Neurobiological Correlates of Classical and Quantum Neural Information Processing from the Perspective of Autism

  • Antonio CassellaEmail author
Reference work entry


The odd performance of autistic individuals in neuropsychological tests and anomalies in their discourse suggest that when nonautistic individuals face a problem, their minds enter quantum coherence: The legitimacy of involved prototypical schemata – guarded by classical neural computing, sequence, or the first attention – is suspended by quantum neural computing, simultaneity, or the second attention; and the consequences of conflicting variants of the schemata on hold are simulated in cerebellar microcomplexes. Within quantum decoherence: The second attention discerns a promising variant (learning); and the first attention will validate the new schema and shield it (memory) against illegitimate change if unfit mistakes are eradicated or amusing mistakes are introduced. In this chapter, psychological aspects of the quantum jump from coherence to decoherence (which autistics cannot follow), damage observed in autopsied brains of autistic subjects, and tertiary research on the cerebellum lead to heuristics on the neurobiological correlates of classical and quantum neural computing.


Purkinje Cell Inverse Model Virtual Object Cerebellar Nucleus Neural Computing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Albus JS. Theory of cerebellar function. Mathem Biosci. 1971;10:25–61.CrossRefGoogle Scholar
  2. Baron-Cohen S. Mindblindness. Cambridge, MA: MIT Press; 1995.Google Scholar
  3. Baron-Cohen S, Leslie A, Frith U. Does the autistic child have a “theory of mind”? Cognition. 1985;21:37–46.PubMedCrossRefGoogle Scholar
  4. Bauman ML, Kemper TL. Structural brain anatomy in autism: what is the evidence? In: Bauman ML, Kemper TL, editors. The neurobiology of autism. Baltimore: Johns Hopkins University Press; 2006. p. 121–35.Google Scholar
  5. Bostan AC, Dum RP, Strick PL. The basal ganglia communicate with the cerebellum. Proc Natl Acad Sci USA. 2010;107(18):8452–6.PubMedCrossRefGoogle Scholar
  6. Cassella A. El desarrollo de la inteligencia social: aportes del autismo. Maracaibo: Ediluz; 2002.Google Scholar
  7. Cassella A. Readjusting what we know with what we imagine. In: Allen R, editor. Human ecology economics: a framework for global sustainability. London: Routledge; 2008. p. 230–57.Google Scholar
  8. Cassella A. Autism and the interplay of deterministic and quantum information processing in the act of creation. Neuroquantology. 2011;9(2):271–87.Google Scholar
  9. Cassella A. Fundamentos cognitivos y semióticos de la creatividad: aportes del autismo. Tesis Doctoral. Caracas, Venezuela: UNESR; 2000.Google Scholar
  10. Cassella A. Self-other differentiation and self-other integration from the perspectives of language development and autism. Master’s thesis, Harvard U; 1997.Google Scholar
  11. Courchesne E, Lincoln AJ, Townsend JP, James HE, Akshoomoff NA, Saitoh O, Yeung-C-Courchesne R, Egaas B, Press GA, Haas RH, Murakami JW, Schreibman L. A new finding: Impairment in shifting attention in autistic and cerebellar patients. In: Broman SH, Grafman J, editors. Atypical cognitive deficits in developmental disorders: Implications for brain function. Hillsdale, NJ: Lawrence Erlbaum; 1994. p. 101–137.Google Scholar
  12. Feynman RP. The strange theory of light and matter. Princeton: Princeton University Press; 1985.Google Scholar
  13. Icke V. The force of symmetry. Cambridge: Cambridge University Press; 1995.CrossRefGoogle Scholar
  14. Ito M. New concepts in cerebellar function. Rev Neurol. 1993;149(11):596–9.PubMedGoogle Scholar
  15. Ito M. Control of mental activities by internal models in the cerebellum. Nat Neurosci. 2008;9:304–13.CrossRefGoogle Scholar
  16. Ito M. The cerebellum: brain for an implicit self. Upper Saddle River: Peared; 2011.Google Scholar
  17. Ito M, Sakurai M, Tongroach P. Climbing fibre induced depression of both mossy fiber responsiveness and glutamate sensitivity of cerebellar Purkinje cells. J Physiol Lond. 1982;324:113–34.PubMedGoogle Scholar
  18. Johnson M. The development of visual attention: a cognitive neuroscience perspective. In: Cazzaniga MS, editor. The cognitive neurosciences. Cambridge, MA: MIT Press; 1995. p. 735–47.Google Scholar
  19. Landry R, Bryson SB. Impaired disengagement of attention in young children with autism. J Child Psychol Psych. 2004;45(6):115–1122.CrossRefGoogle Scholar
  20. Lloyd S. Programming the universe. New York: Alfred E. Knopf; 2006.Google Scholar
  21. Perner J. Understanding the representational mind. Cambridge, MA: MIT Press; 1991.Google Scholar
  22. Rodier PM, Arndt TL. The brainstem in autism. In: Bauman ML, Kemper TL, editors. The neurobiology of autism. Baltimore: Johns Hopkins University Press; 2006. p. 136–49.Google Scholar
  23. Sears LL, Finn PR, Steinmetz JE. Abnormal classical eye-blink conditioning in autism. J Autism Dev Disord. 1994;24(6):737–51.PubMedCrossRefGoogle Scholar
  24. Sears LL, Vest C, Mohamed S, et al. An MRI study of the basal ganglia in autism. Prog Neuro Psycho Psychoph. 1999;23(4):713–24.CrossRefGoogle Scholar
  25. Stanton ME, Erwin RJ, Rush AN, et al. Eye blink conditioning in autism and a developmental rodent model. Neurotoxicol Teratol. 2001;23:297.Google Scholar
  26. Zaitchik D. When representations conflict with reality: the preschooler’s problem with false beliefs and “false” photographs. Cognition. 1990;35:41–68.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Mérida State Institute of Research of Social Intelligence and Autism (IMERISYA)Zea MéridaVenezuela

Personalised recommendations