Bianca Avanzo — The Root Frequency Theory

Root Frequency

Theory

What sustains a coherent sense of self? Root Frequency Theory proposes an integrative framework for understanding how brain, body, and lived experience might remain aligned across time, and what conditions could disrupt this coherence.

Explore the framework
The Paper

Theoretical foundations, key gaps in consciousness research, and the C0–C4 multiscale architecture.

M-RFT Coherence Metric

Formalization of the metric and proposed study designs for investigating cross-scale coordination.

Expected Outcomes

Potential implications for psychopathology research and invitation for academic collaboration.

Why does this matter?

Contemporary neuroscience has made major advances in characterizing neural dynamics1, intrinsic self-related activity2, and the organization of large-scale brain networks, along with their associated vulnerabilities3,4,5,6,7. Yet these domains are often investigated separately, leaving open a critical question: could multiscale alignment play a key role in understanding the maintenance and potential perturbation of lived-experience continuity?

This question becomes increasingly relevant in today's information-dense and cognitively demanding environments. Within this context, Root Frequency Theory considers how cognitive information overload may impact cross-level coordination. We hypothesize that under such sustained load, the system's integrative capacity may be reduced8, thereby placing increased demands on predictive regulation1.

The proposed M-RFT metric aims to quantify variations in cross-scale alignment and examine whether such variations help predict emerging patterns of experiential fragmentation across both clinical and everyday contexts3,7.

Read the paper →M-RFT MetricExpected Outcomes

References

  1. Friston, K. (2010). The free-energy principle: A unified brain theory? Nature Reviews Neuroscience, 11(2), 127–138. https://doi.org/10.1038/nrn2787
  2. Northoff, G. (2016). Neuro-philosophy and the healthy mind: Learning from the unwell brain. W. W. Norton & Company.
  3. Menon, V. (2011). Large-scale brain networks and psychopathology: A unifying triple network model. Trends in Cognitive Sciences, 15(10), 483–506. https://doi.org/10.1016/j.tics.2011.08.003
  4. Seth, A. K., Dienes, Z., Cleeremans, A., Overgaard, M., & Pessoa, L. (2008). Measuring consciousness: Relating behavioural and neurophysiological approaches. Trends in Cognitive Sciences, 12(8), 314–321. https://doi.org/10.1016/j.tics.2008.04.008
  5. Edelman, G. M., Gally, J. A., & Baars, B. J. (2011). Biology of consciousness. Frontiers in Psychology, 2, 4. https://doi.org/10.3389/fpsyg.2011.00004
  6. Cleeremans, A. (2011). The radical plasticity thesis: How the brain learns to be conscious. Frontiers in Psychology, 2, 86. https://doi.org/10.3389/fpsyg.2011.00086
  7. Sapolsky, R. M. (2004). Why zebras don't get ulcers (3rd ed.). Henry Holt.
  8. Tononi, G., Boly, M., Massimini, M., & Koch, C. (2016). Integrated information theory: From consciousness to its physical substrate. Nature Reviews Neuroscience, 17, 450–461. https://doi.org/10.1038/nrn.2016.44