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Theories of consciousness
Abstract
Recent years have seen a blossoming of theories about the biological and physical basis of consciousness. Good theories guide empirical research, allowing us to interpret data, develop new experimental techniques and expand our capacity to manipulate the phenomenon of interest. Indeed, it is only when couched in terms of a theory that empirical discoveries can ultimately deliver a satisfying understanding of a phenomenon. However, in the case of consciousness, it is unclear how current theories relate to each other, or whether they can be empirically distinguished. To clarify this complicated landscape, we review four prominent theoretical approaches to consciousness: higher-order theories, global workspace theories, re-entry and predictive processing theories and integrated information theory. We describe the key characteristics of each approach by identifying which aspects of consciousness they propose to explain, what their neurobiological commitments are and what empirical data are adduced in their support. We consider how some prominent empirical debates might distinguish among these theories, and we outline three ways in which theories need to be developed to deliver a mature regimen of theory-testing in the neuroscience of consciousness. There are good reasons to think that the iterative development, testing and comparison of theories of consciousness will lead to a deeper understanding of this most profound of mysteries. Various theories have been developed for the biological and physical basis of consciousness. In this Review, Anil Seth and Tim Bayne discuss four prominent theoretical approaches to consciousness, namely higher-order theories, global workspace theories, re-entry and predictive processing theories and integrated information theory.
... How one answers this question depends largely on the theory of consciousness to which one subscribes. While the search for a comprehensive, neuroscientifically grounded theory of consciousness is ongoing (Seth & Bayne, 2022), there are certain points that seem uncontroversial among the majority of theories. First, it seems highly plausible that certain brains structures and processes have a privileged relationship with subjective phenomenological experiences. ...
... How exactly consciousness is brought about on a neural level differs largely among major theoretical strands, such as, integrated information theory; higher-order theories; global workspace theories; or predictive processing theories (Seth & Bayne, 2022). When investigating a phenomenon like consciousness, one's assumptions about consciousness greatly influence one's predictions about where to find it. ...
... According to the free energy principle, organisms aim to minimize surprise, and can do so in several ways. They can either change and update the predictions themselves (top-down), so that they match the sensory input, or they can change their environment to change the sensory inputs (bottom-up) so that it matches the prediction (Seth & Bayne, 2022). Due to the intricate connection of predicting and acting, this process is also called active inference (Friston et al., 2017). ...
The convergence of human and artificial intelligence is currently receiving considerable scholarly attention. Much debate about the resulting Hybrid Minds focuses on the integration of artificial intelligence into the human brain through intelligent brain-computer interfaces as they enter clinical use. In this contribution we discuss a complementary development: the integration of a functional in vitro network of human neurons into an in silico computing environment.
To do so, we draw on a recent experiment reporting the creation of silico-biological intelligence as a case study (Kagan et al., 2022b). In this experiment, multielectrode arrays were plated with stem cell-derived human neurons, creating a system which the authors call DishBrain . By embedding the system into a virtual game-world, neural clusters were able to receive electrical input signals from the game-world and to respond appropriately with output signals from pre-assigned motor regions. Using this design, the authors demonstrate how the DishBrain self-organises and successfully learns to play the computer game ‘Pong’, exhibiting ‘sentient’ and intelligent behaviour in its virtual environment.
The creation of such hybrid, silico-biological intelligence raises numerous ethical challenges. Following the neuroscientific framework embraced by the authors themselves, we discuss the arising ethical challenges in the context of Karl Friston’s Free Energy Principle, focusing on the risk of creating synthetic phenomenology. Following the DishBrain’s creator’s neuroscientific assumptions, we highlight how DishBrain’s design may risk bringing about artificial suffering and argue for a congruently cautious approach to such synthetic biological intelligence.
... Given the complexity of consciousness and its phenomenology, several teams of scientists have proposed theories to model how the different aspects of consciousness are generated in the brain. 9 These theories are based on different features and constructs, but are not necessarily mutually exclusive. 10 Before these are described below, we first give a description of several concepts related to consciousness and its contents in addition to outlining the current knowledge of brain functioning underlying consciousness. ...
... It is beyond the scope of this paper to review all of them. 9 In this review, we primarily focus on those theories addressing the phenomenological aspects of consciousness (access consciousness, phenomenal consciousness, and phenomenal selfhood), that is the subjective experience of an individual, as subjective experience during anaesthesia is the most important aspect for our patients. We also limit our description to the ones that have gained most attention in recent years and may have direct applications to the domain of anaesthesia. ...
... We also limit our description to the ones that have gained most attention in recent years and may have direct applications to the domain of anaesthesia. According to the classification of Seth and Bayne, 9 Through N-methyl-D-aspartate (NMDA) glutamate receptor antagonism, ketamine is known to inhibit GABAergic inhibitory interneurons at the cortical level, producing a hyper-glutamatergic state and the activation of specific cortical regions (anterior cingulate, medial prefrontal cortex, insula, and precuneus), the limbic system, and the hippocampus. 65 66 This inhibitory interneuron inhibition also promotes cholinergic, dopaminergic, and other aminergic neurotransmission emerging from subcortical nuclei (e.g. ...
Neuroscientists agree on the value of locating the source of consciousness within the brain. Anaesthesiologists are no exception, and have their own operational definition of consciousness based on phenomenological observations during anaesthesia. The full functional correlates of consciousness are yet to be precisely identified, however rapidly evolving progress in this scientific domain has yielded several theories that attempt to model the generation of consciousness. They have received variable support from experimental observations, including those involving anaesthesia and its ability to reversibly modulate different aspects of consciousness. Aside from the interest in a better understanding of the mechanisms of consciousness, exploring the functional tenets of the phenomenological consciousness states of general anaesthesia has the potential to ultimately improve patient management. It could facilitate the design of specific monitoring devices and approaches, aiming at reliably detecting each of the possible states of consciousness during an anaesthetic procedure, including total absence of mental content (unconsciousness), and internal awareness (sensation of self and internal thoughts) with or without conscious perception of the environment (connected or disconnected consciousness, respectively). Indeed, it must be noted that unresponsiveness is not sufficient to infer absence of connectedness or even absence of consciousness. This narrative review presents the current knowledge in this field from a system-level, underlining the contribution of anaesthesia studies in supporting theories of consciousness, and proposing directions for future research.
... A core difference between these theories is that the GNWH views consciousness from an objective, third-person perspective, while the IIT also tries to operationalize a first-person subjective perspective (for a review see Seth and Bayne, 2022), therefore approximating the Aristotelian view of conscious experience, given the reflexivity that characterises his investigations of cognition and the mind (Caston, 2002;Smit and Hacker, 2020). As valuable to the investigation of consciousness as these theoretical formulations may be, still they involve limitations in empirically evaluating both the objective (access or representational) and the subjective (i.e., phenomenal) aspects of conscious operations. ...
... Although the GNWH and the IIT efficiently provide testable predictions, the fundamental assumptions of these perspectives regarding consciousness and its neural substrates are different (for a review see Seth and Bayne, 2022;Melloni et al., 2023). For example, according to the IIT, a conscious experience will be reflected in sustained neuronal activation throughout the duration of that experience; whereas the GNWH suggests an initial "ignition" or activation upon the entrance of related information into the workspace, followed by a decay. ...
Contemporary theories of consciousness, although very efficient in postulating testable hypotheses, seem to either neglect its relational aspect or to have a profound difficulty in operationalizing this aspect in a measurable manner. We further argue that the analysis of periodic brain activity is inadequate to reveal consciousness’s subjective facet. This creates an important epistemic gap in the quest for the neural correlates of consciousness. We suggest a possible solution to bridge this gap, by analysing aperiodic brain activity. We further argue for the imperative need to inform neuroscientific theories of consciousness with relevant philosophical endeavours, in an effort to define, and therefore operationalise, consciousness thoroughly.
... The pursuit of a well-motivated, operational, and falsifiable theory of consciousness remains hot in cognitive science (see [1]). Such a theory holds the key to answering fundamental questions in psychology, neuroscience, cybernetics, artificial intelligence and robotics. ...
... The ANS component was assumed to be involuntary and hard to control. We simulated agent A1 in two conditions ( Figure 5): (1) with minimal sensitivity to the ANS features expressed by A0 versus (2) with maximal sensitivity to those features (we used a simple weighted average as a first implementation of the sensitivity function). A0 expressed voluntary positive emotions through the AU component to minimize its own FE, even though it disliked A1. ...
Consciousness has been described as acting as a global workspace that integrates perception, imagination, emotion and action programming for adaptive decision making. The mechanisms of this workspace and their relationships to the phenomenology of consciousness need to be further specified. Much research in this area has focused on the neural correlates of consciousness, but, arguably, computational modeling can better be used toward this aim. According to the Projective Consciousness Model (PCM), consciousness is structured as a viewpoint-organized, internal space, relying on 3D projective geometry and governed by the action of the Projective Group as part of a process of active inference. The geometry induces a group-structured subjective perspective on an encoded world model, enabling adaptive perspective taking in agents. Here, we review and discuss the PCM. We emphasize the role of projective mechanisms in perception and the appraisal of affective and epistemic values as tied to the motivation of action, under an optimization process of Free Energy minimization, or more generally stochastic optimal control. We discuss how these mechanisms enable us to model and simulate group-structured drives in the context of social cognition and to understand the mechanisms underpinning empathy, emotion expression and regulation, and approach–avoidance behaviors. We review previous results, drawing on applications in robotics and virtual humans. We briefly discuss future axes of research relating to applications of the model to simulation- and model-based behavioral science, geometrically structured artificial neural networks, the relevance of the approach for explainable AI and human–machine interactions, and the study of the neural correlates of consciousness.
... With the application of binocular rivalry, split brain, blindsight, and other paradigms by passionate pioneers in the last century (Seth, 2018), empirical theories of consciousness have emerged in neuroscience. Currently, the situation has reached a critical point of both hope and challenge in that a large number of theories of consciousness (ToCs), each with specific empirical support, have claimed their respective plausibilities, and their proposed conjectures have led to diverging predictions (Del Pin et al., 2021;Signorelli et al., 2021;Seth and Bayne, 2022;Yaron et al., 2022). Various theories have been discussed, and it appears that this issue is becoming more prevalent. ...
... In this process, four major kinds of ToCs have garnered the most attention (Seth and Bayne, 2022): Integrated Information Theory (IIT) (Tononi, 2008;Oizumi et al., 2014;Tononi et al., 2016), Global Neural Workspace Theory (GNWT) (Dehaene, 2014;Mashour et al., 2020), Higher-Order Theory (HOT) (Lau and Rosenthal, 2011;Brown et al., 2019), and Recurrent Processing Theory (RPT) (Lamme, 2018) and Predictive Processing Theory (PP) (Seth and Hohwy, 2021). ...
... To stay within the scope of this paper the examples of applications for the reviewed scienti¯c theories in this section will only be from the engineering and computer science¯elds. More detailed reviews on theories of consciousness are available [Seth and Bayne, 2022;Zeman, 2001]. ...
... GWT assumes that the brain can be viewed as a collection of processors. Global workspace is a structure associated with consciousness, and it can be compared with a blackboard architecture in which a set of distributed knowledge sources can cooperatively solve problems together that are otherwise not possible by the single sources [Seth and Bayne, 2022]. From the global workspace, the focal contents compete to be broadcast to many unconscious modules. ...
This paper envisions the possibility of a Conscious Aircraft: an aircraft of the future with features of consciousness. To serve this purpose, three main fields are examined: philosophy, cognitive neuroscience, and Artificial Intelligence (AI). While philosophy deals with the concept of what is consciousness, cognitive neuroscience studies the relationship of the brain with consciousness, contributing toward the biomimicry of consciousness in an aircraft. The field of AI leads into machine consciousness. The paper discusses several theories from these fields and derives outcomes suitable for the development of a Conscious Aircraft, some of which include the capability of developing “world-models”, learning about self and others, and the prerequisites of autonomy, selfhood, and emotions. Taking these cues, the paper focuses on the latest developments and the standards guiding the field of autonomous systems, and suggests that the future of autonomous systems depends on its transition toward consciousness. Finally, inspired by the theories suggesting the levels of consciousness, guided by the Theory of Mind, and building upon state-of-the-art aircraft with autonomous systems, this paper suggests the development of a Conscious Aircraft in three stages: Conscious Aircraft with (1) System-awareness, (2) Self-awareness, and (3) Fleet-awareness, from the perspectives of health management, maintenance, and sustainment.
... The PPC holds growing significance in the clinical rehabilitation of individuals with DoC. It serves as a vital connection within the DMN and assumes a pivotal role in the recovery process of patients with DoC [41]. The DMN is commonly acknowledged as a collection of cortical regions, such as the left and right middle frontal gyrus, bilateral medial frontal, left and right middle temporal, occipital gyrus, and bilateral precuneus, among other locations [42]. ...
... This phenomenon could perhaps be attributed to the left PPC, which is an integral component of the DMN. Enhancing the activity of the left PPC is essential for the restoration of consciousness and has been linked to various etiologies of injury in patients [41]. ...
Traumatic brain injury, cardiac arrest, intracerebral hemorrhage, and ischemic stroke may cause disorders of consciousness (DoC). Repetitive transcranial magnetic stimulation (rTMS) has been used to promote the recovery of disorders of consciousness (DoC) patients. In this meta-analysis, we examined whether rTMS can relieve DoC patient symptoms. We searched through journal articles indexed in PubMed, the Web of Science, Embase, Scopus, and the Cochrane Library until 20 April 2023. We assessed whether studies used rTMS as an intervention and reported the pre- and post-rTMS coma recovery scale-revised (CRS-R) scores. A total of 207 patients from seven trials were included. rTMS significantly improved the recovery degree of patients; the weighted mean difference (WMD) of the change in the CRS-R score was 1.89 (95% confidence interval (CI): 1.39–2.39; p < 0.00001) in comparison with controls. The subgroup analysis showed a significant improvement in CRS-R scores in rTMS over the dorsolateral prefrontal cortex (WMD = 2.24; 95% CI: 1.55–2.92; p < 0.00001; I2 = 31%) and the primary motor cortex (WMD = 1.63; 95% CI: 0.69–2.57; p = 0.0007; I2 = 14%). Twenty-hertz rTMS significantly improved CRS-R scores in patients with DoC (WMD = 1.61; 95% CI: 0.39–2.83; p = 0.010; I2 = 31%). Furthermore, CRS-R scores in rTMS over 20 sessions significantly improved (WMD = 1.75; 95% CI: 0.95–2.55; p < 0.0001; I2 = 12%). rTMS improved the symptoms of DoC patients; however, the available evidence remains limited and inadequate.
... In the sciences of mind, a wide variety of proposals to account for consciousness in neurobiological terms have been proposed. As listed by Seth and Bayne (2022) As Merker et al. (2021) point out, "schools" advocating disparate theoretical bids for paradigmatic status contend with one another without the benefit of any shared means of adjudicating the relative merits of their conflicting proposals. In Kuhnian terms, these are the cardinal characteristics of the "prehistory" stage of a nascent science (Kuhn, 1962) (sect. ...
... In order to advance the analyses, a small selection of empirical, brain-based theories has been made here, noting that this does not imply an evaluation of other theories (that could also serve in such a comparative analysis). We chose to compare these theories here because they can serve to illustrate the issues of commensurability, similarity and (possibly common) denominators at hand, and because their neuroscientific aspects have been elaborated to some extent; they are in line with at least some neuroscientific arguments and findings and are under active investigation (for a recent review, see (Seth & Bayne, 2022)). ...
How deep is the current diversity in the panoply of theories to define consciousness, and to what extent do these theories share common denominators? Here we first examine to what extent different theories are commensurable (or comparable) along particular dimensions. We posit logical (and, when applicable, empirical) commensurability as a necessary condition for identifying common denominators among different theories. By consequence, dimensions for inclusion in a set of logically and empirically commensurable theories of consciousness can be proposed. Next, we compare a limited subset of neuroscience-based theories in terms of commensurability. This analysis does not yield a denominator that might serve to define a minimally unifying model of consciousness. Theories that seem to be akin by one denominator can be remote by another. We suggest a methodology of comparing different theories via multiple probing questions, allowing to discern overall (dis)similarities between theories. Despite very different background definitions of consciousness, we conclude that it should be possible in principle to overcome the current Babylonian confusion of tongues and eventually integrate and merge different theories.
... Using a three-phase paradigm in which we independently manipulated perception and task-relevance, we identified a novel neural difference linked with perceptual awareness of SWS words, which we interpreted as a speech-specific version of a perceptual awareness negativity (Dembski et al., 2021) . Future work involving the paradigm developed here along with other methods may help reveal the precise neural mechanisms underlying conscious speech perception and help address diverging predictions from neuroscientific theories of consciousness (Seth and Bayne, 2022) . ...
Identifying neural correlates of conscious perception is a fundamental endeavor of cognitive neuroscience. Most studies so far have focused on visual awareness along with trial-by-trial reports of task relevant stimuli, which can confound neural measures of perceptual awareness with post-perceptual processing. Here, we used a three-phase sine-wave speech paradigm that dissociated between conscious speech perception and task relevance while recording EEG in humans of both sexes. Compared to tokens perceived as noise, physically identical sine-wave speech tokens that were perceived as speech elicited a left-lateralized, near-vertex negativity, which we interpret as a phonological version of a perceptual awareness negativity. This response appeared between 200 and 300 ms after token onset and was not present for frequency-flipped control tokens that were never perceived as speech. In contrast, the P3b elicited by task-irrelevant tokens did not significantly differ when the tokens were perceived as speech versus noise, and was only enhanced for tokens that were both perceived as speech and relevant to the task. Our results extend the findings from previous studies on visual awareness and speech perception, and suggest that correlates of conscious perception, across types of conscious content, are most likely to be found in mid-latency negative-going brain responses in content-specific sensory areas.
... This could disrupt the cortical communication on which consciousness depends 1,2,7 , but the exact link to theories of consciousness is not clear. Many theories of consciousness have focused on the representation and network structure involved in 1 integrating information or linking together cortical representations [8][9][10][11][12][13][14] . For example, one prominent theory of consciousness posits that awareness follows from an "ignition" that produces widespread cortical spiking much like a few claps can lead to a whole audience applauding 10,15,16 . ...
Every day, hundreds of thousands of people undergo general anesthesia. One hypothesis is that anesthesia disrupts dynamic stability, the ability of the brain to balance excitability with the need to be stable and thus controllable. We tested this hypothesis using a new method for quantifying population-level dynamic stability in complex systems, De layed L inear A nalysis for S tability E stimation ( DeLASE ). Propofol was used to transition animals between the awake state and anesthetized unconsciousness. DeLASE was applied to macaque cortex local field potentials (LFPs). We found that neural dynamics were more unstable in unconsciousness compared to the awake state. Cortical trajectories mirrored predictions from destabilized linear systems. We mimicked the effect of propofol in simulated neural networks by increasing inhibitory tone. Paradoxically, increased inhibition also destabilized the networks. Our results suggest that anesthesia disrupts dynamical stability that is required for consciousness.
... Indeed, referring to Nagel's way of capturing the phenomenon is prevalent in the literature (for just some recent examples see e.g. Blum & Blum, 2022;Frohlich et al., 2021;Northoff & Lamme, 2020;Raccah et al., 2021;Seth & Bayne, 2022). However, what exactly what-it-is-likeness entails is a matter of extensive debate. ...
In recent years increasing attention has been given to systematic comparison of theories of consciousness. Laudable practical projects have emerged in this regard, such as adversarial collaboration and the development of databases lending themselves to comparisons of empirical support for theories. In addition to the practical advances, theoretical advances have been made, such as a list of issues a theory of consciousness must address. We propose adding the issue of the ontogenetic emergence (O-emergence) of consciousness to the list of issues we use to evaluate theories of consciousness. O-emergence concerns how and when consciousness emerges ontogenetically in human beings. The underlying assumption is that there exists a point in the development of a human individual before which that individual is not and cannot be conscious. This assumption, in turn, depends on a widely shared assumption of cognitive neuroscience, which is that consciousness somehow depends on — or derives from — brain activity. In this paper, we lay out the O-emergence criterion and investigate whether it can be accounted for within the Global Neuronal Workspace theory, the Self-Organizing Meta-representational Account, and the Reorganization of Elementary Functions framework.
... These studies investigated stimulus-induced INT modulation during conscious wakefulness. While present discussions of brain dynamics often focus on the neuronal correlates of consciousness (see 18,19 for reviews), in line with INT analyses under conscious wakefulness, INT during states of unconsciousness like sleep remain relatively understudied (see refs. 8,20 for two paradigmatic exceptions). ...
Functional magnetic resonance imaging (fMRI) studies have demonstrated that intrinsic neuronal timescales (INT) undergo modulation by external stimulation during consciousness. It remains unclear if INT keep the ability for significant stimulus-induced modulation during primary unconscious states, such as sleep. This fMRI analysis addresses this question via a dataset that comprises an awake resting-state plus rest and stimulus states during sleep. We analyzed INT measured via temporal autocorrelation supported by median frequency (MF) in the frequency-domain. Our results were replicated using a biophysical model. There were two main findings: (1) INT prolonged while MF decreased from the awake resting-state to the N2 resting-state, and (2) INT shortened while MF increased during the auditory stimulus in sleep. The biophysical model supported these results by demonstrating prolonged INT in slowed neuronal populations that simulate the sleep resting-state compared to an awake state. Conversely, under sine wave input simulating the stimulus state during sleep, the model’s regions yielded shortened INT that returned to the awake resting-state level. Our results highlight that INT preserve reactivity to stimuli in states of unconsciousness like sleep, enhancing our understanding of unconscious brain dynamics and their reactivity to stimuli.
... Whereas some decades ago few respected experimental scientists would consider the investigation of consciousness a worthy scientific pursuit, recent years have seen a surge in the study of consciousness and cognition, with natural implications for neuroscience, philosophy, neurology, psychiatry and psychology. As a result, we presently have too many theories and frameworks of consciousness and cognition (Rosenthal, 2020;Seth and Bayne, 2022;Stefanelli, 2023). Some may perceive the abundance of theories as a healthy sign of thinking about consciousness/cognition, however, "growth is not always benign […] Cancer is a good example", as said by philosopher Robert Chis-Ciure in a talk on consciousness theories. ...
There is such a vast proliferation of theories and conceptual frameworks of consciousness and cognition that it is worrying some scholars. There are even competitions to test different theories, and the results are inconclusive. Consciousness research, far from converging toward a unifying framework, is becoming more discordant than ever. We do not need more theories but rather integration across theories to facilitate a comprehensive view on consciousness and cognition and on how normal nervous system dynamics can develop into pathological states. In dealing with what is considered an extremely complex matter, we try to adopt a perspective from which the subject appears in relative simplicity. Grounded in experimental and theoretical observations, we advance an encompassing theory, MaxCon, which incorporates aspects of several main existing theories, finding convergence points in an attempt to simplify and to understand how cellular collective activity is organized to fulfill the dynamic requirements of the diverse theories our proposal comprises. In essence, our proposal derived from the level of description of the interactions among cell networks highlights the tendency to maximise the number of configurations of neural network connections --constrained by neuroanatomy, biophysical features and the environment-- for conscious awareness and proper sensorimotor transformations.
... This approach suggests a framework for the systematic mapping of neural mechanisms onto certain domains of consciousness. Within this context, key dichotomies must be noted when discussing different theories of consciousness [154]. These include (i) global states versus local states, where the former is understood as levels of consciousness and the latter correlates with conscious contents or qualia; (ii) phenomenological properties versus functional properties, each having a unique objective; and (iii) the selection of a local state (why a subject possesses a specific local state) versus the experiential characterization of local states (why a specific local state is tied to a particular experience). ...
Chronic pain has increasingly become a significant health challenge, not just as a symptomatic manifestation but also as a pathological condition with profound socioeconomic implications. Despite the expansion of medical interventions, the prevalence of chronic pain remains remarkably persistent, prompting a turn towards non-pharmacological treatments, such as therapeutic education, exercise, and cognitive-behavioral therapy. With the advent of cognitive neuroscience, pain is often presented as a primary output derived from the brain, aligning with Engel’s Biopsychosocial Model that views disease not solely from a biological perspective but also considering psychological and social factors. This paradigm shift brings forward potential misconceptions and over-simplifications. The current review delves into the intricacies of nociception and pain perception. It questions long-standing beliefs like the cerebral-centric view of pain, the forgotten role of the peripheral nervous system in pain chronification, misconceptions around central sensitization syndromes, the controversy about the existence of a dedicated pain neuromatrix, the consciousness of the pain experience, and the possible oversight of factors beyond the nervous system. In re-evaluating these aspects, the review emphasizes the critical need for understanding the complexity of pain, urging the scientific and clinical community to move beyond reductionist perspectives and consider the multifaceted nature of this phenomenon.
... In addition, as soon as a being is conscious, there arises the risk that it might suffer. The connection between consciousness and suffering sparked a debate on the risks emerging from research which might eventually enable the creation of conscious machines (Metzinger, 2021). 1 Most theories of consciousness are functionalist and thereby entail that a machine with the right causal organization would be conscious (Dehaene et al., 2017;Doerig et al., 2021;Seth & Bayne, 2022). If we build conscious artificial intelligences (AIs) but don't recognize that they are conscious and thus don't treat them appropriately, then we might inadvertently cause -potentially astronomical -suffering (Dung, 2023;Saad & Bradley, 2022;Tomasik, 2014). ...
If a machine attains consciousness, how could we find out? In this paper, I make three related claims regarding positive tests of machine consciousness. All three claims center on the idea that an AI can be constructed “ad hoc”, that is, with the purpose of satisfying a particular test of consciousness while clearly not being conscious. First, a proposed test of machine consciousness can be legitimate, even if AI can be constructed ad hoc specifically to pass this test. This is underscored by the observation that many, if not all, putative tests of machine consciousness can be passed by non-conscious machines via ad hoc means. Second, we can identify ad hoc AI by taking inspiration from the notion of an ad hoc hypothesis in philosophy of science. Third, given the first and the second claim, the most reliable tests of animal consciousness turn out to be valid and useful positive tests of machine consciousness as well. If a non-ad hoc AI exhibits clusters of cognitive capacities facilitated by consciousness in humans which can be selectively switched off by masking and if it reproduces human behavior in suitably designed double dissociation tasks, we should treat the AI as conscious.
... While most arguments were based on a physicalist line of reasoning (for a review, see (Seth and Bayne, 2022)), and also other post-materialistic models of consciousness that are not exclusively based on brain activity exist (for a review and discussion see (Wahbeh et al., 2022)), here it is shown that there are also strictly neuroscientific facts that have not received sufficient appreciation and that give us good reasons to look upon the physicalist assumptions with a more critical eye. Non-neurocentric paradigms of consciousness that posit mind and consciousness as a fundamental primitive, rather than matter, remain a viable option. ...
