Intracranial neural representation of phenomenal and access consciousness in the human brain.

After more than 30 years of extensive investigation, impressive progress has been made in identifying the neural correlates of consciousness (NCC). However, the functional role of spatiotemporally distinct consciousness-related neural activity in conscious perception is debated. An influential framework proposed that consciousness-related neural activities could be dissociated into two distinct processes: phenomenal and access consciousness. However, though hotly debated, its authenticity has not been examined in a single paradigm with more informative intracranial recordings. In the present study, we employed a visual awareness task and recorded the local field potential (LFP) of patients with electrodes implanted in cortical and subcortical regions. Overall, we found that the latency of visual awareness-related activity exhibited a bimodal distribution, and the recording sites with short and long latencies were largely separated in location, except in the lateral prefrontal cortex (lPFC). The mixture of short and long latencies in the lPFC indicates that it plays a critical role in linking phenomenal and access consciousness. However, the division between the two is not as simple as the central sulcus, as proposed previously. Moreover, in 4 patients with electrodes implanted in the bilateral prefrontal cortex, early awareness-related activity was confined to the contralateral side, while late awareness-related activity appeared on both sides. Finally, Granger causality analysis showed that awareness-related information flowed from the early sites to the late sites. These results provide the first LFP evidence of neural correlates of phenomenal and access consciousness, which sheds light on the spatiotemporal dynamics of NCC in the human brain.

A Mechanistic Model of Perceptual Binding Predicts That Binding Mechanism Is Robust against Noise.

The concept of the brain's own time and space is central to many models and theories that aim to explain how the brain generates consciousness. For example, the temporo-spatial theory of consciousness postulates that the brain implements its own inner time and space for conscious processing of the outside world. Furthermore, our perception and cognition of time and space can be different from actual time and space. This study presents a mechanistic model of mutually connected processes that encode phenomenal representations of space and time. The model is used to elaborate the binding mechanism between two sets of processes representing internal space and time, respectively. Further, a stochastic version of the model is developed to investigate the interplay between binding strength and noise. Spectral entropy is used to characterize noise effects on the systems of interacting processes when the binding strength between them is varied. The stochastic modeling results reveal that the spectral entropy values for strongly bound systems are similar to those for weakly bound or even decoupled systems. Thus, the analysis performed in this study allows us to conclude that the binding mechanism is noise-resilient.

Highly connected and highly variable: A Core brain network during resting state supports Propofol-induced unconsciousness.

Despite that leading theories of consciousness make diverging predictions for where and how neural activity gives rise to subjective experience, they all seem to partially agree that the neural correlates of consciousness (NCC) require globally integrated brain activity across a network of functionally specialized modules. However, it is not clear yet whether such functional configurations would be able to identify the NCC. We scanned resting-state fMRI data from 21 subjects during wakefulness, propofol-induced sedation, and anesthesia. Graph-theoretical analyses were conducted on awake fMRI data to search for the NCC candidates as brain regions that exhibit both high rich-clubness and high modular variability, which were found to locate in prefrontal and temporoparietal cortices. Another independent data set of 10 highly-sampled subjects was used to validate the NCC distribution at the individual level. Brain module-based dynamic analysis revealed two discrete reoccurring brain states, one of which was dominated by the NCC candidates (state 1), while the other state was predominately composed of primary sensory/motor regions (state 2). Moreover, state 1 appeared to be temporally more stable than state 2, suggesting that the identified NCC members could sustain conscious content as metastable network representations. Finally, we showed that the identified NCC was modulated in terms of functional connectedness and modular variability in response to the loss of consciousness induced by propofol anesthesia. This work offers a framework to search for neural correlates of consciousness by charting the brain network topology and provides new insights into understanding the roles of different regions in underpinning human consciousness.

Electrophysiological Chronometry of Graded Consciousness during the Attentional Blink.

