Dream Synchronization Method

Overview

The Banchenko's Mnemonic Dream Synchronization Method is a groundbreaking research that investigates the potential for dream synchronization, including lucid dreams, among a group of participants using the concepts of "memes" and "tag-memes" within the framework of the Banchenko Algorithm.

Publication Details

Journal: International Internal Medicine Journal, Volume 2, Issue 1, 2024
Published: January 29, 2024

Authors:

Lord Denis Yurievich Banchenko
Mykhailo Mykhailovich Kapustin
Irina Nikolaevna Bukach
Anna Sergeevna Budanova
Tatiana Viktorovna Burilova
Olena Davletkhanovna Mutsalkhanova-Yushchenko
Ilya Sergeevich Blohin
Shishkin Lev Konstantinovich

Key Findings

✅ Demonstrated synchronization across 8 geographically separated participants
✅ Shared dream elements emerged even when participants were in different locations
✅ Wakeful-state activities influence dream content
✅ AI model validation - Kapustin's model successfully identified dream correspondences

Methodology

Core Concept: Memes and Tag-Memes

The research uses the theory of memes and tag-memes to understand how dream elements can be synchronized across participants:

Memes: Shared dream elements or themes
Tag-memes: Specific markers or identifiers in dreams
Synchronization: Emergence of similar elements in participants' dreams

Integration with Banchenko Algorithm

The dream synchronization method builds upon the Banchenko Algorithm components:

Special Diet - Avoiding sugar, consuming spirulina and cocoa
Daily Routine - Mandatory compliance with work and rest regimen
Breathing Practices - Wim Hof method
Physical Activity - Walking backwards practice
Arm Exercises - Sequential twisting and opening of crossed hands' fingers
Visual Practices - Dream visualization while awake
Dream Diary - Handwritten dream journaling
10 Short Actions - Reality check practice

AI Model: Arcanum12th

Developed by Mykhailo Kapustin under the direction of Denis Banchenko:

Combines tens of thousands of dream interpretations
Advanced analysis and interpretation abilities
Successfully identifies correlations in participants' dreams
Result of years of research by international team

Research Results

The study demonstrated that:

Wakeful-state synchronization activities can influence dream content
Shared "memes" and "tag-memes" emerge in participants' dreams
Synchronization occurs even when participants are geographically separated
The AI model effectively identifies dream correspondences

Applications

Research Applications

Understanding collective unconscious mechanisms
Studying non-local consciousness phenomena
Exploring dream telepathy and synchronization

GFS Integration

Enables systematic collection of synchronized dream data
Provides foundation for collective dream analysis
Supports forecasting through shared dream elements

Detailed Documentation

For comprehensive research details, see: