How do the brain's time and space mediate consciousness and its different dimensions? Temporo-spatial theory of consciousness (TTC)

The subjectivity of self and its ontology: From the world–brain relation to the point of view in the world

The search for the subjective nature of our self is intensely debated in philosophy and neuroscience. However, despite all progress, the subjectivity of self and how it fits into the seemingly objective world remains elusive. Drawing on recent empirical data, we show how the self is shaped by the brain’s scale-free activity, that is, long-range temporal correlation (LRTC) and the world’s ecological context. We assume that the scale-free LRTC of the world–brain relation provides the ontological basis for the point of view as the foundation of subjectivity within the world. We conclude that the temporal, that is, scale-free based point of view through the world–brain relation provides the ontologically necessary a posteriori condition for the subjectivity of self on a deeper neuro-ecological level. This extends phenomenological concepts like subjectivity and world beyond both Heidegger’s fundamental ontology and Sartre’s phenomenological ontology: it complements their subjectivity-based ontologies with a truly world-based ontology.

The neural hierarchy of consciousness

The chief undertaking in the studies of consciousness is that of unravelling "the minimal set of neural processes that are together sufficient for the conscious experience of a particular content - the neural correlates of consciousness". To this day, this crusade remains at an impasse, with a clash of two main theories: consciousness may arise either in a graded and cortically-localised fashion, or in an all-or-none and widespread one. In spite of the long-lasting theoretical debates, neurophysiological theories of consciousness have been mostly dissociated from them. Herein, a theoretical review will be put forth with the aim to change that. In its first half, we will cover the hard available evidence on the neurophysiology of consciousness, whereas in its second half we will weave a series of considerations on both theories and substantiate a novel take on conscious awareness: the levels of processing approach, partitioning the conscious architecture into lower- and higher-order, graded and nonlinear.

Alpha and theta peak frequency track on- and off-thoughts

Our thoughts are highly dynamic in their contents. At some points, our thoughts are related to external stimuli or tasks focusing on single content (on-single thoughts), While in other moments, they are drifting away with multiple simultaneous items as contents (off-multiple thoughts). Can such thought dynamics be tracked by corresponding neurodynamics? To address this question, here we track thought dynamics during post-stimulus periods by electroencephalogram (EEG) neurodynamics of alpha and theta peak frequency which, as based on the phase angle, must be distinguished from non-phase-based alpha and theta power. We show how, on the psychological level, on-off thoughts are highly predictive of single-multiple thought contents, respectively. Using EEG, on-single and off-multiple thoughts are mediated by opposite changes in the time courses of alpha (high in on-single but low in off-multiple thoughts) and theta (low in on-single but high in off-multiple thoughts) peak frequencies. In contrast, they cannot be distinguished by frequency power. Overall, these findings provide insight into how alpha and theta peak frequency with their phase-related processes track on- and off-thoughts dynamically. In short, neurodynamics track thought dynamics.

Anterior precuneus related to the recovery of consciousness

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Degree centrality of anterior precuneus correlated with Glasgow Outcome Scale scores.

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Anterior precuneus was shown as a hub in multiple recoverable unconscious states.

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Anterior precuneus had similar connectivity pattern in recoverable unconscious states.

The neural mechanism that enables the recovery of consciousness in patients with unresponsive wakefulness syndrome (UWS) remains unclear. The aim of the current study is to characterize the cortical hub regions related to the recovery of consciousness. In the current fMRI study, voxel-wise degree centrality analysis was adopted to identify the cortical hubs related to the recovery of consciousness, for which a total of 27 UWS patients were recruited, including 13 patients who emerged from UWS (UWS-E), and 14 patients who remained in UWS (UWS-R) at least three months after the experiment performance. Furthermore, other recoverable unconscious states were adopted as validation groups, including three independent N3 sleep datasets (n = 12, 9, 9 respectively) and three independent anesthesia datasets (n = 27, 14, 6 respectively). Spatial similarity of the hub characteristic with the validation groups between the UWS-E and UWS-R was compared using the dice coefficient. Finally, with the cortical regions persistently shown as hubs across UWS-E and validation states, functional connectivity analysis was further performed to explore the connectivity patterns underlying the recovery of consciousness. The results identified four cortical hubs in the UWS-E, which showed significantly higher degree centrality for UWS-E than UWS-R, including the anterior precuneus, left inferior parietal lobule, left inferior frontal gyrus, and left middle frontal gyrus, of which the degree centrality value also positively correlated with the patients’ Glasgow Outcome Scale (GOS) score that assessed global brain functioning outcome after a brain injury. Furthermore, the anterior precuneus was found with significantly higher similarity of hub characteristics as well as functional connectivity patterns between UWS-E and the validation groups. The results suggest that the recovery of consciousness may be relevant to the integrity of cortical hubs in the recoverable unconscious states, especially the anterior precuneus. The identified cortical hub regions could serve as potential treatment targets for patients with UWS.

Dynamic reconfiguration of human brain networks across altered states of consciousness

Consciousness is supported by rich neuronal dynamics to orchestrate behaviors and conscious processing can be disrupted by general anesthetics. Previous studies suggested that dynamic reconfiguration of large-scale functional network is critical for learning and higher-order cognitive function. During altered states of consciousness, how brain functional networks are dynamically changed and reconfigured at the whole-brain level is still unclear. To fill this gap, using multilayer network approach and functional magnetic resonance imaging (fMRI) data of 21 healthy subjects, we investigated the dynamic network reconfiguration in three different states of consciousness: wakefulness, dexmedetomidine-induced sedation, and recovery. Applying time-varying community detection algorithm, we constructed multilayer modularity networks to track and quantify dynamic interactions among brain areas that span time and space. We compared four high-level network features (i.e., switching, promiscuity, integration, and recruitment) derived from multilayer modularity across the three conditions. We found that sedation state is primarily characterized by increased switching rates as well as decreased integration, representing a whole-brain pattern with higher modular dynamics and more fragmented communication; such alteration can be mostly reversed after the recovery of consciousness. Thus, our work can provide additional insights to understand the modular network reconfiguration across different states of consciousness and may provide some clinical implications for disorders of consciousness.

From Shorter to Longer Timescales: Converging Integrated Information Theory (IIT) with the Temporo-Spatial Theory of Consciousness (TTC)

Time is a key element of consciousness as it includes multiple timescales from shorter to longer ones. This is reflected in our experience of various short-term phenomenal contents at discrete points in time as part of an ongoing, more continuous, and long-term ‘stream of consciousness.’ Can Integrated Information Theory (IIT) account for this multitude of timescales of consciousness? According to the theory, the relevant spatiotemporal scale for consciousness is the one in which the system reaches the maximum cause-effect power; IIT currently predicts that experience occurs on the order of short timescales, namely, between 100 and 300 ms (theta and alpha frequency range). This can well account for the integration of single inputs into a particular phenomenal content. However, such short timescales leave open the temporal relation of specific phenomenal contents to others during the course of the ongoing time, that is, the stream of consciousness. For that purpose, we converge the IIT with the Temporo-spatial Theory of Consciousness (TTC), which, assuming a multitude of different timescales, can take into view the temporal integration of specific phenomenal contents with other phenomenal contents over time. On the neuronal side, this is detailed by considering those neuronal mechanisms driving the non-additive interaction of pre-stimulus activity with the input resulting in stimulus-related activity. Due to their non-additive interaction, the single input is not only integrated with others in the short-term timescales of 100–300 ms (alpha and theta frequencies) (as predicted by IIT) but, at the same time, also virtually expanded in its temporal (and spatial) features; this is related to the longer timescales (delta and slower frequencies) that are carried over from pre-stimulus to stimulus-related activity. Such a non-additive pre-stimulus-input interaction amounts to temporo-spatial expansion as a key mechanism of TTC for the constitution of phenomenal contents including their embedding or nesting within the ongoing temporal dynamic, i.e., the stream of consciousness. In conclusion, we propose converging the short-term integration of inputs postulated in IIT (100–300 ms as in the alpha and theta frequency range) with the longer timescales (in delta and slower frequencies) of temporo-spatial expansion in TTC.

