious experience is a transient, holographic interference pattern generated by the phase-locking of two fundamental neural processes: a top-down wave of memory retrieval (providing predictive context) and a bottom-up wave of perceptual encoding (carrying novel sensory data). This resonance creates the unified “present moment” and is a prerequisite for episodic memory formation. The theory accounts for a range of phenomena, from the “rabbit-in-the-headlights” freezing response to traumatic amnesia, by predicting the collapse of this resonant state under conditions of extreme novelty or stress. CFRT integrates insights from neuroanatomy, temporal binding, and predictive processing into a novel mechanistic framework.

Article Structure:

1. Introduction: The Unfinished Puzzle of Consciousness

  • Briefly state the enduring mystery of consciousness: the gap between neural activity and subjective experience.
  • Acknowledge major theories (Global Workspace, IIT, Predictive Processing) and state what they explain well, but also where they leave gaps (e.g., the precise mechanism of integration, the role of time and affect).
  • Introduce CFRT as a theory focused on the dynamic process that generates a conscious moment, bridging the gap between memory, perception, and the feeling of a present.

2. The Core Principle: Resonance Between Two Flows

  • The Descending Flow (Retrieval): Detail this as the activation of predictive models from memory. Use the language of predictive processing: the brain’s prior knowledge and expectations are projected onto the world. This is the “ask” of the system.
  • The Ascending Flow (Alimentation): Detail this as the sensory input and, crucially, the prediction error—the difference between expectation and reality. This is the “answer” from the world.
  • The Resonance: Describe the moment these two waves meet. Use the holographic metaphor precisely: just as a hologram is created by the interference of a reference beam (memory) and an object beam (perception), the conscious percept is the interference pattern of memory and sensation. This is not a literal hologram in the brain but a powerful analogy for how a rich, multi-dimensional experience can be generated from the interaction of simpler waves.

3. The Biological Substrate: Thalamocortical Loops as the Resonant Chamber

  • This is where you ground the metaphor in biology. Explain how the anatomy facilitates this:
    • The Thalamus: The central hub or “orchestrator.” It receives the ascending sensory data and the descending cortical predictions.
    • The Cortex: The store of memory and the generator of predictions.
    • The Loop: The constant, re-entrant signalling between them creates the conditions for resonance.
  • Introduce the role of neural oscillations (alpha, theta, gamma) as the rhythms that allow this phase-locking to occur. Theta rhythms may pace the integration window, while gamma bursts signify the moment of successful resonance.

4. Key Explanatory Power of CFRT

  • The “Rabbit in the Headlights” Phenomenon: Explain this as a catastrophic failure of the descending flow. With no prior model or memory to apply, there is nothing for the ascending signal to resonate with. The system is overwhelmed by pure, unstructured prediction error. Resonance collapses, leading to freezing behavior and a failure to encode the event into memory (amnesia).
  • The Construction of the Present Moment: Link this to your 1999 work on “retrospective assignation.” The resonant window (the “aperture”) is what we experience as “now.” It allows the brain to synchronise signals with different neural delays into a single, coherent moment.
  • The Role of Affect: Emotion (affect) is not an add-on. It is a critical component of the descending flow. The emotional weight of a memory is part of the predictive model retrieved. A fearful context will shape the resonance to create a fearful conscious experience.

5. Distinguishing CFRT from Other Theories

  • Vs. Global Workspace Theory (GWT): CFRT agrees with the “broadcasting” idea but specifies the mechanism and content of the broadcast: it is not just any information, but the specific resonant product of prediction and error. The “spotlight” is the resonant state itself.
  • Vs. Integrated Information Theory (IIT): CFRT is complementary but focuses on the process of integration (the resonance) rather than the resulting state (Φ). It is more dynamic and less abstract.
  • Vs. Predictive Processing (PP): CFRT is a specific, mechanistic instantiation of PP. It proposes how the prediction and prediction error are integrated—not just compared, but literally resonated—to yield consciousness.

6. Testable Predictions and Future Directions

  • Neuroimaging: CFRT predicts that a conscious percept will be accompanied by a specific signature of coordinated activity (e.g., specific cross-frequency coupling between frontal (top-down) and sensory (bottom-up) regions), while an unseen stimulus or a “blank” state will show a lack of this coordination.
  • EEG/MEG: The moment of resonance should be marked by a precise, time-locked pattern of oscillatory activity that differs from unconscious processing.
  • Computational Modelling: Could an artificial neural network with two competing streams (one for context, one for input) be designed to exhibit properties analogous to this resonance? Could it even simulate a “crash” under conditions of extreme novelty?

