Neuroscience of Consciousness最新文献

During an acute episode of depersonalization/derealization (DP/DR), people report a complex and idiosyncratic change in their perceptual experience. Specifically, derealisation describes the experience of detachment from the external world and altered visual perception in which the surroundings look faded, foggy, or dream-like. Whilst some have argued that there may not be genuine perceptual changes in derealization, this proposal is yet to be tested empirically. Thus, we set out to investigate the potential perceptual changes in derealization. In this Registered Report, we conducted two online experiments to reveal the impact of DP/DR symptoms measured via the state version of the Cambridge Depersonalisation Scale (CDS) on how people evaluate (Experiment 1, N = 200, CDS-state mean: 32.43 ± 29.94 SD) and adjust (Experiment 2, N = 125, CDS-state mean: 29.38 ± 30.47 SD) naturalistic scene images with different levels of saturation and contrast. Participants were asked to rate how real the presented images look compared to their everyday experience (in Experiment 1) and to adjust the contrast or saturation level of images to match their everyday visual experience (in Experiment 2). We tested the effect of CDS-state scores on these subjective ratings via model comparison with Bayes Factors. In both experiments, we found strong evidence supporting the null models, suggesting that DP/DR symptoms did not affect realness ratings or vividness adjustments. These results provide empirical support for theories suggesting that self-reported altered vividness experience in derealization does not reflect genuine perceptual changes, instead they signify the (meta-)cognitive interpretation of these experiences. We discuss pros and cons of the current research practices when assessing derealization and highlight key avenues for the future investigation.

While the beneficial impacts of meditation are increasingly acknowledged, its underlying neural mechanisms remain poorly understood. We examined the electrophysiological brain signals of expert Buddhist monks during two established meditation methods known as Samatha and Vipassana, which employ focused attention and open-monitoring technique. By combining source-space magnetoencephalography with advanced signal processing and machine learning tools, we provide an unprecedented assessment of the role of brain oscillations, complexity, and criticality in meditation. In addition to power spectral density, we computed long-range temporal correlations (LRTC), deviation from criticality coefficient (DCC), Lempel-Ziv complexity, 1/f slope, Higuchi fractal dimension, and spectral entropy. Our findings indicate increased levels of neural signal complexity during both meditation practices compared to the resting state, alongside widespread reductions in gamma-band LRTC and 1/f slope. Importantly, the DCC analysis revealed a separation between Samatha and Vipassana, suggesting that their distinct phenomenological properties are mediated by specific computational characteristics of their dynamic states. Furthermore, in contrast to most previous reports, we observed a decrease in oscillatory gamma power during meditation, a divergence likely due to the correction of the power spectrum by the 1/f slope, which could reduce potential confounds from broadband 1/f activity. We discuss how these results advance our comprehension of the neural processes associated with focused attention and open-monitoring meditation practices.

Measuring awareness on a trial-by-trial basis might impose a multi-task cost on the observed effect. Here, we examined this potential cost, asking if it can be mitigated by training. In two experiments, one group of participants reported awareness offline, in a post-test, and another reported it online, in each trial. To test the effect of training, all participants completed two sessions on separate days. When analyzing all trials, we found overall slower reaction times (RTs) in the online group, suggesting a multi-task cost, but no interaction with the priming effect. Notably, this difference was smaller in the second session, implying that the multi-task cost is reduced by training. Critically however, this analysis yielded no convincing evidence for unconscious priming (due to potential threat of regression to the mean). We accordingly analyzed only trials where RTs were fast. Convincing response priming was found, as well as an interaction between priming and session. This suggests that training did increase priming. We also exploratorily tested for individual differences in priming and found between-session consistency mostly for the offline condition. Taken together, our results indicate that although multi-tasking adds noise and prolongs RTs, it does not necessarily diminish unconscious response priming for fast trials, which in turn can be enhanced by training. Costs and benefits of these methodological choices should thus be considered in future studies, as well as targeting only fast responses, where the effects were more compelling. Future work should also test if these patterns apply to other types of priming.