Temporo-spatial Theory of Consciousness (TTC) - Bridging the gap of neuronal activity and phenomenal states

Consciousness and its neural mechanisms remain a mystery. Current neuroscientific theories focus predominantly on the external input/stimulus and the associated stimulus-related activity during conscious contents. Despite all progress, we encounter two gaps: (i) a gap between spontaneous and stimulus-related activity; (ii) a gap between neuronal and phenomenal features. A novel, different, and unique approach, Temporo-spatial theory of consciousness (TTC) aims to bridge both gaps. The TTC focuses on the brain's spontaneous activity and how its spatial topography and temporal dynamic shape stimulus-related activity and resurface in the corresponding spatial and temporal features of consciousness, i.e., 'common currency'. The TTC introduces four temporo-spatial mechanisms: expansion, globalization, alignment, and nestedness. These are associated with distinct dimensions of consciousness including phenomenal content, access, form/structure, and level/state, respectively. Following up on the first introduction of the TTC in 2017, we review updates, further develop these temporo-spatial mechanisms, and postulate specific neurophenomenal hypotheses. We conclude that the TTC offers a viable approach for (i) linking spontaneous and stimulus-related activity in conscious states; (ii) determining specific neuronal and neurophenomenal mechanisms for the distinct dimensions of consciousness; (iii) an integrative and unifying framework of different neuroscientific theories of consciousness; and (iv) offers novel empirically grounded conceptual assumptions about the biological and ontological nature of consciousness and its relation to the brain.

Intrinsic neural timescales: temporal integration and segregation

We are continuously bombarded by external inputs of various timescales from the environment. How does the brain process this multitude of timescales? Recent resting state studies show a hierarchy of intrinsic neural timescales (INT) with a shorter duration in unimodal regions (e.g., visual cortex and auditory cortex) and a longer duration in transmodal regions (e.g., default mode network). This unimodal-transmodal hierarchy is present across acquisition modalities [electroencephalogram (EEG)/magnetoencephalogram (MEG) and fMRI] and can be found in different species and during a variety of different task states. Together, this suggests that the hierarchy of INT is central to the temporal integration (combining successive stimuli) and segregation (separating successive stimuli) of external inputs from the environment, leading to temporal segmentation and prediction in perception and cognition.

Evolutionary origin and the development of consciousness

This review seeks to combine advances in anthropology and neuroscience to investigate the adaptive value of human consciousness. It uses an interdisciplinary perspective on the origin of consciousness to refute the most common fallacies in considering consciousness, particularly, disregarding the evolutionary origin of the subjective reality in looking for the neural correlates of consciousness and divorcing studies in neuroscience and behavioural sciences. Various explanations linked to consciousness in the field of neuroscience, supplemented with the theoretical explanation of an experience as an ongoing process of overlap between intrinsic neural dynamics and stimulation can be summarised as the stochastic dynamics of one's control system experienced by the individual in the form of subjective reality. This framework elaborates on the world-brain research program and lays foundation for the quantitative description of one's qualitative feelings and naturalistic science of consciousness. Furthermore, this study highlights the philosophical perspective of the inseparability between the physical correlates and the subjective reality contributing to the realistic ontology of conscious processes.

Representational 'touch' and modulatory 'retouch'-two necessary neurobiological processes in thalamocortical interaction for conscious experience

Theories of consciousness using neurobiological data or being influenced by these data have been focused either on states of consciousness or contents of consciousness. These theories have occasionally used evidence from psychophysical phenomena where conscious experience is a dependent experimental variable. However, systematic catalog of many such relevant phenomena has not been offered in terms of these theories. In the perceptual retouch theory of thalamocortical interaction, recently developed to become a blend with the dendritic integration theory, consciousness states and contents of consciousness are explained by the same mechanism. This general-purpose mechanism has modulation of the cortical layer-5 pyramidal neurons that represent contents of consciousness as its core. As a surplus, many experimental psychophysical phenomena of conscious perception can be explained by the workings of this mechanism. Historical origins and current views inherent in this theory are presented and reviewed.

Residual implicit and explicit language abilities in patients with disorders of consciousness: A systematic review

Language assessment in post-comatose patients is difficult due to their limited behavioral repertoire; yet associated language deficits might lead to an underestimation of consciousness levels in unresponsive wakefulness syndrome (UWS) or minimally conscious state (MCS; -/+) diagnoses. We present a systematic review of studies from 2002 assessing residual language abilities with neuroimaging, electrophysiological or behavioral measures in patients with severe brain injury. Eighty-five articles including a total of 2278 patients were assessed for quality. The median percentages of patients showing residual implicit language abilities (i.e., cortical responses to specific words/sentences) were 33 % for UWS, 50 % for MCS- and 78 % for MCS + patients, whereas explicit language abilities (i.e., command-following using brain-computer interfaces) were reported in 20 % of UWS, 33 % of MCS- and 50 % of MCS + patients. Cortical responses to verbal stimuli increased along with consciousness levels and the progressive recovery of consciousness after a coma was paralleled by the reappearance of both implicit and explicit language processing. This review highlights the importance of language assessment in patients with disorders of consciousness.

A reduced level of consciousness affects non-conscious processes

Being conscious is a profound aspect of human existence, and understanding its function and its inception is considered one of the truly grand scientific challenges. However, the nature of consciousness remains enigmatic, to a large part because "being conscious" can refer to both the content (phenomenology) and the level (arousal) of consciousness, and how these different aspects are related remains unclear. To empirically assess the relation between level and content of consciousness, we manipulated these two aspects by presenting stimuli consciously or non-consciously and by using Propofol sedation, while brain activity was measured using fMRI. We observed that sedation affected both conscious and non-conscious processes but at different hierarchical levels; while conscious processing was altered in higher-order regions (the intraparietal sulcus) and spared sensory areas, the opposite effect was observed for non-conscious processing. The observation that Propofol affected non-conscious processing calls for a reconsideration of what kind of information one can gain on "consciousness" from recording neural responses to sedation without considering both (content) conscious and (content) non-conscious processing.

