Scaling in cognitive performance reflects multiplicative multifractal cascade dynamics

Area of Science:

• Complex systems science
• Cognitive neuroscience
• Theoretical biology

Background:

• Self-organized criticality (SOC) proposes that local interactions generate multi-scaled structures.
• Observed scaling in biology is often attributed to power-law relationships, suggesting homogeneity across scales.
• This homogeneity may oversimplify complex biological processes, masking rich cascade dynamics.

Purpose of the Study:

• To re-evaluate the interpretation of scaling phenomena in biological systems, particularly executive functions.
• To propose an alternative framework to self-organized criticality for understanding biological scaling.
• To highlight the limitations of single power-law models in capturing complex dynamics.

Main Methods:

• Review of recent research on multifractality in executive-function cognitive tasks.
• Analysis of the concept of self-similarity in power-law scaling.
• Theoretical exploration of multiplicative interactions across multiple scales.

Main Results:

• Apparent homogeneity from power-law scaling can be misleading when spanning numerous scales.
• Reducing biological processes to a single power-law relationship neglects intricate cascade dynamics.
• Multifractality in cognitive tasks suggests complex interactions rather than pure criticality.

Conclusions:

• Biological scaling, especially in cognitive functions, is better explained by interactions across multiple scales and fluctuation sizes.
• The concept of self-organized criticality may not be the most fitting explanation for observed biological scaling.
• Future research should focus on multifractal analyses to understand the complexity of biological systems.