One of the ongoing debates about visual consciousness is whether it can be considered as an all-or-none or a graded phenomenon. While there is increasing evidence for the existence of graded states of conscious awareness based on paradigms such as visual masking, only little and mixed evidence is available for the attentional blink paradigm, specifically in regard to electrophysiological measures. Thereby, the all-or-none pattern reported in some attentional blink studies might have originated from specifics of the experimental design, suggesting the need to examine the generalizability of results. In the present event-related potential (ERP) study (N = 32), visual awareness of T2 face targets was assessed via subjective visibility ratings on a perceptual awareness scale in combination with ERPs time-locked to T2 onset (components P1, N1, N2, and P3). Furthermore, a classification task preceding visibility ratings allowed to track task performance. The behavioral results indicate a graded rather than an all-or-none pattern of visual awareness. Corresponding graded differences in the N1, N2, and P3 components were observed for the comparison of visibility levels. These findings suggest that conscious perception during the attentional blink can occur in a graded fashion.

What Is It like to Be a Brain Organoid? Phenomenal Consciousness in a Biological Neural Network.

It has been shown that three-dimensional self-assembled multicellular structures derived from human pluripotent stem cells show electrical activity similar to EEG. More recently, neurons were successfully embedded in digital game worlds. The biologically inspired neural network (BNN), expressing human cortical cells, was able to show internal modification and learn the task at hand (predicting the trajectory of a digital ball while moving a digital paddle). In other words, the system allowed to read motor information and write sensory data into cell cultures. In this article, we discuss Neural Correlates of Consciousness (NCC) theories, and their capacity to predict or even allow for consciousness in a BNN. We found that Information Integration Theory (IIT) is the only NCC that offers the possibility for a BNN to show consciousness, since the Φ value in the BNN is >0. In other words, the recording of real-time neural activity responding to environmental stimuli. IIT argues that any system capable of integrating information will have some degree of phenomenal consciousness. We argue that the pattern of activity appearing in the BNN, with increased density of sensory information leading to better performance, implies that the BNN could be conscious. This may have profound implications from a psychological, philosophical, and ethical perspective.

Measuring consciousness in severely damaged brains.

Significant advances have been made in the behavioral assessment and clinical management of disorders of consciousness (DOC). In addition, functional neuroimaging paradigms are now available to help assess consciousness levels in this challenging patient population. The success of these neuroimaging approaches as diagnostic markers is, however, intrinsically linked to understanding the relationships between consciousness and the brain. In this context, a combined theoretical approach to neuroimaging studies is needed. The promise of such theoretically based markers is illustrated by recent findings that used a perturbational approach to assess the levels of consciousness. Further research on the contents of consciousness in DOC is also needed.

Columnar clusters in the human motion complex reflect consciously perceived motion axis.

The specific contents of human consciousness rely on the activity of specialized neurons in cerebral cortex. We hypothesized that the conscious experience of a specific visual motion axis is reflected in response amplitudes of direction-selective clusters in the human motion complex. Using submillimeter fMRI at ultrahigh field (7 T) we identified fine-grained clusters that were tuned to either horizontal or vertical motion presented in an unambiguous motion display. We then recorded their responses while human observers reported the perceived axis of motion for an ambiguous apparent motion display. Although retinal stimulation remained constant, subjects reported recurring changes between horizontal and vertical motion percepts every 7 to 13 s. We found that these perceptual states were dissociatively reflected in the response amplitudes of the identified horizontal and vertical clusters. We also found that responses to unambiguous motion were organized in a columnar fashion such that motion preferences were stable in the direction of cortical depth and changed when moving along the cortical surface. We suggest that activity in these specialized clusters is involved in tracking the distinct conscious experience of a particular motion axis.

Implications of Noise on Neural Correlates of Consciousness: A Computational Analysis of Stochastic Systems of Mutually Connected Processes.

Random fluctuations in neuronal processes may contribute to variability in perception and increase the information capacity of neuronal networks. Various sources of random processes have been characterized in the nervous system on different levels. However, in the context of neural correlates of consciousness, the robustness of mechanisms of conscious perception against inherent noise in neural dynamical systems is poorly understood. In this paper, a stochastic model is developed to study the implications of noise on dynamical systems that mimic neural correlates of consciousness. We computed power spectral densities and spectral entropy values for dynamical systems that contain a number of mutually connected processes. Interestingly, we found that spectral entropy decreases linearly as the number of processes within the system doubles. Further, power spectral density frequencies shift to higher values as system size increases, revealing an increasing impact of negative feedback loops and regulations on the dynamics of larger systems. Overall, our stochastic modeling and analysis results reveal that large dynamical systems of mutually connected and negatively regulated processes are more robust against inherent noise than small systems.