The Temporally-Integrated Causality Landscape: Reconciling Neuroscientific Theories With the Phenomenology of Consciousness

In recent years, there has been a proliferation of neuroscientific theories of consciousness. These include theories which explicitly point to EM fields, notably Operational Architectonics and, more recently, the General Resonance Theory. In phenomenological terms, human consciousness is a unified composition of contents. These contents are specific and meaningful, and they exist from a subjective point of view. Human conscious experience is temporally continuous, limited in content, and coherent. Based upon those phenomenal observations, pre-existing theories of consciousness, and a large body of experimental evidence, I derived the Temporally-Integrated Causality Landscape (TICL). In brief, the TICL proposes that the neural correlate of consciousness is a structure of temporally integrated causality occurring over a large portion of the thalamocortical system. This structure is composed of a large, integrated set of neuronal elements (the System), which contains some subsystems, defined as having a higher level of temporally-integrated causality than the System as a whole. Each Subsystem exists from the point of view of the System, in the form of meaningful content. In this article, I review the TICL and consider the importance of EM forces as a mechanism of neural causality. I compare the fundamentals of TICL to those of several other neuroscientific theories. Using five major characteristics of phenomenal consciousness as a standard, I compare the basic tenets of Integrated Information Theory, Global Neuronal Workspace, General Resonance Theory, Operational Architectonics, and the Temporo-spatial Theory of Consciousness with the framework of the TICL. While the literature concerned with these theories tends to focus on different lines of evidence, there are fundamental areas of agreement. This means that, in time, it may be possible for many of them to converge upon the truth. In this analysis, I conclude that a primary distinction which divides these theories is the feature of spatial and temporal nesting. Interestingly, this distinction does not separate along the fault line between theories explicitly concerned with EM fields and those which are not. I believe that reconciliation is possible, at least in principle, among those theories that recognize the following: just as the contents of consciousness are distinctions within consciousness, the neural correlates of conscious content should be distinguishable from but fall within the spatial and temporal boundaries of the full neural correlates of consciousness.

Expanding the discussion: Revision of the fundamental assumptions framing the study of the neural correlates of consciousness

The way one asks a question is shaped by a-priori assumptions and constrains the range of possible answers. We identify and test the assumptions underlying contemporary debates, models, and methodology in the study of the neural correlates of consciousness, which was framed by Crick and Koch's seminal paper (1990). These premises create a sequential and passive conception of conscious perception: it is considered the product of resolved information processing by unconscious mechanisms, produced by a singular event in time and place representing the moment of entry. The conscious percept produced is then automatically retained to be utilized by post-conscious mechanisms. Major debates in the field, such as concern the moment of entry, the all-or-none vs graded nature, and report vs no-report paradigms, are driven by the consensus on these assumptions. We show how removing these assumptions can resolve some of the debates and challenges and prompt additional questions. The potential non-sequential nature of perception suggests new ways of thinking about consciousness as a dynamic and dispersed process, and in turn about the relationship between conscious and unconscious perception. Moreover, it allows us to present a parsimonious account for conscious perception while addressing more aspects of the phenomenon.

'Consciousnessoids': clues and insights from human cerebral organoids for the study of consciousness

Human cerebral organoids (HCOs) are an in vitro three-dimensional model of early neural development, aimed at modelling and understanding brain development and neurological disorders. In just a few years, there has been a rapid and considerable progress in the attempt to create a brain model capable of showcasing the structure and functions of the human brain. There are still strong limitations to address, including the absence of vascularization that makes it difficult to feed the central layers of organoids. Nevertheless, some important features of the nervous system have recently been observed: HCOs manifest electrical activity, are sensitive to light stimulation and are able to connect to a spinal cord by sending impulses that make a muscle contract. Recent data show that cortical organoid network development at 10 months resembles some preterm babies' electroencephalography (EEG) patterns. In the light of the fast pace of research in this field, one might consider the hypothesis that HCOs might become a living laboratory for studying the emergence of consciousness and investigating its mechanisms and neural correlates. HCOs could be also a benchmark for different neuroscientific theories of consciousness. In this paper, I propose some potential lines of research and offer some clues and insights so as to use HCOs in trying to unveil some puzzles concerning our conscious states. Finally, I consider some relevant ethical issues regarding this specific experimentation on HCOs and conclude that some of them could require strict regulation in this field.

Comparing stimulus-evoked and spontaneous response of the face-selective multi-units in the human posterior fusiform gyrus

The stimulus-evoked neural response is a widely explored phenomenon. Conscious awareness is associated in many cases with the corresponding selective stimulus-evoked response. For example, conscious awareness of a face stimulus is associated with or accompanied by stimulus-evoked activity in the fusiform face area (FFA). In addition to the stimulus-evoked response, spontaneous (i.e. task-unrelated) activity in the brain is also abundant. Notably, spontaneous activity is considered unconscious. For example, spontaneous activity in the FFA is not associated with conscious awareness of a face. The question is: what is the difference at the neural level between stimulus-evoked activity in a case that this activity is associated with conscious awareness of some content (e.g. activity in the FFA in response to fully visible face stimuli) and spontaneous activity in that same region of the brain? To answer this question, in the present study, we had a rare opportunity to record two face-selective multi-units in the vicinity of the FFA in a human patient. We compared multi-unit face-selective task-evoked activity with spontaneous prestimulus and a resting-state activity. We found that when activity was examined over relatively long temporal windows (e.g. 100–200 ms), face-selective stimulus-evoked firing in the recorded multi-units was much higher than the spontaneous activity. In contrast, when activity was examined over relatively short windows, we found many cases of high firing rates within the spontaneous activity that were comparable to stimulus-evoked activity. Our results thus indicate that the sustained activity is what might differentiate between stimulus-evoked activity that is associated with conscious awareness and spontaneous activity.

A relational approach to consciousness: categories of level and contents of consciousness

Characterizing consciousness in and of itself is notoriously difficult. Here, we propose an alternative approach to characterize, and eventually define, consciousness through exhaustive descriptions of consciousness' relationships to all other consciousness. This approach is founded in category theory. Indeed, category theory can prove that two objects A and B in a category can be equivalent if and only if all the relationships that A holds with others in the category are the same as those of B; this proof is called the Yoneda lemma. To introduce the Yoneda lemma, we gradually introduce key concepts of category theory to consciousness researchers. Along the way, we propose several possible definitions of categories of consciousness, both in terms of level and contents, through the usage of simple examples. We propose to use the categorical structure of consciousness as a gold standard to formalize empirical research (e.g. color qualia structure at fovea and periphery) and, especially, the empirical testing of theories of consciousness.

"Project for a Spatiotemporal Neuroscience" - Brain and Psyche Share Their Topography and Dynamic

What kind of neuroscience does psychoanalysis require? At his time, Freud in his "Project for a Scientific Psychology" searched for a model of the brain that could relate to incorporate the psyche's topography and dynamic. Current neuropsychoanalysis builds on specific functions as investigated in Affective and Cognitive (and Social) Neuroscience including embodied approaches. The brain's various functions are often converged with prediction as operationalized in predictive coding (PC) and free energy principle (FEP) which, recently, have been conceived as core for a "New Project for Scientific Psychology." We propose to search for a yet more comprehensive and holistic neuroscience that focuses primarily on its topography and dynamic analogous to Freud's model of the psyche. This leads us to what we describe as "Spatiotemporal Neuroscience" that focuses on the spatial topography and temporal dynamic of the brain's neural activity including how they shape affective, cognitive, and social functions including PC and FEP (first part). That is illustrated by the temporally and spatially nested neural hierarchy of the self in the brain's neural activity (second and third part). This sets the ground for developing our proposed "Project for a Spatiotemporal Neuroscience," which complements and extends both Freud's and Solms' projects (fourth part) and also carries major practical implications as it lays the ground for a novel form of neuroscientifically informed psychotherapy, namely, "Spatiotemporal Psychotherapy." In conclusion, "Spatiotemporal Neuroscience" provides an intimate link of brain and psyche by showing topography and dynamic as their shared features, that is, "common currency."