In the philosophy of mind, neuroscience, and psychology, the causal relationship between phenomenal consciousness, mentation, and brain states has always been a matter of debate. On the one hand, material monism posits consciousness and mind as pure brain epiphenomena. One of its most stringent lines of reasoning relies on a 'loss-of-function lesion premise,' according to which, since brain lesions and neurochemical modifications lead to cognitive impairment and/ or altered states of consciousness, there is no reason to doubt the mind-brain identity. On the other hand, dualism or idealism (in one form or another) regard consciousness and mind as something other than the sole product of cerebral activity pointing at the ineffable, undefinable, and seemingly unphysical nature of our subjective qualitative experiences and its related mental dimension. Here, several neuroscientific findings are reviewed that question the idea that posits phenomenal experience as an emergent property of brain activity, and argue that the premise of material monism is based on a logical correlation-causation fallacy. While these (mostly ignored) findings, if considered separately from each other, could, in principle, be recast into a physicalist paradigm, once viewed from an integral perspective, they substantiate equally well an ontology that posits mind and consciousness as a primal phenomenon.
... Currently, Integrated Information Theory (IIT) is one of the leading scientific theories of consciousness [1][2][3][4]. IIT is especially interesting because it aims to explain the phenomenal, subjective character of experience; not its behavioural, computational or functional correlates [5]. However, the consistency of the theory has been critically addressed on several occasions [6][7][8][9][10]. ...
Integrated Information Theory (IIT) is currently one of the most influential scientific theories of consciousness. Here, we focus specifically on a metaphysical aspect of the theory’s most recent version (IIT 4.0), what we may call its idealistic ontology, and its tension with a kind of realism about the external world that IIT also endorses. IIT 4.0 openly rejects the mainstream view that consciousness is generated by the brain, positing instead that consciousness is ontologically primary while the physical domain is just “operational”. However, this philosophical position is presently underdeveloped and is not rigorously formulated in IIT, potentially leading to many misinterpretations and undermining its overall explanatory power. In the present paper we aim to address this issue. We argue that IIT’s idealistic ontology should be understood as a specific combination of phenomenal primitivism, reductionism regarding Φ-structures and complexes, and eliminativism about non-conscious physical entities. Having clarified this, we then focus on the problematic tension between IIT’s idealistic ontology and its simultaneous endorsement of realism, according to which there is some kind of external reality independent of our minds. After refuting three potential solutions to this theoretical tension, we propose the most plausible alternative: understanding IIT’s realism as an assertion of the existence of other experiences beyond one’s own, what we call a non-solipsistic idealist realism. We end with concluding remarks and future research avenues.
... This approach suggests a framework for the systematic mapping of neural mechanisms onto certain domains of consciousness. Within this context, key dichotomies must be noted when discussing different theories of consciousness [140]. These include: (i) Global states versus local states, where the former is understood as levels of consciousness and the latter correlates with conscious contents or qualia; (ii) Phenomenological properties versus functional properties, each having a unique objective; and (iii) The selection of a local state (why a subject possesses a specific local state) versus the experiential characterization of local states (why a specific local state is tied to a particular experience). ...
Chronic pain has increasingly become a significant health challenge, not just as a symptomatic manifestation but also as a pathological condition with profound socioeconomic implications. Despite the expansion of medical interventions, the prevalence of chronic pain remains remarkably persistent, prompting a turn towards non-pharmacological treatments, such as therapeutic education, exercise and cognitive-behavioral therapy. With the advent of cognitive neuroscience, pain is often presented as a primary output derived from the brain, aligning with Engel's Biopsychosocial Model which views disease not solely from a biological perspective but also considering psychological and social factors. This paradigm shift, brings forward potential misconceptions and over-simplifications. The current review delves into the intricacies of nociception and pain perception. It questions long-standing beliefs like the cerebral-centric view of pain, the forgotten role of the peripheral nervous system in pain chronification, misconceptions around central sensitization syndromes, the controversy about the existence of a dedicated pain neuromatrix, the consciousness of the pain experience and the possible oversight of factors beyond the nervous system. In re-evaluating these aspects, the review emphasizes the critical need for understanding the complexity of pain, urging the scientific and clinical community to move beyond reductionist perspectives and consider the multifaceted nature of this phenomenon.
... QTOC provides the physics foundation and mathematical formulation to study panpsychism and other theories and models of consciousness, such as integrated information theory [58], general resonance theory [59] [60], field models [61] [62] [63], global workspace theory of consciousness [64] [65], theory of consciousness as memory and attention [66] [67], and other models and theories of consciousness [5]. For instance, with QTOC, one can calculate the integrated information proposed in integrated information theory, the coherence and synchrony suggested in general resonance theory, the field indicated in field theory, the cognitive global workspace proposed in the cognitive global workspace theory, and the memory and attention indicated in the theory of consciousness as memory and attention. ...
... From their perspective, a meta-network consisting of individual functional networks can be understood as a set of such functions without putting a brand new name, i.e., phronesis. However, recent neuroscience research on consciousness may suggest that such a view does not explain reality accurately (Seth and Bayne 2022). According to the Integrative Information Theory, which explains the emergence of consciousness from brain networks, the higher-order concept of consciousness emerges when a network can present irreducible integrative information (Tononi et al. 2016). ...
In this paper, I examined whether evidence from the neuroscience of morality supports the standard models of phronesis, i.e., Jubilee and Aretai Centre Models. The standard models explain phronesis as a multifaceted construct based on interaction and coordination among functional components. I reviewed recent neuroscience studies focusing on brain networks associated with morality and their connectivity to examine the validity of the models. Simultaneously, I discussed whether the evidence helps the models address challenges, particularly those from the phronesis eliminativism. Neuroscientific evidence supported the importance of brain networks, i.e., the default mode, salience, and central executive functioning networks, in moral functioning in general. The findings favorably supported the multifaceted and integrative nature of phronesis proposed by the standard models. Finally, I considered how the two models could explain the mechanisms of phronesis more integratively based on neuroscientific findings. At the end of this paper, with the evidence, I proposed several practical ideas to promote the cultivation of phronesis, e.g., the consideration of coordination among components for moral functioning and the use of moral exemplars.
... In nascent fields such as the neuroscience of consciousness, for instance, there is widespread controversy about the fundamental nature of the target phenomenon and how it ought to be investigated. [20][21][22][23] Although several theories of consciousness have garnered empirical support, recent work indicates that they tend to pick out distinct aspects of consciousness rooted in largely non-overlapping domains: e.g., brain networks, phenomenology, information theory, etc. 24 Hence, even if an adversarial experiment were to rule in favor of one theory over another, it may be premature to jettison the defeated candidate altogether: all that has been demonstrated in this situation is a case in which theory A outperforms theory B; the converse may be true in another domain. Consciousness research may be better served by adversarial collaborations that evaluate the performance of various theoretical frameworks in multiple domains (e.g., through a more ''holistic'' series of experiments designed to test a range of predictions about different sorts of observations; see e.g., Melloni et al. 25 ) before arriving at firm abductions about which avenues should be pursued and which excluded from future exploration. ...