A Traditional Scientific Perspective on the Integrated Information Theory of Consciousness.

This paper assesses two different theories for explaining consciousness, a phenomenon that is widely considered amenable to scientific investigation despite its puzzling subjective aspects. I focus on Integrated Information Theory (IIT), which says that consciousness is integrated information (as ϕMax) and says even simple systems with interacting parts possess some consciousness. First, I evaluate IIT on its own merits. Second, I compare it to a more traditionally derived theory called Neurobiological Naturalism (NN), which says consciousness is an evolved, emergent feature of complex brains. Comparing these theories is informative because it reveals strengths and weaknesses of each, thereby suggesting better ways to study consciousness in the future. IIT's strengths are the reasonable axioms at its core; its strong logic and mathematical formalism; its creative "experience-first" approach to studying consciousness; the way it avoids the mind-body ("hard") problem; its consistency with evolutionary theory; and its many scientifically testable predictions. The potential weakness of IIT is that it contains stretches of logic-based reasoning that were not checked against hard evidence when the theory was being constructed, whereas scientific arguments require such supporting evidence to keep the reasoning on course. This is less of a concern for the other theory, NN, because it incorporated evidence much earlier in its construction process. NN is a less mature theory than IIT, less formalized and quantitative, and less well tested. However, it has identified its own neural correlates of consciousness (NCC) and offers a roadmap through which these NNCs may answer the questions of consciousness using the hypothesize-test-hypothesize-test steps of the scientific method.

An ESR Framework for the Study of Consciousness.

I will argue that, in an interdisciplinary study of consciousness, epistemic structural realism (ESR) can offer a feasible philosophical background for the study of consciousness and its associated neurophysiological phenomena in neuroscience and cognitive science while also taking into account the mathematical structures involved in this type of research. Applying the ESR principles also to the study of the neurophysiological phenomena associated with free will (or rather conscious free choice) and with various alterations of consciousness (AOCs) generated by various pathologies such as epilepsy would add explanatory value to the matter. This interdisciplinary approach would be in tune with Quine's well known idea that philosophy is not simple conceptual analysis but is continuous with science and actually represents an abstract branch of the empirical research. The ESR could thus resonate with scientific models of consciousness such as the global neuronal workspace model (inspired by the global workspace theory-GWT) and the integrated information theory (IIT) model. While structural realism has already been employed in physics or biology, its application as a meta-theory contextualising and relating various scientific findings on consciousness is new indeed. Out of the two variants: ontic structural realism (OSR) and epistemic structural realism (ESR), the latter can be considered more suitable for the study of consciousness and its associated neurophysiological phenomena because it removes the pressure of the still unanswered 'What is consciousness?' ontological question and allows us to concentrate instead on the 'What can we know about consciousness?' epistemological question.

The temporally-integrated causality landscape: A theoretical framework for consciousness and meaning.

Theoretical approaches to understanding consciousness have begun to converge upon areas of general agreement, yet substantive differences remain. Here, I introduce a new theoretical framework for the emergence of consciousness from the functional integration of the thalamocortical system: the Temporally-Integrated Causality Landscape (TICL). TICL presents a novel perspective which addresses important phenomenological characteristics of consciousness that other frameworks, such as IIT, do not. First, the TICL is based upon the observation that conscious experiences are temporally continuous, not discrete. Secondly, the TICL establishes a thalamocortical basis for the point-of-view. According to TICL, consciousness is composed of contents that arise from neuronal subsystems that have meaning from the point-of-view of the larger, integrated system in which they are nested. Meaningful contents emerge from the subsystems because they exhibit a level of temporally-integrated causality (TIC) that is distinguishable from that of the larger system.

ERP and MEG correlates of visual consciousness: The second decade.

