A study of different cognitive states for meditators and non-meditators with the use of multiple classification indices derived from the PSD of EEG data and lessons learned about cognitive states and the nature of intelligence in minds and machines.

IF 3.6 4区 医学 Q2 NEUROSCIENCES
Frontiers in Systems Neuroscience Pub Date : 2026-01-23 eCollection Date: 2025-01-01 DOI:10.3389/fnsys.2025.1718733
J J Joshua Davis, Florian Schübeler, Ian J Kirk, Robert Kozma
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引用次数: 0

Abstract

This study explores the layered coherence within human cognition as measured through EEG. Signals were collected from two groups (meditators vs. non-meditators) across six conditions: Meditation, Scrambled Words, Ambiguous Images, Math Mind, Sentences, and Video Watching. We analyzed the EEG data using Shannon Entropy, Pearson's Skewness, Total Power, and Dominant Frequency indices, now taken together, to reveal distinct neurophysiological signatures and a different outcome of hypothesis testing based on one index at a time only. These patterns suggest that cognition is more than merely computational, since it seems to be expressive of deeper experiential states, raising profound questions about the nature of intelligence and whether the human psyche and its experience of meaning, in its different forms, can be meaningfully approached through objective methodologies. Our findings invite a re-examination of scientific inquiry itself, both as a pursuit of mechanistic regularities, and also, holistically, as a means of honoring the subtle interplay between structure and meaning. This is reminiscent of young Carl Friedrich Gauss revealing hidden structure beneath apparent complexity by summing up an arithmetic series with elegant simplicity. This way he reframed a problem through insight rather than brute calculation. If artificial intelligence is to mimic cognition, it must grapple with informational entropy and also with the values and consciousness that give rise to meaning. The entropic balance of EEG signals may offer a window into coherence, yet only a species that is mature enough to honor life, liberty, and the pursuit of deep meaning, should attempt to design artificial "minds." In this convergence of neuroscience and philosophical reflection, we glimpse a deeper imperative: to preserve the truth of what it means to be human in an age increasingly defined by machines.

利用脑电数据PSD衍生的多重分类指标,以及对认知状态和心智与机器智能本质的认识教训,研究冥想者与非冥想者的不同认知状态。
本研究探讨了通过脑电图测量的人类认知的分层一致性。研究人员从两组(冥想者和非冥想者)中收集了六种情况下的信号:冥想、混乱的单词、模糊的图像、数学思维、句子和观看视频。我们使用香农熵、皮尔逊偏度、总功率和主导频率指数分析脑电图数据,现在将它们放在一起,以揭示不同的神经生理特征和一次仅基于一个指标的假设检验的不同结果。这些模式表明,认知不仅仅是计算性的,因为它似乎表达了更深层次的经验状态,提出了关于智力本质的深刻问题,以及人类心理及其不同形式的意义体验是否可以通过客观方法有意义地接近。我们的发现引发了对科学探究本身的重新审视,既是对机械规律的追求,也是对结构与意义之间微妙相互作用的尊重。这让人想起年轻的卡尔·弗里德里希·高斯,他用优雅的简单性总结了一个等比级数,揭示了隐藏在表面复杂之下的结构。通过这种方式,他通过洞察力而不是野蛮的计算来重新构建问题。如果人工智能要模仿认知,它必须与信息熵以及产生意义的价值观和意识作斗争。脑电图信号的熵平衡可能为连贯性提供了一个窗口,但只有成熟到足以尊重生命、自由和追求深刻意义的物种,才应该尝试设计人工“心灵”。在这种神经科学和哲学反思的融合中,我们看到了一种更深层次的迫切需要:在一个日益被机器定义的时代,保持作为人类意味着什么的真相。
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
Frontiers in Systems Neuroscience
Frontiers in Systems Neuroscience Neuroscience-Developmental Neuroscience
CiteScore
6.00
自引率
3.30%
发文量
144
审稿时长
14 weeks
期刊介绍: Frontiers in Systems Neuroscience publishes rigorously peer-reviewed research that advances our understanding of whole systems of the brain, including those involved in sensation, movement, learning and memory, attention, reward, decision-making, reasoning, executive functions, and emotions.
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