Adversarial collaboration has been championed as the gold standard for resolving scientific disputes but has gained relatively limited traction in neuroscience and allied fields. In this perspective, we argue that adversarial collaborative research has been stymied by an overly restrictive concern with the falsification of scientific theories. We advocate instead for a more expansive view that frames adversarial collaboration in terms of Bayesian belief updating, model comparison, and evidence accumulation. This framework broadens the scope of adversarial collaboration to accommodate a wide range of informative (but not necessarily definitive) studies while affording the requisite formal tools to guide experimental design and data analysis in the adversarial setting. We provide worked examples that demonstrate how these tools can be deployed to score theoretical models in terms of a common metric of evidence, thereby furnishing a means of tracking the amount of empirical support garnered by competing theories over time.
... Yet, it can be doubted that the suggestion indeed sets a low threshold for the burden of proof for taking precautions. This is because even in humans, inferences about conscious states based solely on neural patterns remain a subject of debate [44,45]. One of the main reasons is the correlational nature of data, which leaves open the question whether observable patterns indeed play a causal role in the emergence of consciousness or if they should be regarded as mere epiphenomena [46]. ...
Advances in research on human cerebral organoids (HCOs) call for a critical review of current research policies. A challenge for the evaluation of necessary research regulations lies in the severe uncertainty about future trajectories the currently very rudimentary stages of neural cell cultures might take as the technology progresses. To gain insights into organotypic cultures, ethicists, legal scholars, and neuroscientists rely on resemblances to the human brain. They refer to similarities in structural or functional terms that have been established in scientific practice to validate organotypic cultures as models for brain research. In ethical discourse, however, such similarities are also used to justify assumptions about the potential risk to cause harm to HCOs. Ethicists assume that as the technology advances, organotypic cultures will increasingly resemble the human brain, raising more complex ethical issues. I argue that such reasoning is not justified given the heterogeneity of HCOs that have been modified to enable scientists to pursue their research goals. I then discuss the implications this line of thought has for advocates of the precautionary principle, focussing on those suggestions which propose adopting research regulations to the presence of bodily warning signs deemed worthy of protection. In doing so, I illustrate that the prevalent assumptions on similarity in ethical discourse ultimately risk disproportionately restricting research. I conclude that given the severe uncertainty about the technology’s future development, ethical discourse might benefit from narrowing the time frame for anticipation.
... There are currently several theories trying to explain different facets of consciousness and synthesize them under a unified framework (for recent reviews, see Doerig et al. 2021;Seth and Bayne 2022;Yaron et al. 2022). The majority of these theories are concerned with human consciousness and suggest that a "core network," the location and properties of which are hotly debated, instantiates consciousness (Koch et al. 2016;Melloni et al. 2021). ...
The Global Neuronal Workspace theory of consciousness offers an explicit functional architecture that relates consciousness to cognitive abilities such as perception, attention, memory, and evaluation. We show that the functional architecture of the Global Neuronal Workspace, which is based mainly on human studies, corresponds to the cognitive-affective architecture proposed by the Unlimited Associative Learning theory that describes minimal consciousness. However, we suggest that when applied to basal vertebrates, both models require important modifications to accommodate what has been learned about the evolution of the vertebrate brain. Most importantly, comparative studies suggest that in basal vertebrates, the Global Neuronal Workspace is instantiated by the event memory system found in the hippocampal homolog. This proposal has testable predictions and implications for understanding hippocampal and cortical functions, the evolutionary relations between memory and consciousness, and the evolution of unified perception.
... In the tDCS protocol, the choice of target is always a key consideration. Despite the appearance of a number of theories over recent years regarding consciousness [33], the mechanisms underlying consciousness remain unknown. Of the four prominent theories, the Global Workspace Theory and the Higher-order Theory emphasize the importance of the frontal cortex in the generation of consciousness, while the Integrated Information Theory and the Recurrent Processing theory stress the importance of the posterior cortex [34]. ...
Frontal transcranial direct current stimulation (tDCS) and parietal tDCS are effective for treating disorders of consciousness (DoC); however, the relative efficacies of these techniques have yet to be determined. This paper compares the neuromodulation effects of frontal and parietal tDCS on DoC. Twenty patients with DoC were recruited and randomly assigned to two groups. One group received single-session frontal tDCS and single-session sham tDCS. The other group received single-session parietal tDCS and single-session sham tDCS. Before and after every tDCS session, we recorded coma recovery scale-revised (CRS-R) values and an electroencephalogram. CRS-R was also used to evaluate the state of consciousness at 9–12-month follow-up. Both single-session frontal and parietal tDCS caused significant changes in the genuine permutation cross-mutual information (G_PCMI) of local frontal and across brain regions (p < 0.05). Furthermore, the changes in G_PCMI values were significantly correlated to the CRS-R scores at 9–12-month follow-up after frontal and parietal tDCS (p < 0.05). The changes in G_PCMI and CRS-R scores were also correlated (p < 0.05). Both frontal tDCS and parietal tDCS exert neuromodulatory effects in DoC and induce significant changes in electrophysiology. G_PCMI can be used to evaluate the neuromodulation effects of tDCS.
... The pursuit of a well-motivated, operational and falsifiable theory of consciousness remains hot in cognitive science (see [94]). Such a theory holds the key to answering fundamental questions in psychology, neuroscience, cybernetics, artificial intelligence and robotics. ...
Consciousness has been described as acting as a global workspace that integrates perception , imagination, emotion and action programming for adaptive decision making. The mechanisms of such workspace and their relationships to the phenomenology of consciousness need to be further specified. Much research in this connection has focused on the neural correlates of consciousness, but, arguably, computational modeling can better be used toward this aim. According to Projective Consciousness Model (PCM), consciousness is structured as a viewpoint-dependent, internal space, relying on 3D projective geometry and governed by the action of the Projective Group, as part of a process of active inference. The geometry induces a group-structured subjective perspective on an encoded world model, enabling adaptive perspective taking in agents. Here we review and discuss the PCM. We emphasize the role of projective mechanisms in perception and the appraisal of affective and epistemic values as tied to the motivation of action under an optimization process of free energy minimization. We discuss how these mechanisms enable us to model and simulate group-structured drives in the context of social cognition and to understand mechanisms underpinning empathy, emotion expression and regulation, and approach-avoidance behaviors. We review previous results, drawing on applications in robotics and virtual humans. We briefly discuss future axes of research relating to: applications of the model to simulation-and model-based behavioral science; geometrically structured artificial neural networks; the relevance of the approach for explainable AI and human-machine interactions; as well as the study of the neural correlates of consciousness.
This paper investigates the prospect of developing human-interpretable, explainable artificial intelligence (AI) systems based on active inference and the free energy principle. We first provide a brief overview of active inference, and in particular, of how it applies to the modeling of decision-making, introspection, as well as the generation of overt and covert actions. We then discuss how active inference can be leveraged to design explainable AI systems, namely, by allowing us to model core features of “introspective” processes and by generating useful, human-interpretable models of the processes involved in decision-making. We propose an architecture for explainable AI systems using active inference. This architecture foregrounds the role of an explicit hierarchical generative model, the operation of which enables the AI system to track and explain the factors that contribute to its own decisions, and whose structure is designed to be interpretable and auditable by human users. We outline how this architecture can integrate diverse sources of information to make informed decisions in an auditable manner, mimicking or reproducing aspects of human-like consciousness and introspection. Finally, we discuss the implications of our findings for future research in AI, and the potential ethical considerations of developing AI systems with (the appearance of) introspective capabilities.