Explanatory profiles of models of consciousness - towards a systematic classification

Models of consciousness aim to inspire new experimental protocols and aid interpretation of empirical evidence to reveal the structure of conscious experience. Nevertheless, no current model is univocally accepted on either theoretical or empirical grounds. Moreover, a straightforward comparison is difficult for conceptual reasons. In particular, we argue that different models explicitly or implicitly subscribe to different notions of what constitutes a satisfactory explanation, use different tools in their explanatory endeavours and even aim to explain very different phenomena. We thus present a framework to compare existing models in the field with respect to what we call their 'explanatory profiles'. We focus on the following minimal dimensions: mode of explanation, mechanisms of explanation and target of explanation. We also discuss the empirical consequences of the discussed discrepancies among models. This approach may eventually lead to identifying driving assumptions, theoretical commitments, experimental predictions and a better design of future testing experiments. Finally, our conclusion points to more integrative theoretical research, where axiomatic models may play a critical role in solving current theoretical and experimental contradictions.

The brain and its time: intrinsic neural timescales are key for input processing

We process and integrate multiple timescales into one meaningful whole. Recent evidence suggests that the brain displays a complex multiscale temporal organization. Different regions exhibit different timescales as described by the concept of intrinsic neural timescales (INT); however, their function and neural mechanisms remains unclear. We review recent literature on INT and propose that they are key for input processing. Specifically, they are shared across different species, i.e., input sharing. This suggests a role of INT in encoding inputs through matching the inputs' stochastics with the ongoing temporal statistics of the brain's neural activity, i.e., input encoding. Following simulation and empirical data, we point out input integration versus segregation and input sampling as key temporal mechanisms of input processing. This deeply grounds the brain within its environmental and evolutionary context. It carries major implications in understanding mental features and psychiatric disorders, as well as going beyond the brain in integrating timescales into artificial intelligence.

Dreaming the unrepressed unconscious and beyond: repression vs dissociation in the oneiric functioning of severe patients

Starting with Freud and Jung, dreams have always been considered a core source of information for psychoanalysis. Nowadays, neuroscientific findings suggest that dreams are related especially to limbic and right emotional brain circuit, and that during REM stages they engage self-related and visual internally generated processing. These neuroscientific findings together with contemporary psychoanalysis suggest that dreams are related to the sense of self and serve the purpose of re-integrating and re-structuring the integrity of the psyche. However, while dreams are still viewed as 'the via regia to the unconscious', it is the unconscious that has been reconsidered. The repressed unconscious seems to be related with left brain activity while the unrepressed unconscious based on dissociation seems to be associated with limbic and cortical areas of the right hemisphere. This notion of the unconscious might be seen as an implicit self-system encoded in the right brain that evolves in the interaction with a primary caregiver developing through preverbal and bodily stages of maturation enhanced by signals of dual communication. What kind of dreams for which unconscious? What are the differences regarding the capacity to dream for neurotic and borderline personality organizations? Our research aims to integrate psychodynamics, infant research, and neuroscientific findings to better understand the role of dreams in the assessment and treatment of, especially, traumatized and borderline patients. The capacity to dream is here proposed as a sort of enacted manifestation of emotional memories for the development of a more cohesive, coherent and symbolic vs fragmented, diffuse and alexithymic sense of self.

How Energy Supports Our Brain to Yield Consciousness: Insights From Neuroimaging Based on the Neuroenergetics Hypothesis

Consciousness is considered a result of specific neuronal processes and mechanisms in the brain. Various suggested neuronal mechanisms, including the information integration theory (IIT), global neuronal workspace theory (GNWS), and neuronal construction of time and space as in the context of the temporospatial theory of consciousness (TTC), have been laid forth. However, despite their focus on different neuronal mechanisms, these theories neglect the energetic-metabolic basis of the neuronal mechanisms that are supposed to yield consciousness. Based on the findings of physiology-induced (sleep), pharmacology-induced (general anesthesia), and pathology-induced [vegetative state/unresponsive wakeful syndrome (VS/UWS)] loss of consciousness in both human subjects and animals, we, in this study, suggest that the energetic-metabolic processes focusing on ATP, glucose, and γ-aminobutyrate/glutamate are indispensable for functional connectivity (FC) of normal brain networks that renders consciousness possible. Therefore, we describe the energetic-metabolic predispositions of consciousness (EPC) that complement the current theories focused on the neural correlates of consciousness (NCC).

Brain-Heart Interactions Underlying Traditional Tibetan Buddhist Meditation

Despite accumulating evidence suggesting improvement in one's well-being as a result of meditation, little is known about if or how the brain and the periphery interact to produce these behavioral and mental changes. We hypothesize that meditation reflects changes in the neural representations of visceral activity, such as cardiac behavior, and investigated the integration of neural and visceral systems and the spontaneous whole brain spatiotemporal dynamics underlying traditional Tibetan Buddhist meditation. In a large cohort of long-term Tibetan Buddhist monk meditation practitioners, we found distinct transient modulations of the neural response to heartbeats in the default mode network (DMN), along with large-scale network reconfigurations in the gamma and theta bands of electroencephalography (EEG) activity induced by meditation. Additionally, temporal-frontal network connectivity in the EEG theta band was negatively correlated with the duration of meditation experience, and gamma oscillations were uniquely, directionally coupled to theta oscillations during meditation. Overall, these data suggest that the neural representation of cardiac activity in the DMN and large-scale spatiotemporal network integrations underlie the fundamental neural mechanism of meditation and further imply that meditation may utilize cortical plasticity, inducing both immediate and long-lasting changes in the intrinsic organization and activity of brain networks.

Dynamic relationships between spontaneous and evoked electrophysiological activity

Spontaneous neural activity fluctuations have been shown to influence trial-by-trial variation in perceptual, cognitive, and behavioral outcomes. However, the complex electrophysiological mechanisms by which these fluctuations shape stimulus-evoked neural activity remain largely to be explored. Employing a large-scale magnetoencephalographic dataset and an electroencephalographic replication dataset, we investigate the relationship between spontaneous and evoked neural activity across a range of electrophysiological variables. We observe that for high-frequency activity, high pre-stimulus amplitudes lead to greater evoked desynchronization, while for low frequencies, high pre-stimulus amplitudes induce larger degrees of event-related synchronization. We further decompose electrophysiological power into oscillatory and scale-free components, demonstrating different patterns of spontaneous-evoked correlation for each component. Finally, we find correlations between spontaneous and evoked time-domain electrophysiological signals. Overall, we demonstrate that the dynamics of multiple electrophysiological variables exhibit distinct relationships between their spontaneous and evoked activity, a result which carries implications for experimental design and analysis in non-invasive electrophysiology.

