Fractal geometry, unlike Euclidean geometry, describes patterns that emerge at the boundary of regularity and irregularity—precisely the condition in which natural balancing occurs. In the brain, neural networks form geometric curvatures that, when strained, oscillate dynamically. These oscillations generate fractal-like self-similar patterns, which manifest in the imagery, behaviors, and cognitive processing of the brain.
If neural networks at rest encode memory features, strained networks have the potential to regenerate these features either through direct repetition or by integrating variations that produce novel brain activities. The structural and functional interplay of neural networks follows a fractal pattern, where cognition and emotions emerge as fluctuating yet self-similar constructs within the continuum of brain activity.
This article is a base of the interview between the author and A.I.