Fractals in the nervous system: conceptual implications for theoretical neuroscience

Area of Science:

• Neuroscience
• Complexity Science
• Dynamical Systems Theory

Background:

• Fractals exhibit self-similarity and power-law scaling, properties observed across biological systems.
• The nervous system's complex structure and function may be explained by fractal geometry.
• Self-organized criticality (SOC) is a theoretical framework for understanding complex systems near critical states.

Purpose of the Study:

• To document the widespread presence of fractals in the nervous system.
• To explore the functional implications of fractal geometry in neurodynamics.
• To highlight unresolved questions regarding power-law scaling, self-similarity, and SOC in the nervous system.

Main Methods:

• Review of existing literature on fractal analysis in neuroscience.
• Discussion of theoretical frameworks including allometric scaling and SOC.
• Synthesis of evidence for fractal dynamics in neural processes.

Main Results:

• Fractal patterns are documented at multiple levels of the nervous system.
• Evidence suggests fractal dynamics contribute to the nervous system's adaptability.
• Criticality has emerged as a key concept in neurodynamics.

Conclusions:

• The prevalence of fractals in the nervous system supports their functional significance.
• Further research is essential to elucidate the precise relationships between fractal properties, allometric control, and SOC.
• Understanding these complex dynamics is crucial for advancing neurodynamic research.