Holographic Memory: A Novel Model of Information Processing by Neuronal Microcircuits

  • Alexey RedozubovEmail author
Part of the Springer Series in Cognitive and Neural Systems book series (SSCNS, volume 11)


In the proposed model, each cortical minicolumn possesses a complete copy of the memory characteristic of the entire cortical zone to which it belongs. Hence, the cortex has holographic properties, where each fragment of an information carrier contains not just a part of the information but a complete copy. It is argued that each minicolumn encodes the new information using its own interpretation. Such transcoding is equivalent to considering the source information in a particular context. The model suggests that the cortex zone is a space of possible contexts for interpretation. The presence of a full copy of the memory at each minicolumn allows to determine which context is most suitable for interpreting the current information. Possible biological mechanisms are discussed that could implement the model components, including information processing algorithms that enable high computing power.


Holographic memory Microcircuits Information waves Hippocampus Meaning of information Membrane receptors Cluster of receptors Cerebral cortex Dendrites Combination of neurotransmitters 



The author expresses his deep gratitude to Ioan Opris, Dmitry Shabanov and Mikhail Lebedev for the constructive discussion and assistance in the preparation and translation of this article.


  1. Bloom BH (1970) Space/time trade-offs in hash coding with allowable errors. Commun ACM Т 13(7):422–426CrossRefGoogle Scholar
  2. Bondy CA, Whitnall MH, Brady LS, Gainer H (1989) Coexisting peptides in hypothalamic neuroendocrine systems: some functional implications. Cell Mol Neurobiol 9:427–446CrossRefPubMedGoogle Scholar
  3. Braitenberg V, Schuz A (1998) Cortex: statistics and geometry of neuronal connectivity, 2nd edn. Springer, BerlinCrossRefGoogle Scholar
  4. Dunlap К, Holz GG, Rane SG (1987) G proteins as regulators of ion channel function. Trends Neurosci 10:244–247CrossRefGoogle Scholar
  5. Fields RD, Stevens-Graham B (2002) New insights into neuron-glia communication. Science 298:556–562CrossRefPubMedPubMedCentralGoogle Scholar
  6. Fukushima K (1980) Neocognitron: a self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biol Cybern 36(4):193–202CrossRefPubMedGoogle Scholar
  7. Gabor D (1948) A new microscopic principle. Nature 161:777–778CrossRefPubMedGoogle Scholar
  8. Gardner M (1970) Mathematical games – the fantastic combinations of John Conway’s new solitaire game “life”. Sci Am 223:120–123CrossRefGoogle Scholar
  9. Hafting T, Fyhn M, Molden S, Moser MB, Moser EI (2005) Microstructure of a spatial map in the entorhinal cortex. Nature 436:801–806CrossRefPubMedGoogle Scholar
  10. Halassa MM, Fellin T, Takano H, Dong J-H, Haydon PG (2007) Synaptic islands defined by the territory of a single astrocyte. J Neurosci 27:6473–6477CrossRefPubMedGoogle Scholar
  11. Lebedev M, Opris I (2015) Brain-machine interfaces: from macro- to microcircuits. In: Recent advances on the modular organization of the cortex. Springer, DordrechtGoogle Scholar
  12. LeCun Y, Bengio Y (1995) Convolutional networks for images, speech, and time-series. MIT Press, CambridgeGoogle Scholar
  13. Lundberg JM (1996) Pharmacology of cotransmission in the autonomic nervous system: integrative aspects on amines, neuropeptides, adenosine triphosphate, amino acids and nitric oxide. Pharmacol Rev 48:113–178PubMedGoogle Scholar
  14. MacDonald CJ, Lepage KQ, Eden UT, Eichenbaum H (2011) Hippocampal “time cells” bridge the gap in memory for discontiguous events. Neuron 71:737–749CrossRefPubMedPubMedCentralGoogle Scholar
  15. Minsky M (1974) A framework for representing knowledge, MIT-AI Laboratory Memo 306. Massachusetts Institute of Technology A.I. Laboratory, CambridgeGoogle Scholar
  16. O’Keefe J, Dostrovsky J (1971) The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. Brain Res 34:171–175CrossRefPubMedGoogle Scholar
  17. Petermanna T, Thiagarajana TC, Lebedevb MA, Nicolelisb MAL, Chialvoc DR, Plenz D (2009) Spontaneous cortical activity in awake monkeys composed of neuronal avalanches. Proc Nat Acad Sci 106:37CrossRefGoogle Scholar
  18. Radchenko AN (2007) Information mechanisms of the brain. St. Petersburg: s.nGoogle Scholar
  19. Redozubov A (2016) The logic of consciousness. [Online].
  20. Redozubov A. Programs. [Online]
  21. Scoviille W, Milner B (1957) Loss of recent memory after bilateral hippocampal lesions. J Neurol Neurosurg Psychiatry 20:1CrossRefGoogle Scholar
  22. Von Neumann J, Burks AW (1966) Theory of self-reproducing automata. University of Illinois Press, UrbanaGoogle Scholar
  23. Wilfrid R (1959) Branching dendritic trees and motoneuron membrane resistivity. Exp Neurol 1:491–527CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.St. PetersburgRussia

Personalised recommendations