Mesmer Prism

Simulated psychedelic vision

Deep Dream

Deep Dream is the project where I am trying to say, as precisely as possible, what hallucination-machine systems do and do not simulate. It sits between machine vision, VR, cyberdelic design, community replication cultures, and the broader problem of treating altered perception as something that can be modeled without flattening it into hype.

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Direction

What the project is trying to clarify

The useful question is not whether DeepDream recreates “the psychedelic state” wholesale. The useful question is what kind of similarity is being claimed: phenomenological resemblance, questionnaire overlap, partial neural convergence, a controllable stimulus class for experiments, or simply a historically interesting cyberdelic design move. Those are different claims and the field often slides between them too quickly.

This project therefore treats simulation as graded. It tracks the lineage from Inceptionism and community video-stabilization hacks into the Hallucination Machine literature, then asks where the evidence is strongest, where stimulus provenance or rights issues matter, and which mismatch cases remain unresolved.

Active lanes

  • Historical lineage from Google DeepDream to VR hallucination platforms
  • Phenomenological fidelity and questionnaire-matching claims
  • EEG, entropy, and cognitive-flexibility results under DeepDream exposure
  • Media provenance, replication culture, and stimulus-pipeline transparency

Connected projects

Boundary

What keeps the line useful

Deep Dream becomes stronger when it refuses the all-or-nothing trap. It is already a valuable model of altered visual phenomenology, a concrete cyberdelic design history, and a test case for how machine priors get projected back onto sensory input. It does not need to claim equivalence to pharmacological psychedelics in order to matter.

The project is also a reminder that stimulus engineering is part of the method. Parameter choices, stabilization pipelines, optical-flow inheritance, and rights provenance all shape what kind of hallucination object is actually being studied.

Current public emphasis

  • Graded simulation claims instead of totalizing rhetoric
  • Explicit separation of fidelity, outcome, and provenance questions
  • Cyberdelics as a historical and technical design line

Reference Surface

Current references

These are the main anchors shaping the current Deep Dream line.

Core simulation lineage

  • Mordvintsev, Olah, and Tyka. "Inceptionism: Going Deeper into Neural Networks." Google Research blog (2015).
  • Suzuki et al. "A Deep-Dream Virtual Reality Platform for Studying Altered Perceptual Phenomenology." Scientific Reports (2017).
  • Greco et al. "Increased Entropic Brain Dynamics during DeepDream-Induced Altered Perceptual Phenomenology." Entropy (2021).
  • Rastelli et al. "Simulated Visual Hallucinations in Virtual Reality Enhance Cognitive Flexibility." Scientific Reports (2022).
  • Suzuki, Seth, and Schwartzman. "Modelling Phenomenological Differences in Aetiologically Distinct Visual Hallucinations Using Deep Neural Networks." Frontiers in Human Neuroscience (2024).

Cyberdelics, phenomenology, and comparison

  • Hartogsohn. "Cyberdelics in Context: On the Prospects and Challenges of Mind-Manifesting Technologies." Frontiers in Psychology (2023).
  • Aqil et al. "More than Meets the Eye: The Role of Sensory Dimensions in Psychedelic Brain Dynamics, Experience, and Therapeutics." (2023).
  • Hewitt et al. "Stroboscopically Induced Visual Hallucinations: Historical, Phenomenological, and Neurobiological Perspectives." Neuroscience of Consciousness (2025).
  • Smith and Warner. "Cyberdelics: Context Engineering Psychedelics for Altered Traits." EVA London 2022.
  • Kaup et al. "Psychedelic Replications in Virtual Reality and their Potential as a Therapeutic Instrument: An Open-Label Feasibility Study." Frontiers in Psychiatry (2023).