Out-of-step: brain-heart desynchronization in anxiety disorders

Imaging studies in anxiety disorders (AD) show abnormal functional connectivity primarily in the salience network (SN), somatomotor network (SMN), and default mode network (DMN). However, it is not clear how precisely these network changes occur including their relation to psychopathological symptoms. Here, we show that the functional networks affected in AD overlap with cortical regions that receive visceral inputs (the so-called central/visceral autonomic network). Focusing on cardiac afferents, we suggest that network changes in AD may be due to reduced phase synchronization between ongoing neural and cardiac activity. This neuro-cardiac desynchronization occurs due to the abnormal phase resetting of neural activity at the onset of each heartbeat, as measured by a lower intertrial coherence and heartbeat-evoked potential. Biochemically, cardiac afferents reach subcortical serotonergic raphe nuclei and noradrenergic locus coeruleus (among others) which, in turn, are known to reciprocally modulate the DMN and SMN/SN on the cortical level. Consistent with the network changes in AD, decreases in serotonergic and noradrenergic activity are known to increase connectivity in both SMN and SN while, at the same time, they decrease DMN connectivity. SMN and SN increases, in turn, lead to increased emotional arousal/anxiety and bodily awareness whereas decreased DMN connectivity leads to an unstable sense-of-self in AD. Finally, we integrate our proposal with interoceptive predictive processing models suggesting neuro-cardiac desynchronization as a mechanism for "noisy" bottom-up information leading to a persistently uncertain bodily state in top-down models. In sum, integrating theories on active interference and hyperarousal, we propose a precise neuro-cardiac and biochemically -driven mechanisms for key psychopathological symptoms of AD.

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.

Anterior insula regulates brain network transitions that gate conscious access

Conscious access to sensory information is likely gated at an intermediate site between primary sensory and transmodal association cortices, but the structure responsible remains unknown. We perform functional neuroimaging to determine the neural correlates of conscious access using a volitional mental imagery task, a report paradigm not confounded by motor behavior. Titrating propofol to loss of behavioral responsiveness in healthy volunteers creates dysfunction of the anterior insular cortex (AIC) in association with an impairment of dynamic transitions of default-mode and dorsal attention networks. Candidate subcortical regions mediating sensory gating or arousal (thalamus, basal forebrain) fail to show this association. The gating role of the AIC is consistent with findings in awake participants, whose conscious access is predicted by pre-stimulus AIC activity near perceptual threshold. These data support the hypothesis that AIC, situated at an intermediate position of the cortical hierarchy, regulates brain network transitions that gate conscious access.

In a human neuroimaging study, Huang et al. manipulate the level and content of consciousness using independent experimental protocols to demonstrate that the anterior insula, situated between unimodal and transmodal cortical areas along the brain’s functional hierarchy, serves as a gate for conscious access of sensory information.

Overcoming Rest-Task Divide-Abnormal Temporospatial Dynamics and Its Cognition in Schizophrenia

Schizophrenia is a complex psychiatric disorder exhibiting alterations in spontaneous and task-related cerebral activity whose relation (termed "state dependence") remains unclear. For unraveling their relationship, we review recent electroencephalographic (and a few functional magnetic resonance imaging) studies in schizophrenia that assess and compare both rest/prestimulus and task states, ie, rest/prestimulus-task modulation. Results report reduced neural differentiation of task-related activity from rest/prestimulus activity across different regions, neural measures, cognitive domains, and imaging modalities. Together, the findings show reduced rest/prestimulus-task modulation, which is mediated by abnormal temporospatial dynamics of the spontaneous activity. Abnormal temporospatial dynamics, in turn, may lead to abnormal prediction, ie, predictive coding, which mediates cognitive changes and psychopathological symptoms, including confusion of internally and externally oriented cognition. In conclusion, reduced rest/prestimulus-task modulation in schizophrenia provides novel insight into the neuronal mechanisms that connect task-related changes to cognitive abnormalities and psychopathological symptoms.

Special Issue: Consciousness science and its theories Time consciousness: the missing link in theories of consciousness

There are plenty of issues to be solved in order for researchers to agree on a neural model of consciousness. Here we emphasize an often under-represented aspect in the debate: time consciousness. Consciousness and the present moment both extend in time. Experience flows through a succession of moments and progresses from future predictions, to present experiences, to past memories. However, a brief review finds that many dominant theories of consciousness only refer to brief, static, and discrete "functional moments" of time. Very few refer to more extended, dynamic, and continuous time, which is associated with conscious experience (cf. the "experienced moment"). This confusion between short and discrete versus long and continuous is, we argue, one of the core issues in theories of consciousness. Given the lack of work dedicated to time consciousness, its study could test novel predictions of rival theories of consciousness. It may be that different theories of consciousness are compatible/complementary if the different aspects of time are taken into account. Or, if it turns out that no existing theory can fully accommodate time consciousness, then perhaps it has something new to add. Regardless of outcome, the crucial step is to make subjective time a central object of study.

Brain Entropy During Aging Through a Free Energy Principle Approach

Neural complexity and brain entropy (BEN) have gained greater interest in recent years. The dynamics of neural signals and their relations with information processing continue to be investigated through different measures in a variety of noteworthy studies. The BEN of spontaneous neural activity decreases during states of reduced consciousness. This evidence has been showed in primary consciousness states, such as psychedelic states, under the name of "the entropic brain hypothesis." In this manuscript we propose an extension of this hypothesis to physiological and pathological aging. We review this particular facet of the complexity of the brain, mentioning studies that have investigated BEN in primary consciousness states, and extending this view to the field of neuroaging with a focus on resting-state functional Magnetic Resonance Imaging. We first introduce historic and conceptual ideas about entropy and neural complexity, treating the mindbrain as a complex nonlinear dynamic adaptive system, in light of the free energy principle. Then, we review the studies in this field, analyzing the idea that the aim of the neurocognitive system is to maintain a dynamic state of balance between order and chaos, both in terms of dynamics of neural signals and functional connectivity. In our exploration we will review studies both on acute psychedelic states and more chronic psychotic states and traits, such as those in schizophrenia, in order to show the increase of entropy in those states. Then we extend our exploration to physiological and pathological aging, where BEN is reduced. Finally, we propose an interpretation of these results, defining a general trend of BEN in primary states and cognitive aging.

Temporal hierarchy of intrinsic neural timescales converges with spatial core-periphery organization

The human cortex exhibits intrinsic neural timescales that shape a temporal hierarchy. Whether this temporal hierarchy follows the spatial hierarchy of its topography, namely the core-periphery organization, remains an open issue. Using magnetoencephalography data, we investigate intrinsic neural timescales during rest and task states; we measure the autocorrelation window in short (ACW-50) and, introducing a novel variant, long (ACW-0) windows. We demonstrate longer ACW-50 and ACW-0 in networks located at the core compared to those at the periphery with rest and task states showing a high ACW correlation. Calculating rest-task differences, i.e., subtracting the shared core-periphery organization, reveals task-specific ACW changes in distinct networks. Finally, employing kernel density estimation, machine learning, and simulation, we demonstrate that ACW-0 exhibits better prediction in classifying a region's time window as core or periphery. Overall, our findings provide fundamental insight into how the human cortex's temporal hierarchy converges with its spatial core-periphery hierarchy.

