Fuzzy-based computational simulations of brain functions – preliminary concept

Author:

Prokopowicz Piotr,Mikołajewski Dariusz

Abstract

AbstractResearch on the computational models of the brain constitutes an important part of the current challenges within computational neuroscience. The current results are not satisfying. Despite the continuous efforts of scientists and clinicians, it is hard to fully explain all the mechanisms of a brain function. Computational models of the brain based on fuzzy logic, including ordered fuzzy numbers, may constitute another breakthrough in the aforementioned area, offering a completing position to the current state of the art. The aim of this paper is to assess the extent to which possible opportunities concerning computational brain models based on fuzzy logic techniques may be exploited both in the area of theoretical and experimental computational neuroscience and in clinical applications, including our own concept. The proposed approach can open a family of novel methods for a more effective and (neuro)biologically reliable brain simulation based on fuzzy logic techniques useful in both basic sciences and applied sciences.

Publisher

Walter de Gruyter GmbH

Subject

Health Informatics,Biochemistry, Genetics and Molecular Biology (miscellaneous),Medicine (miscellaneous),General Computer Science

Reference58 articles.

1. Understanding neurodynamical systems via fuzzy symbolic dynamics;Neural Netw,2010

2. Defuzzification functionals of ordered fuzzy numbers;IEEE Trans Fuzzy Syst,2013

3. Ordered fuzzy numbers;Bull Polish Acad Sci Ser Sci Math,2003

4. Noise in the nervous system;Nat Rev Neurosci,2008

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Modified Euclidean-Canberra blend distance metric for kNN classifier;Intelligent Decision Technologies;2023-05-15

2. Modified Euclidean-Canberra blend distance metric for kNN classifier;Intelligent Decision Technologies;2023-01-16

3. From Neuroimaging to Computational Modeling of Burnout: The Traditional versus the Fuzzy Approach—A Review;Applied Sciences;2022-11-13

4. Fuzzy-based Description of Computational Complexity of Central Nervous Systems;Journal of Telecommunications and Information Technology;2020-09-30

5. OFN-Based Brain Function Modeling;Theory and Applications of Ordered Fuzzy Numbers;2017

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3