The emergence of dynamic form through phase relations in dynamical systems

Area of Science:

• Computational Neuroscience
• Visual Perception
• Cognitive Science

Background:

• Theories of visual form struggle with correspondence across time and space.
• Gregory Bateson's concept of knowledge from relations among flows of difference provides a foundation.

Purpose of the Study:

• To propose a computational model explaining visual form emergence.
• To demonstrate how phase relations eliminate the correspondence problem in visual perception.
• To investigate the role of dynamic form in apparent motion.

Main Methods:

• Developed a computational model using Boolean networks and attractor cycles.
• Introduced a second cyclic systemic flow with a controllable frequency.
• Analyzed phase relations between two frequency flows to generate dynamic visual forms.

Main Results:

• The model successfully generates dynamic visual forms from phase relations.
• Apparent motion phenomena are shown to be integral to dynamic form perception.
• The model offers a novel solution to the visual form correspondence problem.

Conclusions:

• Dynamic visual form perception can emerge from the phase relations of multiple difference flows.
• Apparent motion is not an illusion but serves dynamic form perception.
• This model provides a new framework for understanding perceptual organization and moving form.