The first decade of event-related potential (ERP) research had established that the most consistent correlates of the onset of visual consciousness are the early visual awareness negativity (VAN), a posterior negative component in the N2 time range, and the late positivity (LP), an anterior positive component in the P3 time range. Two earlier extensive reviews ten years ago had concluded that VAN is the earliest and most reliable correlate of visual phenomenal consciousness, whereas LP probably reflects later processes associated with reflective/access consciousness. This article provides an update to those earlier reviews. ERP and MEG studies that have appeared since 2010 and directly compared ERPs between aware and unaware conditions are reviewed, and important new developments in the field are discussed. The result corroborates VAN as the earliest and most consistent signature of visual phenomenal consciousness, and casts further doubt on LP as an ERP correlate of phenomenal consciousness.

The role of levels of processing in disentangling the ERP signatures of conscious visual processing.

We aimed to distinguish electrophysiological signatures of visual awareness from other task-related processes through manipulating the level of processing of visual stimuli. During an event-related EEG experiment, 36 subjects performed either color (low-level condition) or magnitude (high-level condition) evaluations of masked digits. Participants also assessed subjective visibility of each stimulus using the Perceptual Awareness Scale (PAS). Mean amplitude of the components of interest was analyzed (VAN - 140-240 ms; LP - 380-480 ms) with weighted regression mixed model. In the VAN component time window the mean amplitude correlated with PAS rating in both conditions. Mean amplitude in the LP time window correlated with PAS ratings in the high-level condition, but not in the low-level condition. Our results support the temporal unfolding of ERP makers of conscious processing, with an early component reflecting the initial perceptual experience and a late component being a correlate of the conscious experience of non-perceptual information.

Consciousness as a concrete physical phenomenon.

The typical empirical approach to studying consciousness holds that we can only observe the neural correlates of experiences, not the experiences themselves. In this paper we argue, in contrast, that experiences are concrete physical phenomena that can causally interact with other phenomena, including observers. Hence, experiences can be observed and scientifically modelled. We propose that the epistemic gap between an experience and a scientific model of its neural mechanisms stems from the fact that the model is merely a theoretical construct based on observations, and distinct from the concrete phenomenon it models, namely the experience itself. In this sense, there is a gap between any natural phenomenon and its scientific model. On this approach, a neuroscientific theory of the constitutive mechanisms of an experience is literally a model of the subjective experience itself. We argue that this metatheoretical framework provides a solid basis for the empirical study of consciousness.

Consciousness Regained: Disentangling Mechanisms, Brain Systems, and Behavioral Responses.

How consciousness (experience) arises from and relates to material brain processes (the "mind-body problem") has been pondered by thinkers for centuries, and is regarded as among the deepest unsolved problems in science, with wide-ranging theoretical, clinical, and ethical implications. Until the last few decades, this was largely seen as a philosophical topic, but not widely accepted in mainstream neuroscience. Since the 1980s, however, novel methods and theoretical advances have yielded remarkable results, opening up the field for scientific and clinical progress. Since a seminal paper by Crick and Koch (1998) claimed that a science of consciousness should first search for its neural correlates (NCC), a variety of correlates have been suggested, including both content-specific NCCs, determining particular phenomenal components within an experience, and the full NCC, the neural substrates supporting entire conscious experiences. In this review, we present recent progress on theoretical, experimental, and clinical issues. Specifically, we (1) review methodological advances that are important for dissociating conscious experience from related enabling and executive functions, (2) suggest how critically reconsidering the role of the frontal cortex may further delineate NCCs, (3) advocate the need for general, objective, brain-based measures of the capacity for consciousness that are independent of sensory processing and executive functions, and (4) show how animal studies can reveal population and network phenomena of relevance for understanding mechanisms of consciousness.

A methodological dilemma for investigating consciousness empirically.

This paper exposes a methodological dilemma arising for the research program of finding the neural correlate of consciousness (NCC), the minimal set of brain processes sufficient for a particular percept. The main claim is that it is doubtful that the right kind of correlations will ever be obtained because the foregoing conceptual decisions regarding the relations between consciousness, attention, cognitive access, report, and other cognitive functions determine the interpretation of the correlation data that can be obtained. Relying on subjective reports likely leads to confounding the NCC with neural mechanisms for cognitive functions because reports presuppose cognitive access. No-report paradigms are in danger of confounding the NCC with neural mechanisms underlying unconscious processes. So there does not seem to be a way of making sure to have isolated the neural correlate of conscious experience.