Anomalous experiences, such as hallucinations and mystical experiences, are positively related to delusional ideation, religiosity, and paranormal beliefs. Some researchers argue that these relationships are explained by 'transliminality'-a trait describing sensitivity to stimuli crossing the threshold into consciousness. This claim suggests such beliefs may be attempts to interpret barely perceptible stimuli. The strongest evidence for this comes from Crawley et al. (2002), who found transliminality was associated with responses to subperceptual primes. In the current study, we attempted a high-powered replication of Crawley et al.'s findings that: (i) transliminality predicts identification of subperceptual visual primes, and (ii) this relationship is explained by stimulus sensitivity rather than response bias. Participants completed a transliminality measure and an online card guessing task in two parts. In part one, participants were shown 100 images of playing cards and asked to guess which of five shapes was on the other side of the card. A total of 50 trials contained a subperceptual prime in the form of a target shape, and 50 trials were unprimed. In part two, participants were shown 20 primed and 20 unprimed trials. They were told a prime was sometimes present and asked to report whether they noticed this on each trial. We found strong evidence against an association between transliminality and prime perception in both tasks. These results do not support conceptualizing transliminality as a measure of subperceptual processing capabilities. This study did demonstrate the feasibility of conducting research involving rapidly presented visual stimuli in an online setting.

A central question of consciousness research is which cognitive processes can occur unconsciously. To investigate this, researchers typically compare participants' ability to consciously discriminate a stimulus to their unconscious processing of the same stimulus (e.g. measured via reaction time or brain activity). If participants are not significantly different from chance in the awareness (or "direct") measure while nevertheless there is a significant effect in the processing (or "indirect") measure, researchers argue that there is no conscious processing of the stimulus, while the stimulus is nevertheless somehow processed, as indicated by the processing measure. In consequence researchers conclude that the stimulus has been processed unconsciously. Using neuroimaging techniques such as functional magnetic resonance imaging (fMRI), researchers then infer which brain regions are involved in unconscious versus conscious processing. However, this methodology is based on a fundamental statistical fallacy that has likely led to an overestimation of the scope of unconscious processing, regarding both its capacity and the brain areas involved. The key problem is that sensitivities in the two measures are never directly compared. Therefore, it is not appropriate to conclude that the processing measure had higher sensitivity than the awareness measure. We reanalyzed the results from 16 fMRI studies directly comparing the sensitivities of both measures in 80 experimental conditions. Our results show that, using this sensitivity comparison method, only eight experimental conditions provide evidence for unconscious processing. These results question the validity of the interpretations commonly drawn in the field.

We have a fair understanding of what contributes to our confidence when performing individual trials of a task. However, little is known regarding the factors driving more global metacognitive estimates when a task is repeated. The present study investigates the contribution of uncertainty to global performance monitoring. In two pre-registered experiments, participants performed four trials of an orientation matching task and reported their mean response and an estimated dispersion around this perceived mean as a proxy for global performance monitoring. We considered several sources of uncertainty: response-related uncertainty, related to the participants and observed in their response variability, and perceptual or attentional uncertainty related to the sensory stimulation. Our results suggest that adults can reliably estimate the mean and dispersion of their performance and use it together with stimulus-dependent uncertainty to inform their global performance monitoring. In particular, participants adequately report that their performance was worse when uncertainty was higher. However, this capacity decreases when different types of uncertainty increase jointly. We discuss these results in light of a model of confidence that reproduced our main findings. These behavioral and computational results clarify the role of uncertainty in perceptual metacognition and the relationship between local and global performance monitoring.

There have been many very promising theories published concerning the generation of consciousness. These theories mostly link the emergence of consciousness to neural activity, but very few attempt to show how that neural activity specifically causes experience to occur. This article explores this problem at the level of individual networks by examining the information changes that occur as input patterns are processed. It looks at how networks can identify spatially distributed input patterns, and generate representations of that identity. It argues that if those representations are directly fed back then such networks will be identifying their own depictions of the original identity. It goes on to argue that in this state the identity acquired is not what the input is to the network but how the input seems to it. There would be content to that inner portrayal that must present itself in some way to the receiver, and this could underlie the emergence of qualia. The article goes on to argue how top-down modulation could select which qualia are established at any moment.

