HEPOE Theory: High Entropy Predictive Organization Efficiency

There is a newer version of the record available.

Published May 21, 2026 | Version 4
Preprint Open

THE ARCHITECTURE OF IMPEDANCE: Unifying Synaptic Proteins, Nyquist-Shannon Sampling, and P-FIT Bus Resistance in the Autism Spectrum Phenotype

Authors/Creators

  • 1. Independent Researcher

Description

ABSTRACT

Current psychiatric paradigms primarily characterize Autism Spectrum Disorder (ASD) through behavioral observation, resulting in a dualistic gap between molecular genetics and systemic cognitive output. We propose a paradigm shift utilizing the High Entropy Predictive Organization Efficiency (HEPOE) framework to suggest that ASD is not fundamentally a behavioral or developmental deficit, but rather can be conceptualized as an Architecture of Impedance, generating a state of Compulsory Thermodynamic Inefficiency. By integrating the structural decay of post-synaptic density proteins (e.g., SHANK3) with the Nyquist-Shannon sampling theorem, we hypothesize that the core of the ASD phenotype is the inability to compress data at the sensory entry gate (Ωsensory). This uncompressed, high-volume data load is proposed to force the predictive architecture to push raw information through high-resistance white matter pathways defined by the Parieto-Frontal Integration Theory (P-FIT), generating massive network friction (Ωnetwork). We introduce the comprehensive Systemic Friction equation. This framework redefines the varying Support Levels of ASD (Levels 1, 2, and 3) not as static psychological traits, but as the mathematical rate of Predictive Solvency (S(t)) decay. The so-called "social deficits" and rigid routines are thereby reframed as autonomous Entropic Damping protocols, emergent homeostatic attractor states representing the path of least thermodynamic resistance to prevent thermal and metabolic exhaustion in a high-friction neural hardware.

LAY SUMMARY

This study proposes that autism is not a behavioral defect, but a physical difference in how the brain's hardware manages data. Because autistic brains process immense amounts of unfiltered information through high-resistance neural pathways, they rapidly drain their biological energy. Therefore, behaviors like social withdrawal or repetitive movements are not flaws to be cured, but vital survival strategies used to prevent burnout and protect against sensory overload.

Keywords: Autism Spectrum Disorder (ASD). HEPOE Theory. Predictive Solvency. Nyquist-Shannon Sampling. Systemic Friction. P-FIT Bus Resistance. Systemic Impedance. Entropic Damping.

Files

ASD_Brezolin_and_Freitas_v4.pdf

Files (858.2 kB)

Name Size
md5:dfd66a497bd218d6d19fb499b8327c5e
858.2 kB Preview Download

Additional details

Identifiers

URL
https://originalmy.com/bitregistro/9ea73fdfe3c512c8943d2857112e402b4ce168f22a15d8defaa5304323622555
Other
INPI BR 10 2026 003603 0
Other
INPI BR 51 2026 000122 6
Other
INPI BR 51 2026 000781 0

Related works

References
Preprint: 10.5281/ZENODO.18284802 (DOI)