Visual illusions provide valuable insights into the brain’s interpretation of the world given sensory inputs. However, the precise manner in which brain activity translates into illusory experiences remains largely unknown. Here, we leverage a brain decoding technique combined with deep neural network (DNN) representations to reconstruct illusory percepts as images from brain activity. The reconstruction model was trained on natural images to establish a link between brain activity and perceptual features and then tested on two types of illusions: illusory lines and neon color spreading. Reconstructions revealed lines and colors consistent with illusory experiences, which varied across the source visual cortical areas. This framework offers a way to materialize subjective experiences, shedding light on the brain’s internal representations of the world.
The Computational Theory of Mind says that the mind is a computing system. It has a long history going back to the idea that thought is a kind of computation. Its modern incarnation relies on analogies with contemporary computing technology and the use of computational models. It comes in many versions, some more plausible than others. This Element supports the theory primarily by its contribution to solving the mind-body problem, its ability to explain mental phenomena, and the success of computational modelling and artificial intelligence. To be turned into an adequate theory, it needs to be made compatible with the tractability of cognition, the situatedness and dynamical aspects of the mind, the way the brain works, intentionality, and consciousness.
Bistable perception follows from observing a static, ambiguous, (visual) stimulus with two possible interpretations. Here, we present an active (Bayesian) inference account of bistable perception and posit that perceptual transitions between different interpretations (i.e. inferences) of the same stimulus ensue from specific eye movements that shift the focus to a different visual feature. Formally, these inferences are a consequence of precision control that determines how confident beliefs are and change the frequency with which one can perceive—and alternate between—two distinct percepts. We hypothesized that there are multiple, but distinct, ways in which precision modulation can interact to give rise to a similar frequency of bistable perception. We validated this using numerical simulations of the Necker cube paradigm and demonstrate the multiple routes that underwrite the frequency of perceptual alternation. Our results provide an (enactive) computational account of the intricate precision balance underwriting bistable perception. Importantly, these precision parameters can be considered the computational homologs of particular neurotransmitters—i.e. acetylcholine, noradrenaline, dopamine—that have been previously implicated in controlling bistable perception, providing a computational link between the neurochemistry and perception.
Understanding the neurobiological mechanisms underlying consciousness remains a significant challenge. Recent evidence suggests that the coupling between distal–apical and basal–somatic dendrites in thick-tufted layer 5 pyramidal neurons (L5 PN ), regulated by the nonspecific-projecting thalamus, is crucial for consciousness. Yet, it is uncertain whether this thalamocortical mechanism can support emergent signatures of consciousness, such as integrated information. To address this question, we constructed a biophysical network of dual-compartment thick-tufted L5 PN , with dendrosomatic coupling controlled by thalamic inputs. Our findings demonstrate that integrated information is maximized when nonspecific thalamic inputs drive the system into a regime of time-varying synchronous bursting. Here, the system exhibits variable spiking dynamics with broad pairwise correlations, supporting the enhanced integrated information. Further, the observed peak in integrated information aligns with criticality signatures and empirically observed layer 5 pyramidal bursting rates. These results suggest that the thalamocortical core of the mammalian brain may be evolutionarily configured to optimize effective information processing, providing a potential neuronal mechanism that integrates microscale theories with macroscale signatures of consciousness.
Objective: Brain connectivity, allowing information to be shared between distinct cortical areas and thus to be processed in an integrated way, has long been considered critical for conscious access. However, the relationship between functional intercortical interactions and the structural connections thought to underlie them is poorly understood. In the present work, we aim to explore this structure-function relationship in patients with disorders of consciousness, and to investigate the interest of exploring both types of connectivity for clinical diagnosis.
Methods: We explore both functional (with an EEG-based metric: the median weighted symbolic mutual information in the theta band) and structural (with a brain MRI-based metric: fractional anisotropy) connectivities in a cohort of 78 patients affected with a disorder of consciousness.
Results: Both metrics could distinguish patients in a vegetative state from patients in minimally conscious state. Crucially, we discovered a significant positive correlation between functional and structural connectivities. We then showed that this structure-function relationship takes place in the long-range cortico-cortical deep white matter bundles involved in the Global Neuronal Workspace theory of consciousness.
Interpretation: Altogether, these results support the interest of a multimodal assessment of brain connectivity to refine the diagnostic and prognostic evaluation of patients with disorders of consciousness.
A realistic understanding of artificial intelligence (AI) technology benefits everyone because most of us interact with it on a daily basis. Promoting AI literacy allows more people to participate in the discussion about the benefits and costs of AI technology, how and when it should be used, and what we want our future with AI to look like in general. Myths and misconceptions about AI can impede these debates and, at worst, lead to bad actions or decisions. This should be avoided. To that end, this document clarifies common myths and misconceptions about AI through simple explanations, supplemented by supporting examples, analogies, and remarks. I hope that a broad audience will find this comprehensive resource useful.
Розглянута специфіка формування процедурних умінь, коли ці уміння детермінуються декларативними інструкціями. Увага приділена аспектам подібності цього процесу в сфері вивчення інформатики та в спортивних тренуваннях. Розглянута динаміка транзиту декларативного знання в процедурні навички та уміння на прикладі виконання послідовностей стандартних дій, кожне з яких не викликає координаційних труднощів. У ході дослідження були отримані і проаналізовані статистичні розподіли швидкостей дій виконання окремих завдань у роботі з файлами і текстами в інтерфейсі Windows. Порівнювались розподіли, відповідні різним спробам виконати пакети завдань великими групами учнів. Застосовано модельний підхід до аналізу статистичних розподілів швидкостей виконання завдань. Експериментальні розподіли в моделі представлено сумами нормальних контурів, зміщених один відносно одного у шкалі швидкості виконання завдання. Кожний нормальний контур в цій моделі відповідав деякому одному з чотирьох станів формування процедурного уміння. Площа під модельним контуром відповідає кількості людей у відповідному стані сформованості уміння. Крайні стани, в цьому контексті, це: стан повільного виконання, коли людина виконує дії усвідомлюючи кожний крок; та стан, який є цільовим у тренуванні, стан швидких дій, коли дії повністю автоматизовані, а сенсо-моторика працює майже без участі свідомості. Від спроби до спроби експериментальні розподіли зміщувались у бік високої швидкодії та звужувались. Аналіз динаміки цього процесу базується на метафорі перекачування площ з під нормальних контурів повільної роботи, під контури швидкісної роботи. Побудовані відповідні графіки. Зроблений аналіз трансформації площ розподілів на предмет динаміки тренувального процесу. Зроблено рекомендації стосовно специфіки тренувань у контексті отриманих результатів.
