Verification of Source Activations in a 3D Brain Model Using ‘CLEVER’ Algorithm for Mental Arithmetic Conditions

IF 1.8 Q4 NEUROSCIENCES
Jeenal Rambhia, Rajendra Sutar
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引用次数: 0

Abstract

Background: Living conditions are becoming challenging day by day. Mental stress on individuals is increasing due to multiple reasons. As mental stress is a major cause of mental illness, it must be detected at the earliest to prevent serious conditions such as depression and anxiety. Purpose: The focus of this study is to detect the exact location of the source which causes such damage. In this article, we analyse the mental conditions of subjects under a workload of performing mental arithmetic calculations for various frequency bands and plot the topography to understand the areas of active potentials. Methods: We propose a Novel Cluster Ensemble Verifier (CLEVER) algorithm, which combines two different techniques: clustering and source localisation. The proposed algorithm is highly efficient in identifying the exact location of the source. It is seen that the topographic plots of the independent component analysis (ICA), which has the maximum percentage of relative variance, correlates to the cluster generated. We are able to give the percentage-wise contribution of every component which is responsible for brain source activation with less time complexity. Results: Out of 72 subjects, in 67 subjects, 299 out of 433 components originate from the occipital and parietal areas of the brain with a maximum power of 43.5 µv 2 . As an example, the relative variance of one component is found to be contributing up to 74.03% to source activations. Clusters show similarity across the subjects in the parietal and occipital areas of the brain. The dataset used for experimentation is EEGMAT from Physionet’s repository. The computation time for the algorithms is 17.6 ± 3.2 minutes. Conclusion: Findings show that during mental arithmetic calculations, both occipital and parietal areas of the brain are involved. As the data is acquired by orally mentioning the mathematical problem, subjects tend to visualise the numbers while finding the solution, which is reflected in the occipital area of the brain. CLEVER algorithm verifies the origin of the activity in the occipital and parietal areas of the brain.
使用 "CLEVER "算法验证三维脑模型中的源激活,以确定心算条件
背景介绍生活条件日趋严峻。由于多种原因,个人的精神压力越来越大。由于精神压力是导致精神疾病的主要原因,因此必须尽早发现精神压力,以预防抑郁症和焦虑症等严重疾病。目的:本研究的重点是检测造成此类损害的源头的确切位置。在本文中,我们分析了受试者在不同频段进行心算的工作量下的精神状况,并绘制了地形图,以了解活跃电位的区域。方法:我们提出了一种新颖的聚类集合验证器(CLEVER)算法,它结合了两种不同的技术:聚类和源定位。所提出的算法在确定源的确切位置方面效率很高。从独立成分分析(ICA)的地形图可以看出,相对方差百分比最大的独立成分分析与生成的聚类相关。我们能够以较少的时间复杂度给出每个成分对脑源激活的贡献百分比。结果在 72 个受试者中,67 个受试者的 433 个成分中有 299 个来自大脑枕叶和顶叶区域,最大功率为 43.5 µv 2。例如,一个成分的相对方差对源激活的贡献率高达 74.03%。在大脑顶叶和枕叶区域,不同受试者的集群显示出相似性。实验使用的数据集是 Physionet 数据库中的 EEGMAT。算法的计算时间为 17.6 ± 3.2 分钟。结论研究结果表明,在心算过程中,大脑的枕叶区和顶叶区都参与了计算。由于数据是通过口头提及数学问题获得的,受试者在寻找解决方案时倾向于将数字视觉化,这反映在大脑的枕叶区。CLEVER 算法可验证大脑枕叶区和顶叶区活动的起源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Annals of Neurosciences
Annals of Neurosciences NEUROSCIENCES-
CiteScore
2.40
自引率
0.00%
发文量
39
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