In this study, we explore how the notion of meta-representations in higher-order theories (HOT) of consciousness can be implemented in computational models. HOT suggests that consciousness emerges from meta-representations, which are representations of first-order sensory representations. However, translating this abstract concept into a concrete computational model, such as those used in artificial intelligence, presents a theoretical challenge. For example, a simplistic interpretation of meta-representation as a representation of representation makes the notion rather trivial and ubiquitous. Here, as a foundational step toward understanding meta-representations, we propose a refined computational interpretation that focuses specifically on process-level representations. Contrary to the simplistic view of meta-representations as mere transformations of the first-order representational states or confidence estimates, we argue that meta-representations represent the computational processes that generate first-order representations, building on the Radical Plasticity Thesis by Cleeremans (2011). https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2011.00086.) This presents a process-oriented view whereby meta-representations capture the qualitative aspect of how sensory information is transformed into first-order representations. As a proof-of-concept of this formulated notion of meta-representation, we constructed "meta-networks" designed to explicitly model meta-representations within deep learning architectures while methodologically isolating process representations from specific sensory activations to avoid confounding effects. Specifically, we constructed meta-networks by implementing autoencoders of first-order neural networks. In this architecture, the latent spaces embedding those first-order networks correspond to the meta-representations of first-order networks. By applying meta-networks to embed neural networks trained to encode visual and auditory datasets, we show that the meta-representations of first-order networks successfully capture the qualitative aspects of those networks by separating the visual and auditory networks in the meta-representation space. We argue that such meta-representations would be useful for quantitatively comparing and contrasting the qualitative differences of computational processes. While whether such meta-representational systems exist in the human brain remains an open question, this formulation of meta-representation offers a new empirically testable hypothesis that there are brain regions that represent the processes of transforming a representation in one brain region to a representation in another brain region. Furthermore, this form of meta-representations might underlie our ability to describe the qualitative aspect of sensory experience or qualia.

Affective stimuli, such as fearful faces, are assumed to receive prioritized processing over neutral stimuli, making them easier to detect when perception is suppressed using techniques such as visual masking or binocular rivalry. Moreover, some studies suggest that fearful expressions can be processed outside of conscious awareness, as evidenced by enhanced early event-related potentials (ERPs) in response to subliminally presented fearful vs. neutral faces. This might be associated with increased detection of fear-related stimuli. However, it remains unclear whether increased cortical processing of unseen fearful faces is a necessary condition for detection advantages and whether effects are related to expression-related or low-level features of stimuli. In the present pre-registered ERP study, we addressed these questions using stereoscopic forward masking (FM). Forty-eight male and female participants were presented with fearful and neutral, intact and phase-scrambled faces. The behavioural results showed that masked fearful faces were detected better than neutral faces. Phase-scrambled faces did not show this effect, indicating that the perceptual advantage was not mediated by low-level spectral stimulus properties. ERPs elicited by consciously perceived faces showed typical expression effects in the form of enhanced occipito-temporal negativities in the time range of the N170 and the early posterior negativity (EPN). Crucially, these effects were absent for subjectively invisible faces, as corroborated by Bayesian statistics. Taken together, our results suggest that the perceptual advantage of fearful faces under dichoptic FM cannot be attributed to low-level stimulus properties. Furthermore, within this paradigm, the perceptual advantage does not coincide with the amplification of early ERPs to subjectively invisible faces, suggesting a dissociation between unconscious stimulus processing and stimulus detection.

This article presents a neuroscientific interpretation of Carl Jung's theory of archetypes and their experience in altered states of consciousness. We begin by rehearsing the Free Energy Principle and Predictive Processing as foundational frameworks that subserve and inform the thesis that follows. The following sections examine three aspects of archetypes: the affective core rooted in subcortical systems, archetypal imagery emergent in altered states such as psychedelic experiences, and archetypal stories encoded in higher cortical areas. Specifically, we propose a trilogical interplay between the high-level cortex, the low-level cortex, and subcortical/affective systems in instantiating these archetypal phenomena. We then explore how archetypes may be transmitted between individuals, developing into a collective unconscious through social learning and subsequent attunement. Throughout, we provide syntheses of Jungian psychology with contemporary neuroscience, offering testable hypotheses regarding the neurological bases of archetypal phenomena. We conclude by discussing implications for both psychoanalytic theory and neuroscientific research. By bridging these disciplines, we aim to lend construct validity to Jungian concepts and encourage further empirical investigation of archetypes and the collective unconscious.