Pérez Pauline, Manasova Dragana, Hermann Bertrand, Raimondo Federico, Rohaut Benjamin, Bekinschtein Tristán A, Naccache Lionel, Arzi Anat, Sitt Jacobo D
Institut du Cerveau - Paris Brain Institute, Inserm, CNRS, Sorbonne Université, Paris 75013, France.
Hospice Civils de Lyon-HCL, Département anesthésie-réanimation, Hôpital Edouard Herriot.
Neurosci Conscious. 2024 Jul 12;2024(1):niae027. doi: 10.1093/nc/niae027. eCollection 2024.
Identifying the neuronal markers of consciousness is key to supporting the different scientific theories of consciousness. Neuronal markers of consciousness can be defined to reflect either the brain signatures underlying specific conscious content or those supporting different states of consciousness, two aspects traditionally studied separately. In this paper, we introduce a framework to characterize markers according to their dynamics in both the "state" and "content" dimensions. The 2D space is defined by the marker's capacity to distinguish the conscious states from non-conscious states (on the -axis) and the content (e.g. perceived versus unperceived or different levels of cognitive processing on the -axis). According to the sign of the - and -axis, markers are separated into four quadrants in terms of how they distinguish the state and content dimensions. We implement the framework using three types of electroencephalography markers: markers of connectivity, markers of complexity, and spectral summaries. The neuronal markers of state are represented by the level of consciousness in (i) healthy participants during a nap and (ii) patients with disorders of consciousness. On the other hand, the neuronal markers of content are represented by (i) the conscious content in healthy participants' perception task using a visual awareness paradigm and (ii) conscious processing of hierarchical regularities using an auditory local-global paradigm. In both cases, we see separate clusters of markers with correlated and anticorrelated dynamics, shedding light on the complex relationship between the state and content of consciousness and emphasizing the importance of considering them simultaneously. This work presents an innovative framework for studying consciousness by examining neuronal markers in a 2D space, providing a valuable resource for future research, with potential applications using diverse experimental paradigms, neural recording techniques, and modeling investigations.
识别意识的神经元标记物是支持不同意识科学理论的关键。意识的神经元标记物可以被定义为反映特定意识内容背后的大脑特征，或者支持不同意识状态的特征，这两个方面传统上是分开研究的。在本文中，我们引入了一个框架，根据标记物在“状态”和“内容”维度上的动态特性来对其进行表征。二维空间由标记物区分意识状态与非意识状态的能力（在x轴上）以及内容（例如，感知到的与未感知到的，或者在y轴上不同水平的认知加工）来定义。根据x轴和y轴的符号，标记物根据它们区分状态和内容维度的方式被分为四个象限。我们使用三种类型的脑电图标记物来实现这个框架：连接性标记物、复杂性标记物和频谱汇总。状态的神经元标记物由以下两种情况表示：（i）小睡期间健康参与者的意识水平，以及（ii）意识障碍患者的意识水平。另一方面，内容的神经元标记物由以下两种情况表示：（i）使用视觉意识范式的健康参与者感知任务中的意识内容，以及（ii）使用听觉局部-全局范式对层次规律的意识加工。在这两种情况下，我们都看到了具有相关和反相关动态特性的标记物集群，这揭示了意识状态和内容之间的复杂关系，并强调了同时考虑它们的重要性。这项工作通过在二维空间中检查神经元标记物，提出了一个研究意识的创新框架，为未来的研究提供了宝贵的资源，具有使用各种实验范式、神经记录技术和建模研究的潜在应用。
