Probabilistic pathway representation of cognitive information

被引:23
|
作者
Khrennikov, A [1 ]
机构
[1] Univ Vaxjo, Int Ctr Math Modeling Phys & Cognit Sci, S-35195 Vaxjo, Sweden
关键词
mental space; mental dynamics; body-mind field; materialistic axiom; metal diffusion; psychological time;
D O I
10.1016/j.jtbi.2004.07.015
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
We present for mental processes the program of mathematical mapping which has been successfully realized for physical processes. We emphasize that our project is not about mathematical simulation of the brain's functioning as a complex physical system, i.e., mapping of physical and chemical processes in the brain on mathematical spaces. The project is about mapping of purely mental processes on mathematical spaces. We present various arguments-philosophic, mathematical, information, and neurophysiological-in favor of the p-adic model of mental space. p-adic spaces have structures of hierarchic trees and in our model such a tree hierarchy is considered as an image of neuronal hierarchy. Hierarchic neural pathways are considered as fundamental units of information processing. As neural pathways can go through the whole body, the mental space is produced by the whole neural system. Finally, we develop the probabilistic neural pathway model in that mental states are represented by probability distributions on mental space. (C) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码:597 / 613
页数:17
相关论文
共 50 条
  • [1] Representation of incomplete probabilistic information
    Baudrit, C
    Dubois, D
    Fargier, H
    SOFT METHODOLOGY AND RANDOM INFORMATION SYSTEMS, 2004, : 149 - 156
  • [2] Neural representation of probabilistic information
    Barber, MJ
    Clark, JW
    Anderson, CH
    NEURAL COMPUTATION, 2003, 15 (08) : 1843 - 1864
  • [3] Representation of Uncertainty with Information and Probabilistic Information Granules
    Manish Aggarwal
    International Journal of Fuzzy Systems, 2017, 19 : 1617 - 1634
  • [4] Representation of Uncertainty with Information and Probabilistic Information Granules
    Aggarwal, Manish
    INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, 2017, 19 (05) : 1617 - 1634
  • [5] Representation and extraction of information by probabilistic logic
    Rodder, W
    KernIsberner, G
    INFORMATION SYSTEMS, 1996, 21 (08) : 637 - 652
  • [6] Towards a multilevel cognitive probabilistic representation of space
    Tapus, A
    Vasudevan, S
    Siegwart, R
    Human Vision and Electronic Imaging X, 2005, 5666 : 39 - 48
  • [7] Towards a cognitive probabilistic representation of space for mobile robots
    Vasudevan, Shrihari
    Nguyen, Viet
    Siegwart, Roland
    2006 IEEE INTERNATIONAL CONFERENCE ON INFORMATION ACQUISITION, VOLS 1 AND 2, CONFERENCE PROCEEDINGS, 2006, : 353 - 359
  • [8] Information Representation and Processing in Cognitive Nanoinformatics
    Shakhnov, Vadim
    Rezchikova, Elena
    Zinchenko, Lyudmila
    Kosolapov, Ilya
    2014 5TH IEEE CONFERENCE ON COGNITIVE INFOCOMMUNICATIONS (COGINFOCOM), 2014, : 43 - 47
  • [9] DOCUMENT REPRESENTATION IN PROBABILISTIC MODELS OF INFORMATION-RETRIEVAL
    CROFT, WB
    JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE, 1981, 32 (06): : 451 - 457
  • [10] Affective and Cognitive Factors Influencing Sensitivity to Probabilistic Information
    Tyszka, Tadeusz
    Sawicki, Przemyslaw
    RISK ANALYSIS, 2011, 31 (11) : 1832 - 1845