The levels of perceptual processing and the neural correlates of increasing subjective visibility.

According to the levels-of-processing hypothesis, transitions from unconscious to conscious perception may depend on stimulus processing level, with more gradual changes for low-level stimuli and more dichotomous changes for high-level stimuli. In an event-related fMRI study we explored this hypothesis using a visual backward masking procedure. Task requirements manipulated level of processing. Participants reported the magnitude of the target digit in the high-level task, its color in the low-level task, and rated subjective visibility of stimuli using the Perceptual Awareness Scale. Intermediate stimulus visibility was reported more frequently in the low-level task, confirming prior behavioral results. Visible targets recruited insulo-fronto-parietal regions in both tasks. Task effects were observed in visual areas, with higher activity in the low-level task across all visibility levels. Thus, the influence of level of processing on conscious perception may be mediated by attentional modulation of activity in regions representing features of consciously experienced stimuli.

Juxtaposing the real-time unfolding of subjective experience and ERP neuromarker dynamics.

Electroencephalographic (EEG) potentials have remained a valuable source of data and theories concerning neural correlates of consciousness (NCC). The EEG based methods are far from being exhausted and are continually valuable in the quest for the markers of NCC. To set the background for the research presented in this issue, we review the published work on EEG-based markers of NCC. The article is organized according to the principle of the time-course aspect of brain potentials with regard to the stimuli for which subject's awareness is experimentally measured and/or manipulated. We treat brain potentials as the principal dependent measure as well as independent variable. More specifically, we also draw attention to the fact that in the overwhelming share of studies relative negativization of the ERPs tends to mark NCC.

Homing in on consciousness in the nervous system: An action-based synthesis.

What is the primary function of consciousness in the nervous system? The answer to this question remains enigmatic, not so much because of a lack of relevant data, but because of the lack of a conceptual framework with which to interpret the data. To this end, we have developed Passive Frame Theory, an internally coherent framework that, from an action-based perspective, synthesizes empirically supported hypotheses from diverse fields of investigation. The theory proposes that the primary function of consciousness is well-circumscribed, serving the somatic nervous system. For this system, consciousness serves as a frame that constrains and directs skeletal muscle output, thereby yielding adaptive behavior. The mechanism by which consciousness achieves this is more counterintuitive, passive, and "low level" than the kinds of functions that theorists have previously attributed to consciousness. Passive frame theory begins to illuminate (a) what consciousness contributes to nervous function, (b) how consciousness achieves this function, and (c) the neuroanatomical substrates of conscious processes. Our untraditional, action-based perspective focuses on olfaction instead of on vision and is descriptive (describing the products of nature as they evolved to be) rather than normative (construing processes in terms of how they should function). Passive frame theory begins to isolate the neuroanatomical, cognitive-mechanistic, and representational (e.g., conscious contents) processes associated with consciousness.

Psychophysical "blinding" methods reveal a functional hierarchy of unconscious visual processing.

Numerous non-invasive experimental "blinding" methods exist for suppressing the phenomenal awareness of visual stimuli. Not all of these suppressive methods occur at, and thus index, the same level of unconscious visual processing. This suggests that a functional hierarchy of unconscious visual processing can in principle be established. The empirical results of extant studies that have used a number of different methods and additional reasonable theoretical considerations suggest the following tentative hierarchy. At the highest levels in this hierarchy is unconscious processing indexed by object-substitution masking. The functional levels indexed by crowding, the attentional blink (and other attentional blinding methods), backward pattern masking, metacontrast masking, continuous flash suppression, sandwich masking, and single-flash interocular suppression, fall at progressively lower levels, while unconscious processing at the lowest levels is indexed by eye-based binocular-rivalry suppression. Although unconscious processing levels indexed by additional blinding methods is yet to be determined, a tentative placement at lower levels in the hierarchy is also given for unconscious processing indexed by Troxler fading and adaptation-induced blindness, and at higher levels in the hierarchy indexed by attentional blinding effects in addition to the level indexed by the attentional blink. The full mapping of levels in the functional hierarchy onto cortical activation sites and levels is yet to be determined. The existence of such a hierarchy bears importantly on the search for, and the distinctions between, neural correlates of conscious and unconscious vision.