Visual fixation in disorders of consciousness: Development of predictive models to support differential diagnosis

The visual fixation represents a doubtful behavioral sign to discriminate Vegetative from Minimally Conscious State (MCS). To disentangle its meaning, we fitted univariate and multivariable logistic regression models matching different neurophysiological and neuroimaging data of 54 patients with Disorders of Consciousness to select the best model predicting which visual performance (visual blink or pursuit) was shown by patients and the best predictors set. The best models found highlighted the importance of the structural MRI and the visual evoked potentials data in predicting visual pursuit. Then, a qualitative pilot test was made on four patients showing visual fixation revealing that the obtained models correctly predict whether the patients' visual performance could support/correlate to a cognitively mediated behavior. The present pilot models could help clinicians to evaluate if the visual fixation response can support the MCS diagnosis.

The neural correlates of the visual consciousness in schizophrenia: an fMRI study

In the current literature, two distinct and opposite models are suggested to explain the consciousness disorders in schizophrenia. The first one suggests that consciousness disorders rely on a low-level processing deficit, when the second model suggests that consciousness disorders rely on disruption in the ability to consciously access information, with preserved unconscious processing. The current study aims to understand the mechanisms associated with visual consciousness disorder in order to pave the road that will settle the debate regarding these hypotheses. During a functional magnetic resonance imaging session, 19 healthy participants (HC) and 15 patients with schizophrenia (SCZ) performed a visual detection task to compare the neural substrates associated with the conscious access to the visual inputs. The visual detection threshold was significantly higher in SCZ than in HC [t(32) = 3.37, p = 0.002]. Whole-brain ANOVA demonstrated that around the visual detection threshold patients with SCZ failed to activate a large network of brain areas compared to HC. (1) During conscious vision, HC engaged more the left cuneus and the right occipital cortex than patients with SCZ, (2) during unconscious vision, HC engaged a large network that patients with SCZ failed to activate, and finally, (3) during the access to consciousness process, patients with SCZ failed to activate the anterior cingulate cortex. These results suggest that the consciousness disorders in schizophrenia rely on specific dysfunctions depending on the consciousness stage. The disorders of the conscious vision are associated with dysfunction of occipital areas while the ones associated with unconscious vision rely on a large widespread network. Finally, the conscious access to the visual inputs is impaired by a dysfunction of the anterior cingulate cortex. The current study suggests that none of the two suggested models can explain consciousness disorders in schizophrenia. We suggest that there is an alternative model supporting that the conscious access to visual inputs is due to a disengagement of the supragenual anterior cingulate during the unconscious processing of the visual inputs associated with a sensory deficit.

All roads lead to the motor cortex: psychomotor mechanisms and their biochemical modulation in psychiatric disorders

Psychomotor abnormalities have been abundantly observed in psychiatric disorders like major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCH). Although early psychopathological descriptions highlighted the truly psychomotor nature of these abnormalities, more recent investigations conceive them rather in purely motor terms. This has led to an emphasis of dopamine-based abnormalities in subcortical-cortical circuits including substantia nigra, basal ganglia, thalamus, and motor cortex. Following recent findings in MDD, BD, and SCH, we suggest a concept of psychomotor symptoms in the literal sense of the term by highlighting three specifically psychomotor (rather than motor) mechanisms including their biochemical modulation. These include: (i) modulation of dopamine- and substantia nigra-based subcortical-cortical motor circuit by primarily non-motor subcortical raphe nucleus and serotonin via basal ganglia and thalamus (as well as by other neurotransmitters like glutamate and GABA); (ii) modulation of motor cortex and motor network by non-motor cortical networks like default-mode network and sensory networks; (iii) global activity in cortex may also shape regional distribution of neural activity in motor cortex. We demonstrate that these three psychomotor mechanisms and their underlying biochemical modulation are operative in both healthy subjects as well as in MDD, BD, and SCH subjects; the only difference consists in the fact that these mechanisms are abnormally balanced and thus manifest in extreme values in psychiatric disorders. We conclude that psychomotor mechanisms operate in a dimensional and cross-nosological way as their degrees of expression are related to levels of psychomotor activity (across different disorders) rather than to the diagnostic categories themselves. Psychomotor mechanisms and their biochemical modulation can be considered paradigmatic examples of a dimensional approach as suggested in RDoC and the recently introduced spatiotemporal psychopathology.

Hierarchical disruption in the cortex of anesthetized monkeys as a new signature of consciousness loss

Anesthesia induces a reconfiguration of the repertoire of functional brain states leading to a high function-structure similarity. However, it is unclear how these functional changes lead to loss of consciousness. Here we suggest that the mechanism of conscious access is related to a general dynamical rearrangement of the intrinsic hierarchical organization of the cortex. To measure cortical hierarchy, we applied the Intrinsic Ignition analysis to resting-state fMRI data acquired in awake and anesthetized macaques. Our results reveal the existence of spatial and temporal hierarchical differences of neural activity within the macaque cortex, with a strong modulation by the depth of anesthesia and the employed anesthetic agent. Higher values of Intrinsic Ignition correspond to rich and flexible brain dynamics whereas lower values correspond to poor and rigid, structurally driven brain dynamics. Moreover, spatial and temporal hierarchical dimensions are disrupted in a different manner, involving different hierarchical brain networks. All together suggest that disruption of brain hierarchy is a new signature of consciousness loss.

The Self and Its Nature: A Psychopathological Perspective on the Risk-Reducing Effects of Environmental Green Space for Psychosis

Epidemiological studies have shown that environmental green space contributes to the reduction of psychosis incidence in the population. Clarifying the psychological and neuro-functional mechanisms underlying the risk-decreasing effects of green surroundings could help optimize preventive environmental interventions. This perspective article specifically aims to open a new window on the link between environmental green space and psychosis by considering its core psychopathological features. Psychotic disorders, such as schizophrenia, are essentially characterized by self-disturbances. The psychological structure of the self has been described as a multidimensional phenomenon that emerges from the reciprocal interaction with the environment through intrinsic and extrinsic self-processes. The intrinsic self refers to the experience of mental activity and environmental information as inherently related to one’s own person, which involves self-referential processing, self-reflection, memory, interoception, and emotional evaluation. The extrinsic self refers to sensorimotor interactions with the environment and the sense of agency, that is, the experience of being the source of one’s own actions and the multisensory consequences thereof. In psychosis, anomalous self-processing has been related to a functional fragmentation of intrinsic and extrinsic self-processes and related brain networks. Moreover, evidence from cognitive neuroscience suggests that green space could have beneficial effects on self-related processing. Based on the literature, it could be hypothesized that self-processing is involved in mediating the beneficial effects of green space for psychosis. Considering the multidimensionality of the self, it is proposed that urban green space design aimed at improving mental health ideally impacts the complexity of self-facets and thus restores the individual’s self.

