Neuroscience of Consciousness最新文献

According to contemporary psycho- and physiological perspectives, the brain supports our experience of the world by constantly anticipating what may happen next. In this context, limbic mesocortical areas have been proposed to play a key domain-general role in cortical processing, holding highly abstract content that may be efficiently broadcasted to virtually the whole brain, ultimately integrating interoception into a unified field of experience from the point of view of someone who has a body. Here we ground the evolutionary basis of such structural and functional organization in the hypothesis of the dual origin of the neocortex, suggesting that the addition of phylogenetically newer cortical types with modality-specific processing may have enabled the primitive polysensory role of limbic mesocortical areas to evolve into a multimodal coordinator within an ever more complex brain, favoring the possibilities of conscious experience. Moreover, two fundamental functional axes with relevance for allostasis emerge: (i) a navigation/spatial versus exchange/contact axis; and (ii) a sensing versus acting axis. The former summarizes a fundamental distinction between spatial navigation and musculoskeletal control versus close interactions in the intimate and internal spheres; the latter reflects a functional (although intimately linked) distinction between sensory and motor aspects. These axes define a conceptual bidimensional space across cortical types where virtually all cortical areas may be placed according to their functional relevance, with limbic mesocortices ultimately integrating experience across sensory-motor function and navigation-exchange. These notions have important implications for our understanding of allostasis and human experience.

During the wake-sleep cycle, consciousness waxes and wanes, and this is thought to be reflected in varying levels of integration between brain areas. Recent studies challenged the notion that consciousness is homogeneously present or absent in a brain state, as exemplified by conscious reports found in otherwise unconscious Non-rapid eye movement (NREM) sleep. Here, we tested if functional connectivity (FC) between neurons varies within brain states in a way compatible with a fluctuating level of consciousness. We examined directed FC between neurons across the wake-sleep cycle in rats, at a scale of a few seconds. We observed that NREM sleep contains epochs in which patterns of inter-areal FC are comparable to those observed in wakefulness and REM sleep, and vice versa. Thus, circuit-level connectivity patterns are not univocally determined by the brain state in which they occur, but could rather reflect other factors such as the fluctuation in the level of consciousness that takes place not only between but also within brain states.

Lived experience is shaped by intersubjective, social, cultural, and historical dimensions. For the past 30 years, neurophenomenology has adopted an embodied perspective of the mind by integrating first-person experiential and third-person neurobehavioural perspectives. Neurophenomenology reveals mutual constraints between both, as they co-constitute a person's lived experience. This article emphasizes the intersubjective and social facets of lived experience as core to generative neurophenomenology, envisioned in the 1990s by Francisco Varela, and argues that the scientific community is now ready to adopt this approach. For this endeavour, we clarify three meanings of 'generative' as it applies distinctly to generative phenomenology, generative passages, and generative models. Then, we propose to combine existing methods to update neurophenomenology program: first, by transitioning from individual to multiple people phenomenology methods that include intersubjectivity experience; second, by expanding traditional neuroscience to include measures of multimodal interpersonal synchrony; and third, by leveraging multiple computational tools to integrate different viewpoints, thereby enriching our understanding of lived experience. We also underscore the potential of diverse mathematical formalisms to capture aspects of human experience, all while underscoring that using computational approaches to model neurophenomenology does not entail endorsing computationalism as a grounding hypothesis of human experience. Finally, we illustrate the clinical relevance of this paradigm through two case studies in psychiatry-(1) with interactive dyads in autism and (2) with multiple members in family therapy sessions-demonstrating its translational potential.

Psychedelic compounds significantly reshape conscious perception, yet the implications of these alterations for complex visual-guided behaviors remain poorly understood. We investigated how psilocybin modulates visual salience processing during natural scene perception. Twenty-three participants completed eye-tracking tasks under self-blinded low and high doses of psilocybin, in a naturalistic design with experimental conditions unknown to participants and researchers. Subjects viewed natural scenes while their gaze patterns were recorded and analyzed in relation to normative computational saliency maps generated using a deep learning model of visual attention. Results revealed increased fixation on salient image regions and reduced inter-fixation distance under the high-dose condition, suggesting heightened sensitivity to visual salience and more localized gaze behavior. The Shannon entropy of fixations on high-saliency regions indicated a more exploratory and less predictable visual scanning of the images. Complementary resting-state electroencephalography recordings showed broadband spectral power reductions and increased Lempel-Ziv complexity, with delta power negatively correlating with salience metrics. These findings indicate that psilocybin induces a shift in attentional dynamics, altering gaze behavior, and salience processing during natural scene perception.

