Issues

 / 

2023

 / 

December

  

Reviews of topical problems


Stochastic processes in the brain's neural network and their impact on perception and decision-making

  a,   b, c
a Center for Biomedical Technology Technical University of Madrid, Campus Montegancedo, Pozuelo de Alarcón, Madrid, 28223, Spain
b Baltic Center for Neurotechnology and Artificial Intelligence, Immanuel Kant Baltic Federal University, Aleksandr Nevskii str. 14, Kaliningrad, 236041, Russian Federation
c Saratov State Medical University named after V. I. Razumovsky, Bolshaya Kazachya str. 112, Saratov, 410012, Russian Federation

The article deals with the influence of stochastic dynamics of the brain's neural ensembles on the perception and processing of sensory information, as well as on decision-making based on it. The review considers sources of noise in the nervous system during sensory information processing, as well as some nervous system strategies of compensating for or taking into account stochastic processes. Experiments and mathemat„ical models are discussed in which stochastic brain dynamics begins to play a significant role in the perception of sensory information. Particular attention is paid to brain noise research paradigms such as the perception of weak stimuli close to the sensitivity threshold and bistable ambiguous stimuli. Methods for assessing brain noise using both psychophysical experiments and direct analysis of neuroimaging data are described. Finally, some issues in applying the concept of stochastic brain dynamics to problems in the biomedical diagnosis of various neurological diseases are considered.

Fulltext pdf (1.9 MB)
Fulltext is also available at DOI: 10.3367/UFNe.2022.12.039309
Keywords: neural networks, brain, stochastic process, perception, mathematical models, psychophysics, stochastic/coherence resonance, electroencephalogram and magnetoencephalogram analysis
PACS: 05.45.−a, 87.19.L−, 87.85.−d (all)
DOI: 10.3367/UFNe.2022.12.039309
URL: https://ufn.ru/en/articles/2023/12/c/
001172931200004
2-s2.0-85177602649
2023PhyU...66.1224P
Citation: Pisarchik A N, Hramov A E "Stochastic processes in the brain's neural network and their impact on perception and decision-making" Phys. Usp. 66 1224–1247 (2023)
BibTexBibNote ® (generic)BibNote ® (RIS)MedlineRefWorks

Received: 8th, December 2022, 27th, December 2022

Оригинал: Писарчик А Н, Храмов А Е «Стохастические процессы в нейронной сети головного мозга и их влияние на восприятие и принятие решений» УФН 193 1298–1324 (2023); DOI: 10.3367/UFNr.2022.12.039309

References (224) Cited by (2) Similar articles (20) ↓

  1. A.E. Hramov, N.S. Frolov et alFunctional networks of the brain: from connectivity restoration to dynamic integrationPhys. Usp. 64 584–616 (2021)
  2. A.N. Pavlov, A.E. Hramov et alWavelet analysis in neurodynamicsPhys. Usp. 55 845–875 (2012)
  3. O.V. Maslennikov, M.M. Pugavko et alNonlinear dynamics and machine learning of recurrent spiking neural networksPhys. Usp. 65 1020–1038 (2022)
  4. M.I. Rabinovich, M.K. Muezzinoglu “Nonlinear dynamics of the brain: emotion and cognitionPhys. Usp. 53 357–372 (2010)
  5. A.A. Koronovskii, O.I. Moskalenko, A.E. Hramov “On the use of chaotic synchronization for secure communicationPhys. Usp. 52 1213–1238 (2009)
  6. V.V. Klinshov, V.I. Nekorkin “Synchronization of delay-coupled oscillator networksPhys. Usp. 56 1217–1229 (2013)
  7. V.S. Anishchenko, A.B. Neiman et alStochastic resonance: noise-enhanced orderPhys. Usp. 42 7–36 (1999)
  8. V.S. Anishchenko, S.V. Astakhov “Poincaré recurrence theory and its applications to nonlinear physicsPhys. Usp. 56 955–972 (2013)
  9. M.V. Kalashnik, M.V. Kurgansky, O.G. Chkhetiani “Baroclinic instability in geophysical fluid dynamicsPhys. Usp. 65 1039–1070 (2022)
  10. L.V. Doronina-Amitonova, I.V. Fedotov et alNeurophotonics: optical methods to study and control the brainPhys. Usp. 58 345–364 (2015)
  11. A.B. Medvinskii, S.V. Petrovskii et alSpatio-temporal pattern formation, fractals, and chaos in conceptual ecological models as applied to coupled plankton-fish dynamicsPhys. Usp. 45 27–57 (2002)
  12. O.V. Maslennikov, V.I. Nekorkin “Adaptive dynamical networksPhys. Usp. 60 694–704 (2017)
  13. V.I. Klyatskin “Integral characteristics: a key to understanding structure formation in stochastic dynamic systemsPhys. Usp. 54 441–464 (2011)
  14. S.P. Kuznetsov “Dynamical chaos and uniformly hyperbolic attractors: from mathematics to physicsPhys. Usp. 54 119–144 (2011)
  15. A. Loskutov “Fascination of chaosPhys. Usp. 53 1257–1280 (2010)
  16. V.S. Anishchenko, T.E. Vadivasova et alStatistical properties of dynamical chaosPhys. Usp. 48 151–166 (2005)
  17. G.N. Borisyuk, R.M. Borisyuk et alModels of neural dynamics in brain information processing — the developments of ’the decade’Phys. Usp. 45 1073–1095 (2002)
  18. A.V. Slunyaev, D.E. Pelinovsky, E.N. Pelinovsky “Rogue waves in the sea: observations, physics, and mathematicsPhys. Usp. 66 148–172 (2023)
  19. G.I. Strelkova, V.S. Anishchenko “Spatio-temporal structures in ensembles of coupled chaotic systemsPhys. Usp. 63 145–161 (2020)
  20. A.A. Makarov, A.L. Malinovsky, E.A. Ryabov “Intramolecular vibrational redistribution: from high-resolution spectra to real-time dynamicsPhys. Usp. 55 977–1007 (2012)

The list is formed automatically.

© 1918–2024 Uspekhi Fizicheskikh Nauk
Email: ufn@ufn.ru Editorial office contacts About the journal Terms and conditions