Human cerebral organoids and consciousness: a double-edged sword

Human cerebral organoids (HCOs) are three-dimensional in vitro cell cultures that mimic the developmental process and organization of the developing human brain. In just a few years this technique has produced brain models that are already being used to study diseases of the nervous system and to test treatments and drugs. Currently, HCOs consist of tens of millions of cells and have a size of a few millimeters. The greatest limitation to further development is due to their lack of vascularization. However, recent research has shown that human cerebral organoids can manifest the same electrical activity and connections between brain neurons and EEG patterns as those recorded in preterm babies. All this suggests that, in the future, HCOs may manifest an ability to experience basic sensations such as pain, therefore manifesting sentience, or even rudimentary forms of consciousness. This calls for consideration of whether cerebral organoids should be given a moral status and what limitations should be introduced to regulate research. In this article I focus particularly on the study of the emergence and mechanisms of human consciousness, i.e. one of the most complex scientific problems there are, by means of experiments on HCOs. This type of experiment raises relevant ethical issues and, as I will argue, should probably not be considered morally acceptable.

Disruption of Conscious Access in Psychosis Is Associated with Altered Structural Brain Connectivity

According to global neuronal workspace (GNW) theory, conscious access relies on long-distance cerebral connectivity to allow a global neuronal ignition coding for conscious content. In patients with schizophrenia and bipolar disorder, both alterations in cerebral connectivity and an increased threshold for conscious perception have been reported. The implications of abnormal structural connectivity for disrupted conscious access and the relationship between these two deficits and psychopathology remain unclear. The aim of this study was to determine the extent to which structural connectivity is correlated with consciousness threshold, particularly in psychosis. We used a visual masking paradigm to measure consciousness threshold, and diffusion MRI tractography to assess structural connectivity in 97 humans of either sex with varying degrees of psychosis: healthy control subjects (n = 46), schizophrenia patients (n = 25), and bipolar disorder patients with (n = 17) and without (n = 9) a history of psychosis. Patients with psychosis (schizophrenia and bipolar disorder with psychotic features) had an elevated masking threshold compared with control subjects and bipolar disorder patients without psychotic features. Masking threshold correlated negatively with the mean general fractional anisotropy of white matter tracts exclusively within the GNW network (inferior frontal-occipital fasciculus, cingulum, and corpus callosum). Mediation analysis demonstrated that alterations in long-distance connectivity were associated with an increased masking threshold, which in turn was linked to psychotic symptoms. Our findings support the hypothesis that long-distance structural connectivity within the GNW plays a crucial role in conscious access, and that conscious access may mediate the association between impaired structural connectivity and psychosis.

Are intrinsic neural timescales related to sensory processing? Evidence from abnormal behavioral states

The brain exhibits a complex temporal structure which translates into a hierarchy of distinct neural timescales. An open question is how these intrinsic timescales are related to sensory or motor information processing and whether these dynamics have common patterns in different behavioral states. We address these questions by investigating the brain's intrinsic timescales in healthy controls, motor (amyotrophic lateral sclerosis, locked-in syndrome), sensory (anesthesia, unresponsive wakefulness syndrome), and progressive reduction of sensory processing (from awake states over N1, N2, N3). We employed a combination of measures from EEG resting-state data: auto-correlation window (ACW), power spectral density (PSD), and power-law exponent (PLE). Prolonged neural timescales accompanied by a shift towards slower frequencies were observed in the conditions with sensory deficits, but not in conditions with motor deficits. Our results establish that the spontaneous activity's intrinsic neural timescale is related to the neural capacity that specifically supports sensory rather than motor information processing in the healthy brain.

Altered Global Brain Signal during Physiologic, Pharmacologic, and Pathologic States of Unconsciousness in Humans and Rats

BACKGROUND

Consciousness is supported by integrated brain activity across widespread functionally segregated networks. The functional magnetic resonance imaging-derived global brain signal is a candidate marker for a conscious state, and thus the authors hypothesized that unconsciousness would be accompanied by a loss of global temporal coordination, with specific patterns of decoupling between local regions and global activity differentiating among various unconscious states.

METHODS

Functional magnetic resonance imaging global signals were studied in physiologic, pharmacologic, and pathologic states of unconsciousness in human natural sleep (n = 9), propofol anesthesia (humans, n = 14; male rats, n = 12), and neuropathological patients (n = 21). The global signal amplitude as well as the correlation between global signal and signals of local voxels were quantified. The former reflects the net strength of global temporal coordination, and the latter yields global signal topography.

RESULTS

A profound reduction of global signal amplitude was seen consistently across the various unconscious states: wakefulness (median [1st, 3rd quartile], 0.46 [0.21, 0.50]) versus non-rapid eye movement stage 3 of sleep (0.30 [0.24, 0.32]; P = 0.035), wakefulness (0.36 [0.31, 0.42]) versus general anesthesia (0.25 [0.21, 0.28]; P = 0.001), healthy controls (0.30 [0.27, 0.37]) versus unresponsive wakefulness syndrome (0.22 [0.15, 0.24]; P < 0.001), and low dose (0.07 [0.06, 0.08]) versus high dose of propofol (0.04 [0.03, 0.05]; P = 0.028) in rats. Furthermore, non-rapid eye movement stage 3 of sleep was characterized by a decoupling of sensory and attention networks from the global network. General anesthesia and unresponsive wakefulness syndrome were characterized by a dissociation of the majority of functional networks from the global network. This decoupling, however, was dominated by distinct neuroanatomic foci (e.g., precuneus and anterior cingulate cortices).

CONCLUSIONS

The global temporal coordination of various modules across the brain may distinguish the coarse-grained state of consciousness versus unconsciousness, while the relationship between the global and local signals may define the particular qualities of a particular unconscious state.

Entropy and the Brain: An Overview

Entropy is a powerful tool for quantification of the brain function and its information processing capacity. This is evident in its broad domain of applications that range from functional interactivity between the brain regions to quantification of the state of consciousness. A number of previous reviews summarized the use of entropic measures in neuroscience. However, these studies either focused on the overall use of nonlinear analytical methodologies for quantification of the brain activity or their contents pertained to a particular area of neuroscientific research. The present study aims at complementing these previous reviews in two ways. First, by covering the literature that specifically makes use of entropy for studying the brain function. Second, by highlighting the three fields of research in which the use of entropy has yielded highly promising results: the (altered) state of consciousness, the ageing brain, and the quantification of the brain networks' information processing. In so doing, the present overview identifies that the use of entropic measures for the study of consciousness and its (altered) states led the field to substantially advance the previous findings. Moreover, it realizes that the use of these measures for the study of the ageing brain resulted in significant insights on various ways that the process of ageing may affect the dynamics and information processing capacity of the brain. It further reveals that their utilization for analysis of the brain regional interactivity formed a bridge between the previous two research areas, thereby providing further evidence in support of their results. It concludes by highlighting some potential considerations that may help future research to refine the use of entropic measures for the study of brain complexity and its function. The present study helps realize that (despite their seemingly differing lines of inquiry) the study of consciousness, the ageing brain, and the brain networks' information processing are highly interrelated. Specifically, it identifies that the complexity, as quantified by entropy, is a fundamental property of conscious experience, which also plays a vital role in the brain's capacity for adaptation and therefore whose loss by ageing constitutes a basis for diseases and disorders. Interestingly, these two perspectives neatly come together through the association of entropy and the brain capacity for information processing.

Neural signs and mechanisms of consciousness: Is there a potential convergence of theories of consciousness in sight?