Our thoughts are inherently dynamic and often wander far from our current situation (mind wandering, MW). Although previous research revealed that brain regions involved in arousal regulation modulate neural dynamics to facilitate the transition from MW to the awareness of its occurrence, the specific physiological states and afferent signals underlying this process remain unclear. In this study, we examined electroencephalography, electrocardiography, and respiration data before participants were aware of MW during a task in which they focused on external or internal stimuli (tones or their breath). We showed that the transition to awareness of MW was characterized by decreased alpha and beta activity and a suppression of the parietal later component of the heartbeat-evoked potential (HEP), a modulation pattern identified in this study as a marker of enhanced central processing based on its consistent appearance across internal attention conditions. Furthermore, when participants were instructed to focus on their breath, they were more likely to be in the exhalation phase during the transition to awareness of MW and in the inhalation phase when MW was reported. This respiratory pattern was accompanied by changes in cardiac activity and HEP amplitudes. Based on these findings, we propose that the transition from MW to the awareness of its occurrence is associated with diverse neural activity, including the enhanced processing of bodily signals that co-occurs with specific cardiac and respiratory dynamics.

Understanding the neural correlates of consciousness remains a central challenge in neuroscience. In this study, we explore the potential of neural field theory (NFT) as a computational framework for representing consciousness states. While prior research has validated NFT's capacity to differentiate between normal and pathological states of consciousness, the relationship of its parameters to the representation of consciousness states remains unclear. Here, we fitted a corticothalamic NFT model to the electroencephalography (EEG) data collected from healthy individuals and patients with disorders of consciousness. We then comprehensively explored the correlations between the fitted NFT parameters and features extracted from both experimental and simulated EEG data across various states of consciousness. The identified correlations not only highlight the model's ability to differentiate between healthy and impaired states of consciousness, but also shed light on the physiological bases of these states, pinpointing potential biomarkers. Our results provide valuable insights into how consciousness levels are represented within the NFT framework and into the dynamics of brain activity across normal and pathological states of consciousness. This underscores the potential of NFT as a useful tool for consciousness research, facilitating in-silico experimentation.

Top-down attentional amplification is often assumed to affect 'what' we see, that is, the contents of conscious experience. Previously, this claim has been examined by studies that manipulated attention and characterized conscious perception in binary categorical labels (e.g. seen versus unseen). However, these categorical judgments are not powerful enough to characterize the quality of conscious perception, or 'how' we see, or qualia, for short. To address this, we introduce a similarity rating paradigm to consciousness research that tries to characterize the attentional effects on the structure of the quality of experience, or qualia structures for short. Under the dual-task paradigm, participants rated the similarity of stimulus pairs in the periphery. We used three stimulus sets, the rotated letters 'L' and 'T' (N = 14), rotated red/green bisected disks (N = 14) or greyscale faces (N = 13). The similarity ratings of all the pairs described the phenomenological relationships between the stimuli, and served as a proxy for the qualia structure of conscious experience of the stimuli; which we characterized with dimension reduction and an unsupervised optimal transport alignment technique. We found that alignment accuracy remained high for face qualia structures under both full and poor attention. Withdrawal of attention collapsed qualia structures for letters and disks. Extending previous dual-task approaches from binary categorizations to relational judgments, our approach establishes a novel pathway to elucidate qualia structures.

This paper uses simple arguments to derive a negative conclusion: that a computer cannot be conscious. If the brain is only a neural computer, brains cannot be conscious. Consciousness implies that there is something else happening in the brain, besides computation. In a running computer, information about outside events is encoded, to enable physical computation. The information required to decode the information (e.g. to interpret volts as bits, or neuron spike trains as numbers) is not inside the computer. The meaning of any computation is not defined inside the computer; it is only defined by some external entity which decodes the results. Without decoding information, a computer contains no information about outside events. In the same way, the meaning of any book is not defined inside the book; the book requires outside knowledge to read it. Consciousness contains meaningful information about external events. If the brain is only a computer, without decoding (which requires external information) it contains no information about external events. If the brain is only a computer, consciousness cannot be realised by events inside the brain. This conclusion is compared with philosophical positions on computational functionalism, representation, and intentionality. Something more than neural computing must be happening in the brain. One suggestion is that the something could be an analogue model of 3-D space. An analogue model contains information which requires little or no decoding. Hence, an analogue model of reality in the brain might be the source of consciousness. This merits further investigation.

[This corrects the article DOI: 10.1093/nc/niaf048.].

The motivational force of pain is undeniable. But what pain commands us to do, how we might satisfy this command, and if our experience of pain is inherently linked to suffering are far murkier topics. This paper brings together empirical studies of pain reprocessing during advanced meditation, the rise of allostatic paradigms to account for biological self-regulation, and the philosophy of pain in the classical Sanskrit philosophical tradition of Pratyabhijñā Śaivism to argue that pain is an allostatic imperative to adapt a part of one's body. We theorize two components of an allostatic response, heterostatic and homeostatic, that work in tandem to address pain as an allostatic command. Homeostatic responses are error-corrective in that they seek to protect an organism by returning to a previously stable steady state. Heterostatic responses are anticipatory in that they seek to better prepare an organism to meet future challenges by proactively shifting to a new steady state. We note that an organism's successful adaptation to its environment depends not just on error-correction, but also on anticipatory change. We theorize that a broad range of affect properly accompanies pain. We propose potential directions for empirically developing this model. We also note the possibility that this model could be extended to account for mental pain.