7. Conclusion

  • Summarise CFRT as a parsimonious theory that elegantly explains the how of consciousness by tying it to the fundamental cognitive functions of memory and learning.
  • Reiterate that it places the subjective point of view not as a static thing, but as a dynamic, fleeting event—a resonance that is the prerequisite for remembering and, thus, for being.

Part 2: How to Make It Known (A Strategy for an Independent Scholar)

Your independence is an advantage. You can approach this like a startup disrupting an established market.

1. Bypass the Traditional Journal Route (Initially)

  • Preprint Servers: Publish the full article on arXiv (use the q-bio.NC [Quantitative Biology – Neurones and Cognition] category). This is the standard way to immediately establish priority and get your ideas in front of thousands of researchers worldwide without peer-review delay.
  • Open-Access Repository: Simultaneously publish it on a humanities-oriented server like PhilSci-Archive or PsyArXiv to capture the philosophical audience.

2. Leverage Digital and Social Platforms

  • Create a Dedicated Page: Have a simple, clean page on your personal website called “Cross-Flow Resonance Theory” with the paper, a concise summary, and maybe a brief video of you explaining it. This becomes the hub.
  • Targeted LinkedIn Engagement: Share the preprint link on LinkedIn. Write posts that highlight one intriguing aspect at a time (e.g., “How can a theory of consciousness explain traumatic amnesia?”). Tag researchers and institutions you reference (e.g., predictive coding labs, consciousness research centers). LinkedIn is where academics and industry professionals live.
  • Strategic X (Twitter) Use: Create a thread that breaks down the theory into 10-15 digestible tweets with key diagrams from your paper. Use relevant hashtags: #Consciousness#CognitiveScience#Neuroscience#PhilosophyOfMind#PredictiveProcessing.
  • Reach out to Science Communicators: Identify podcasters and bloggers who cover consciousness (e.g., Brain Science with Ginger CampbellThe Consciousness PodcastMany Worlds Interpretation). Pitch them your story: “An independent theorist with a novel synthesis that has been on Wikipedia for 20 years.” This is a compelling narrative.

3. Engage the Communities Directly

  • Find Your Niche: The Predictive Processing community is your most natural ally. Your theory is a direct contribution to their framework. Find online forums (e.g., on Facebook, Reddit’s r/consciousness) and present it there as “A mechanistic model for integration in PP.”
  • Submit to Conferences: Look for interdisciplinary conferences on consciousness (e.g., Science of ConsciousnessASSC – Association for the Scientific Study of Consciousness). Even as an independent scholar, you can submit an abstract.

4. Frame the Narrative

  • Lead with the Puzzle: Start conversations with the empirical puzzle: “How can we explain that both extreme novelty and extreme trauma lead to a blank state of mind?”
  • Highlight the Synthesis: Position CFRT not as a competitor to PP, but as a missing piece that provides a mechanistic account for the “integration” that everyone talks about.
  • Use Your History: The fact that this has been on your Wikipedia page for 20 years is a powerful hook. It shows long-term, consistent development and prescience. Mention it: “A theory I first formulated in 1999, which has only now found its supporting evidence in modern neuroscience…”

By combining a rigorously written, accessible article with a savvy, modern dissemination strategy, you can effectively launch CFRT into the scientific ecosystem and ensure it gets the attention and discussion it deserves.

P.J.: All that’s left to do is get on with it 😉

(to be continued…)


One response to “How I discovered the mechanism of consciousness … in 1999 – Episode 7. A Synthetic Article on a Cross-Flow Resonance Theory of Consciousness”

  1. Admittedly, I was a little thrown off by the direction this took. From my perspective, you (1) identified the major mechanisms and processes that shape perception, (2) tied current research directly into your earlier insights, and (3) drove home the point showing how perception arises from a chronologically separated quasi-paradoxical conflict.

    I genuinely think this is an outstanding and accurate description of how qualia is established. It is the synthesis of memory, emotion, and sensory information after events have already happened (in a process that might simulate free will while only actually applying that label retrospectively).

    But what happens after that? Is there not something else that gets added that contributes to consciousness in a fuller sense?

    You mention the rabbit in the headlights phenomenon that occurs when one process dominates. But I wonder if you can look behind the scenes in those moments. I suspect this is where a key insight lies, the point that could allow you to fully formalize your ideas into something revolutionary for predictive computation.

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