Various theories for the neural basis of consciousness have been proposed, suggesting a diversity of neural signs and mechanisms. We ask to what extent this diversity is real, or whether many theories share the same basic ideas with a potential for convergence towards a more unified theory of the neural basis of consciousness. For that purpose, we review and compare the various neural signs, measures, and mechanisms proposed in the different theories. We demonstrate that different theories focus on neural signs and measures of distinct aspects of neural activity including stimulus-related, prestimulus, and resting state activity as well as on distinct features of consciousness. Therefore, the various mechanisms proposed in the different theories may, in part, complement each other. Together, we provide insight into the shared basis and convergences (and, in part, discrepancies) of the different theories of consciousness. We conclude that the different theories concern distinct aspects of both neural activity and consciousness which, as we suppose, may be integrated and nested within the brain's overall temporo-spatial dynamics.

The temporal evolution of pre-stimulus slow cortical potentials is associated with an upcoming stimulus' access to visual consciousness

Slow cortical potentials (SCPs) have been proposed to be essential for the formation of conscious experience. To examine their temporal characteristics, we recorded electroencephalography during a visual backward-masking task, which required participants to localize the missing part of a target stimulus. A subsequent confidence rating was used as a proxy for the target's access to consciousness. Event-related potentials (ERPs) of all correct trials were determined relative to a brief period immediately before the target and then compared among consciousness levels. In an interval ranging from 2 s prior to target presentation up to this period, a negative relationship between slowly fluctuating ERP values and the level of consciousness became evident. After target presentation, high conscious awareness was characterized by an enhanced visual awareness negativity, an increased P3 component, and associated positive SCPs. Together, these findings add new evidence to the proposed role of SCPs in the emergence of visual consciousness.

Dissociation as a disorder of integration - On the footsteps of Pierre Janet

At the end of the 19th century Pierre Janet described dissociation as an altered state of consciousness manifested in disrupted integration of psychological functions. Clinically, such disruption comprises compartmentalization symptoms like amnesia, detachment symptoms like depersonalization/derealization, and structural dissociation of personality with changes in the sense of self. The exact neuronal mechanisms leading to these different symptoms remain unclear. We here suggest to put Janet's original account of dissociation as disrupted integration of psychological functions into a novel context, that is, a neuronal context as related to current brain imaging. This requires a combined theoretical and empirical approach on data supporting such neuronal reframing of Janet. For that, we here review (i) past and (ii) recent psychological and neuronal views on dissociation together with neuroscientific theories of integration, which (iii) are supported and complemented by preliminary fMRI data. We propose three neuronal mechanisms of dynamic integration operating at different levels of the brain's spontaneous activity - temporo-spatial binding on the regional level, temporo-spatial synchronization on the network level, and temporo-spatial globalization on the global level. These neuronal mechanisms, in turn, may be related to different symptomatic manifestation of dissociation operating at different levels, e.g., compartmentalization, detachment, and structural, which, as we suggest, can all be traced to disrupted integration of neuronal and psychological functions as originally envisioned by Janet.

Spatiotemporal neuroscience - what is it and why we need it

The excellent commentaries to our target paper hint upon three main issues, (i) spatiotemporal neuroscience; (ii) neuro-mental relationship; and (iii) mind, brain, and world relationship. (i) We therefore discuss briefly the history of Spatiotemporal Neuroscience. Distinguishing it from Cognitive Neuroscience and related branches (like Affective, Social, etc. Neuroscience), Spatiotemporal Neuroscience can be characterized by focus on brain activity (rather than brain function), spatiotemporal relationship (rather than input-cognition-output relationship), and structure (rather than stimuli/contents). (ii) Taken in this sense, Spatiotemporal Neuroscience allows one to conceive the neuro-mental relationship in dynamic spatiotemporal terms that complement and extend (rather than contradict) their cognitive characterization. (iii) Finally, more philosophical issues like the need to dissolve the mind-body problem (and replace it by the world-brain relation) and the question for different levels of time including their nestedness are discussed.

An Integrated World Modeling Theory (IWMT) of Consciousness: Combining Integrated Information and Global Neuronal Workspace Theories With the Free Energy Principle and Active Inference Framework; Toward Solving the Hard Problem and Characterizing Agentic Causation

The Free Energy Principle and Active Inference Framework (FEP-AI) begins with the understanding that persisting systems must regulate environmental exchanges and prevent entropic accumulation. In FEP-AI, minds and brains are predictive controllers for autonomous systems, where action-driven perception is realized as probabilistic inference. Integrated Information Theory (IIT) begins with considering the preconditions for a system to intrinsically exist, as well as axioms regarding the nature of consciousness. IIT has produced controversy because of its surprising entailments: quasi-panpsychism; subjectivity without referents or dynamics; and the possibility of fully-intelligent-yet-unconscious brain simulations. Here, I describe how these controversies might be resolved by integrating IIT with FEP-AI, where integrated information only entails consciousness for systems with perspectival reference frames capable of generating models with spatial, temporal, and causal coherence for self and world. Without that connection with external reality, systems could have arbitrarily high amounts of integrated information, but nonetheless would not entail subjective experience. I further describe how an integration of these frameworks may contribute to their evolution as unified systems theories and models of emergent causation. Then, inspired by both Global Neuronal Workspace Theory (GNWT) and the Harmonic Brain Modes framework, I describe how streams of consciousness may emerge as an evolving generation of sensorimotor predictions, with the precise composition of experiences depending on the integration abilities of synchronous complexes as self-organizing harmonic modes (SOHMs). These integrating dynamics may be particularly likely to occur via richly connected subnetworks affording body-centric sources of phenomenal binding and executive control. Along these connectivity backbones, SOHMs are proposed to implement turbo coding via loopy message-passing over predictive (autoencoding) networks, thus generating maximum a posteriori estimates as coherent vectors governing neural evolution, with alpha frequencies generating basic awareness, and cross-frequency phase-coupling within theta frequencies for access consciousness and volitional control. These dynamic cores of integrated information also function as global workspaces, centered on posterior cortices, but capable of being entrained with frontal cortices and interoceptive hierarchies, thus affording agentic causation. Integrated World Modeling Theory (IWMT) represents a synthetic approach to understanding minds that reveals compatibility between leading theories of consciousness, thus enabling inferential synergy.

Individual Alpha Frequency Predicts Perceived Visuotactile Simultaneity

Temporal encoding is a key feature in multisensory processing that leads to the integration versus segregation of perceived events over time. Whether or not two events presented at different offsets are perceived as simultaneous varies widely across the general population. Such tolerance to temporal delays is known as the temporal binding window (TBW). It has been recently suggested that individual oscillatory alpha frequency (IAF) peak may represent the electrophysiological correlate of TBW, with IAF also showing a wide variability in the general population (8–12 Hz). In our work, we directly tested this hypothesis by measuring each individual's TBW during a visuotactile simultaneity judgment task while concurrently recording their electrophysiological activity. We found that the individual's TBW significantly correlated with their left parietal IAF, such that faster IAF accounted for narrower TBW. Furthermore, we found that higher prestimulus alpha power measured over the same left parietal regions accounted for more veridical responses of non-simultaneity, which may be explained either by accuracy in perceptual simultaneity or, alternatively, in line with recent proposals by a shift in response bias from more conservative (high alpha power) to more liberal (low alpha power). We propose that the length of an alpha cycle constrains the temporal resolution within which perceptual processes take place.