Neuroscience of Consciousness最新文献

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 x-axis) and the content (e.g. perceived versus unperceived or different levels of cognitive processing on the y-axis). According to the sign of the x- and y-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.

The Integrated Information Theory is a theoretical framework that aims to elucidate the nature of consciousness by postulating that it emerges from the integration of information within a system, and that the degree of consciousness depends on the extent of information integration within the system. When consciousness is lost, the core complex of consciousness proposed by the Integrated Information Theory disintegrates, and Φ measures, which reflect the level of integrated information, are expected to diminish. This study examined the predictions of the Integrated Information Theory using the global brain network acquired via functional magnetic resonance imaging during various tasks and sleep. We discovered that the complex located within the frontoparietal network remained constant regardless of task content, while the regional distribution of the complex collapsed in the initial stages of sleep. Furthermore, Φ measures decreased as sleep progressed under limited analysis conditions. These findings align with predictions made by the Integrated Information Theory and support its postulates.

[This corrects the article DOI: 10.1093/nc/niae017.].

The contents of awareness can substantially change without any modification to the external world. Such effects are exemplified in binocular rivalry, where a different stimulus is presented to each eye causing instability in perception. This phenomenon has made binocular rivalry a quintessential method for studying consciousness and the necessary neural correlates for awareness. However, to conduct research on binocular rivalry usually requires self-reports of changes in percept, which can produce confounds and exclude states and contexts where self-reports are undesirable or unreliable. Here, we use a novel multivariate spatial filter dubbed 'Rhythmic Entrainment Source Separation' to extract steady state visual evoked potentials from electroencephalography data. We show that this method can be used to quantify the perceptual switch-rate of participants during binocular rivalry and therefore may be valuable in experimental contexts where self-reports are methodologically problematic or impossible, particularly as an adjunct. Our analyses also reveal that 'no-report' conditions may affect the deployment of attention and thereby neural correlates, another important consideration for consciousness research.

A recent advancement in consciousness science has been the introduction of a multidimensional framework of consciousness. This framework has been applied to global states of consciousness, including psychedelic states and disorders of consciousness, and the consciousness of non-human animals. The multidimensional framework enables a finer parsing of both various states of consciousness and forms of animal consciousness, paving the way for new scientific investigations into consciousness. In this paper, the multidimensional model is expanded by constructing temporal profiles. This expansion allows for the modelling of changes in consciousness across the life cycles of organisms and the progression over time of disorders of consciousness. The result of this expansion is 2-fold: (i) it enables new modes of comparison, both across stages of development and across species; (ii) it proposes that more attention be given to the various types of fluctuations that occur in patients who are suffering from disorders of consciousness.

Modern medicine has been shaken by the surge of psychedelic science that proposes a new approach to mitigate mental disorders, such as depression and post-traumatic stress disorder. Clinical trials to investigate whether psychedelic substances can treat psychiatric conditions are now underway, yet less discussion gravitates around their use in neurological disorders due to brain injury. One suggested implementation of brain-complexity enhancing psychedelics is to treat people with post-comatose disorders of consciousness (DoC). In this article, we discuss the rationale of this endeavour, examining possible outcomes of such experiments by postulating the existence of an optimal level of complexity. We consider the possible counterintuitive effects of both psychedelics and DoC on the functional connectivity of the default mode network and its possible impact on selfhood. We also elaborate on the role of computational modelling in providing complementary information to experimental studies, both contributing to our understanding of the treatment mechanisms and providing a path towards personalized medicine. Finally, we update the discourse surrounding the ethical considerations, encompassing clinical and scientific values.

Trance states include various practices characterized by a modulation of consciousness, but with their own specific characteristics and induction techniques. They have been very seldom scientifically studied, and their phenomenological similarities and differences are poorly documented. This paper will focus on two types of Western trances developed after the leaders were trained in traditional shamanic communities: the auto-induced cognitive trance (AICT) and the Mahorikatan^® trance (MT). Twenty-five AICT and 26 MT participants who were able to self-induce the trance state completed questionnaires about their trance practice (e.g. context of the first trance episode, frequency of practice, and consequences on personal life) and the phenomenological characteristics (i.e. emotional, physical, and cognitive) of the trance episodes they experienced. These characteristics were compared to explore similarities and differences between the two trance states. AICT and MT are characterized by the expression of different emotions, modification of various perceptions, a feeling of unicity (i.e. being completely oneself), and an expansion of consciousness. AICT participants commonly reported body movements, vocalizations, as well as increased creativity, visions of entities and/or places, and feeling of interaction with the environment. MT participants commonly reported a feeling of body dissolution. Most participants in both groups reported positive effects of their trance practice on their personal life. These results helped characterize AICT and MT, as well as their similarities and differences. Further studies should continue to explore the characteristics of such trance states, as well as their potential clinical applications.

[This corrects the article DOI: 10.1093/nc/niae001.].

In daily life, we can not only estimate confidence in our inferences ('I'm sure I failed that exam'), but can also estimate whether those feelings of confidence are good predictors of decision accuracy ('I feel sure I failed, but my feeling is probably wrong; I probably passed'). In the lab, by using simple perceptual tasks and collecting trial-by-trial confidence ratings visual metacognition research has repeatedly shown that participants can successfully predict the accuracy of their perceptual choices. Can participants also successfully evaluate 'confidence in confidence' in these tasks? This is the question addressed in this study. Participants performed a simple, two-interval forced choice numerosity task framed as an exam. Confidence judgements were collected in the form of a 'predicted exam grade'. Finally, we collected 'meta-metacognitive' reports in a two-interval forced-choice design: trials were presented in pairs, and participants had to select that in which they thought their confidence (predicted grade) best matched their accuracy (actual grade), effectively minimizing their quadratic scoring rule (QSR) score. Participants successfully selected trials on which their metacognition was better when metacognitive performance was quantified using area under the type 2 ROC (AUROC2) but not when using the 'gold-standard' measure m-ratio. However, further analyses suggested that participants selected trials on which AUROC2 is lower in part via an extreme-confidence heuristic, rather than through explicit evaluation of metacognitive inferences: when restricting analyses to trials on which participants gave the same confidence rating AUROC2 no longer differed as a function of selection, and likewise when we excluded trials on which extreme confidence ratings were given. Together, our results show that participants are able to make effective metacognitive discriminations on their visual confidence ratings, but that explicit 'meta-metacognitive' processes may not be required.