TL;DR:
ICT treats matter as fixed information, consciousness as the rate of informational change, and time as the structuring of this change.
The model unexpectedly drew interest from researchers in information physics (feedback below) and includes three concrete falsifiable experiments.

1. Core Idea

ICT is based on three relations:

1. Matter = fixed information
   M = I_fixed

2. Consciousness = rate of informational change in time
   C is proportional to dI/dT
   (meaning: consciousness grows when informational updates per unit time increase)

3. Reality = interaction of stable and flowing information
   R = function(I_fixed, dI/dT)

This aligns with:

Landauer’s limit (energy cost of changing information)

Friston’s free-energy principle (entropy/information gradients)

Bekenstein bounds (informational density limits)

integrated-information ideas (but without assuming a biological substrate)

Key shift:
Information is not an abstraction — it is the actual substrate of physics.

1. Time as an informational process

In ICT, time is defined as:

“The transition of potential information into structured experience.”

This connects:

subjective/phenomenological time

physical/relativistic time

computational/informational time

Consciousness shapes this transition — creating a local arrow of time through patterns of information change.

1. Experimental roadmap (all falsifiable)

Experiment 1 — C ∝ dI/dT (neuroenergetic test)

Task: multilevel oddball or sequence-learning with strict entropy control.
Measurements: EEG or MEG + metabolic markers.
Prediction: higher informational update-rate (dI/dT) increases both energetic cost and long-range neural integration.

Experiment 2 — R = f(I) (“structure without energy”)

Equal power input, but different informational structure:
compressible vs pseudorandom signals, in sensory streams or light patterns.
Prediction: informational form changes neural / behavioral / physical outcomes, even when energy is identical.

Experiment 3 — M = I_fixed (energy of fixation)

Measure energy thresholds for stable information across substrates:
DRAM, Flash, PCM/memristors, spintronics, and possibly neural cultures.
Prediction: matter behaves as stabilized information with substrate-dependent fixation thresholds.

1. External feedback

A researcher specializing in information physics and the nature of time — background:

MSU’s “Institute for Time Nature Explorations”

electrical engineering

information science

systemic research

interdisciplinary time studies

left a detailed review on Academia.edu.

Key excerpts:

"The author proposes an interesting approach to the relationship between matter, consciousness and information, incorporating the complex concept of time."

"'Matter as fixed information' opens a path toward an information physics of consciousness."

"The experimental framework is clear and promising."

— Irina L. Zerchaninova, researcher in information physics & time studies

1. Why posting on Beehaw

ICT sits at the intersection of:

physics

computation

information theory

philosophy of mind

AGI research

This is an early-stage but testable model.
Technical critique is welcome.

Links

Preprint (equations + experimental criteria):
https://www.academia.edu/s/8924eff666

Main publication (open access):
https://doi.org/10.5281/zenodo.17584783

PDF:
https://www.academia.edu/144946662