References

  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). doi: https://doi.org/10.1176/appi.books.9780890425596.
  • Astrup, J., Siesjö, B. K., and Symon, L. (1981). Thresholds in cerebral ischemia - the ischemic penumbra. Stroke, 12(6), 723-725. doi: https://doi.org/10.1161/01.str.12.6.723.
  • Bourgeron, T. (2015). From the genetic architecture to synaptic plasticity in autism spectrum disorder. Nature Reviews Neuroscience, 16(9), 551-563. doi: https://doi.org/10.1038/nrn3992.
  • Brezolin, C. L. M., and Freitas, S. B. (2026). THE SENTINEL PHENOTYPE: A Theoretical Bioenergetic and Neurobiological Framework for High-Fidelity Predictive Systems (HEPOE Theory). Zenodo Preprint. doi: https://doi.org/10.5281/zenodo.19324682.
  • Bullmore, E., and Sporns, O. (2012). The economy of brain network organization. Nature Reviews Neuroscience, 13(5), 336-349. https://doi.org/10.1038/nrn3214.
  • Carmassi, C., Palagini, L., Caruso, D., Masci, I., Nobili, L., and Dell'Osso, L. (2019). Systematic Review of Sleep Disturbances and Circadian Sleep Desynchronization in Autism Spectrum Disorder: Toward an Integrative and Comprehensive Model. Frontiers in Psychiatry, 10, 366. doi: https://doi.org/10.3389/fpsyt.2019.00366.
  • Fradkin, Y., Anguera, J. A., Simon, A. J., De Taboada, L., and Steingold, E. (2025). Transcranial photobiomodulation for reducing symptoms of autism spectrum disorder and modulating brain electrophysiology in children aged 2-7: an open label study. Frontiers in Child and Adolescent Psychiatry, 4, 1477839. doi: https://doi.org/10.3389/frcha.2025.1477839.
  • Friston, K. (2010). The free-energy principle: a unified brain theory? Nat. Rev. Neurosci. 11, 127–138. doi: https://doi.org/10.1038/nrn2787.
  • Genuis, S. J., and Bouchard, T. P. (2010). Celiac disease presenting as autism. Journal of Child Neurology, 25(1), 114-119. doi: https://doi.org/10.1177/0883073809336127.
  • Hamilton, C., El Khoury, H., Hamilton, D., Nicklason, F., and Mitrofanis, J. (2022). Lights on for Autism: Exploring Photobiomodulation as an Effective Therapeutic Option. Neurology International, 14(4), 884-893. doi: https://doi.org/10.3390/neurolint14040071.
  • Hossmann, K. A. (1994). Viability thresholds and the penumbra of focal ischemia. Annals of Neurology, 36(4), 557-565. doi: https://doi.org/10.1002/ana.410360404.
  • Hsiao, E. Y., McBride, S. W., Hsien, S., Sharon, G., Hyde, E. R., McCue, T., ... and Mazmanian, S. K. (2013). Microbiota modulate behavioral and physiological abnormalities associated with neurodevelopmental disorders. Cell, 155(7), 1451-1463. doi: https://doi.org/10.1016/j.cell.2013.11.024.
  • Hull, L., Petrides, K. V., Allison, C., Smith, P., Baron-Cohen, S., Lai, M. C., and Mandy, W. (2017). "Putting on My Best Normal": Social camouflaging in adults with autism spectrum conditions. J. Autism Dev. Disord. 47, 2519–2534. doi: https://doi.org/10.1007/s10803-017-3166-5.
  • Jung, R. E., and Haier, R. J. (2007). The parieto-frontal integration theory (P-FIT) of intelligence. Behav. Brain Sci. 30, 135–154. doi: https://doi.org/10.1017/S0140525X0700118X.
  • Just, M. A., Cherkassky, V. L., Keller, T. A., and Minshew, N. J. (2004). Cortical activation and synchronization during sentence comprehension in high-functioning autism: evidence of underconnectivity. Brain, 127(8), 1811-1821. doi: https://doi.org/10.1093/brain/awh199.
  • Lai, M. C., Lombardo, M. V., Ruigrok, A. N., Chakrabarti, B., Auyeung, B., Szatmari, P., ... and Baron-Cohen, S. (2017). Quantifying and exploring camouflaging in men and women with autism. Autism, 21(6), 713-728. https://doi.org/10.1177/1362361316671012.
  • Landauer, R. (1961). Irreversibility and heat generation in the computing process. IBM Journal of Research and Development, 5(3), 183-191. doi: https://doi.org/10.1147/rd.53.0183.
  • Laughlin, S. B., de Ruyter van Steveninck, R. R., and Anderson, J. C. (1998). The metabolic cost of neural information. Nature Neuroscience, 1(1), 36-41. https://doi.org/10.1038/236.
  • Mousain-Bosc, M., Roche, M., Polge, A., Blanc-Niquin, D., Rapin, J. R., and Bali, J. P. (2006). Improvement of neurobehavioral disorders in children supplemented with magnesium-vitamin B6. I. Attention deficit hyperactivity disorders. Magnesium Research, 19(1), 46-52. PMID: 16846100. Available at: https://pubmed.ncbi.nlm.nih.gov/16846100/.
  • Ooi, Y. P., Weng, S. J., Jang, L. Y., Low, L., Seah, J., Teo, S., ... and Fung, D. S. (2015). Omega-3 fatty acids in the management of autism spectrum disorders: findings from an openlabel pilot study in Singapore. European Journal of Clinical Nutrition, 69(8), 969-971. doi: https://doi.org/10.1038/ejcn.2015.28.
  • Pellicano, E., and Burr, D. (2012). When the world becomes 'too real': a Bayesian explanation of autistic perception. Trends in Cognitive Sciences, 16(10), 504-510. https://doi.org/10.1016/j.tics.2012.08.009.
  • Rossignol, D. A., and Frye, R. E. (2012). Mitochondrial dysfunction in autism spectrum disorders: a systematic review and meta-analysis. Molecular Psychiatry, 17(3), 290- 314. doi: https://doi.org/10.1038/mp.2010.136.
  • Rubenstein, J. L., and Merzenich, M. M. (2003). Model of autism: increased ratio of excitation/inhibition in key neural systems. Genes, Brain and Behavior, 2(5), 255-267. doi: https://doi.org/10.1034/j.1601-183X.2003.00037.x.
  • Shannon, C. E. (1948). A mathematical theory of communication. Bell Syst. Tech. J. 27, 379– 423. doi: https://doi.org/10.1002/j.1538-7305.1948.tb01338.x.
  • Südhof, T. C. (2008). Neuroligins and neurexins link synaptic function to cognitive disease. Nature, 455(7215), 903-911. doi: https://doi.org/10.1038/nature07456.
  • Tononi, G., and Cirelli, C. (2014). Sleep and the price of plasticity: from synaptic and cellular homeostasis to memory consolidation and integration. Neuron, 81(1), 12-34. doi: https://doi.org/10.1016/j.neuron.2013.12.025.
  • Vargas, D. L., Nascimbene, C., Krishnan, C., Zimmerman, A. W., and Pardo, C. A. (2005). Neuroglial activation and neuroinflammation in the brain of patients with autism. Annals of Neurology, 57(1), 67-81. doi: https://doi.org/10.1002/ana.20315.
  • Watts, D. J., and Strogatz, S. H. (1998). Collective dynamics of 'small-world' networks. Nature, 393(6684), 440-442. https://doi.org/10.1038/30918.
  • Wilson, E. O. (1998). Consilience: The Unity of Knowledge. New York, NY: Knopf. ISBN: 978-0679450771.
  • Yizhar, O., Fenno, L. E., Prigge, M., Schneider, F., Davidson, T. J., O'Shea, D. J., ... and Deisseroth, K. (2011). Neocortical excitation/inhibition balance in information processing and social dysfunction. Nature, 477(7363), 171-178. doi: https://doi.org/10.1038/nature10360.