Organoids and specifically human cerebral organoids (HCOs) are one of the most relevant novelties in the field of biomedical research. Grown either from embryonic or induced pluripotent stem cells, HCOs can be used as in vitro three-dimensional models, mimicking the developmental process and organization of the developing human brain. Based on that, and despite their current limitations, it cannot be assumed that they will never at any stage of development manifest some rudimentary form of consciousness. In the absence of behavioral indicators of consciousness, the theoretical neurobiology of consciousness being applied to unresponsive brain-injured patients can be considered with respect to HCOs. In clinical neurology, it is difficult to discern a capacity for consciousness in unresponsive brain-injured patients who provide no behavioral indicators of consciousness. In such scenarios, a validated neurobiological theory of consciousness, which tells us what the neural mechanisms of consciousness are, could be used to identify a capacity for consciousness. Like the unresponsive patients that provide a diagnostic difficulty for neurologists, HCOs provide no behavioral indicators of consciousness. Therefore, this article discusses how three prominent neurobiological theories of consciousness apply to human cerebral organoids. From the perspective of the Temporal Circuit Hypothesis, the Global Neuronal Workspace Theory, and the Integrated Information Theory, we discuss what neuronal structures and functions might indicate that cerebral organoids have a neurobiological capacity to be conscious.
It would be unwise to dismiss the possibility of human brain organoids developing sentience. However, scepticism about this idea is appropriate when considering current organoids. It is a point of consensus that a brainstem-dead human is not sentient, and current organoids lack a functioning brainstem. There are nonetheless troubling early warning signs, suggesting organoid research may create forms of sentience in the near future. To err on the side of caution, researchers with very different views about the neural basis of sentience should unite behind the “brainstem rule”: if a neural organoid develops or innervates a functioning brainstem that registers and prioritizes its needs, regulates arousal, and leads to sleep-wake cycles, then it is a sentience candidate. If organoid research leads to the creation of sentience candidates, a moratorium or indefinite ban on the creation of the relevant type of organoid may be appropriate. A different way forward, more consistent with existing approaches to animal research, would be to require ethical review and harm-benefit analysis for all research on sentience candidates.
I argue that newborn infants are conscious. I propose a methodology for investigating infant consciousness and I present two approaches for determining whether newborns are conscious. First, I consider behavioral and neurobiological markers of consciousness.Second, I investigate the major theories of consciousness, including both philosophical and scientific theories, and I discuss what they predict about infant consciousness.
The standard approach in the field of consciousness research involves identifying the neural correlates of consciousness (NCCs) by comparing neural activity between conscious and unconscious trials. However, this method has been met with criticism due to the lack of consensus on how to operationalize and measure consciousness. In this paper, I propose an alternative approach: the exclusionary approach. Rather than utilizing near-threshold conditions to contrast conscious and unconscious trials, this approach leverages the widely accepted notion that subjective reports are reliable under normal conditions. I propose that this can be done by assessing whether consciousness remains stable across trials while manipulating other factors such as reports, tasks, stimulation, or attention. We can use the resulting contrast to exclude certain kinds of neural activity as candidate NCCs. This method produces results that are less contentious, allowing for the establishment of hard criteria for theories of consciousness. Additionally, this approach does not require the development of new research paradigms, but can incorporate existing studies, particularly those aimed at identifying confounding factors in the standard approach. It is important to note, however, that the proposed exclusionary approach does not negate the value of the identification approach. Rather, they should be considered as complementary methods.
Recently, Kirchhoff and Kiverstein have argued that the extended consciousness thesis, namely the claim that the material vehicles of consciousness extend beyond our heads, is entirely compatible with, and actually mandated by, a correct interpretation of the predictive processing framework. To do so, they rely on a potent argument in favor of the extended consciousness thesis, namely the Dynamical Entanglement and Unique Temporal Signature (DEUTS) argument. Here, we will critically examine Kirchhoff and Kiverstein’s endeavor, arguing for the following three claims. First, we will claim that Kirchhoff and Kiverstein’s emphasis on culture and cultural practices does not help them substantiate the extended consciousness thesis. Secondly, we will argue that the way in which Kirchhoff and Kiverstein formalize the boundaries of a subject’s conscious mind is inadequate, as it yields conclusions running counter some of their assumptions. Lastly, we will argue that the DEUTS argument does not establish the extended consciousness thesis, as it licenses a phenomenal bloat objection which is exactly analogous to the “cognitive bloat” objection to the extended mind thesis. We will thus conclude that Kirchhoff and Kiverstein’s proposed marriage between the extended consciousness thesis and predictive processing fails, and that, contrary to a popular opinion, DEUTS is not a strong argument in favor of the extended consciousness thesis.
The authors postulate that their recently published theory explaining the essence of human self-awareness is useful to consider whether a personal planetary consciousness is emerging on our planet. Their earlier published theory posits that the feeling of self-awareness can be effectively explained when it is assumed that it arises as a result of the interaction of three processes, namely the feeling of qualia, the recurrent activity of neural circuits realizing the self-image, and the formation of the brain's electromagnetic field, important for the sense of subjectivity. This allows the authors in the next stage of inference to consider whether it is possible to find analogical elements and processes on a planetary scale. The authors specify the layers of distributed intelligence emerging on Earth. This allows them to consider the concept of a planetary global brain. The authors believe that the recent, quite unexpected, widespread use of new global-scale artificial intelligence systems such as Chat/GPT is an argument in favor of the formation of a global brain. Next, the authors mention the first known published intuitions related to planetary consciousness, especially Teilhard de Chardin's concept of the noosphere. The authors also indicate the observable manifestations of existence of alleged planetary consciousness. They believe that people's transcendent feelings should be considered as such its manifestation. They hypothesize that the recently observed polarization of worldviews is also magnified by alleged emerging planetary consciousness. The authors, drawing on the analogy between brain hemisphere specialization and the planet's two ideological blocks, conclude that it's vital to patiently moderate conflicts and accept that altering this pattern is unfeasible. Some other practical conclusions are also formulated.
تأثیــر میدان هــای شــعوری (ط) بــر مــواد و موجــودات زنــده در مطالعــات متعــدد مــورد بررســی قــرار گرفتــه اســت. بــا توجــه بــه عــدم رخــداد مداخلــه فیزیکــی در مطالعــات بررســی اثرگــذاری میدان هــای شــعوری (ط)، نتایــج حاصلــه گویــای آنســت کــه اطلاعــات منتقــل شــده از جایــگاه شــعور کل، نقشــی اساســی در تاثیرگــذاری میدان هــای شــعوری (ط) بــر موضــوع مــورد مطالعــه دارد. نویســندگان دو مطالعــه تجربــی پیــش از ایــن پژوهــش داشــته انــد؛ در مطالعــه اول pH آب خالــص تحــت تاثیــر میدان هــای شــعوری (ط) کاهــش یافــت. در مطالعــه دوم، تولیــد انــرژی زیســتی ATP در رده ی ســلولی انســانی HEK-293 بررســی شــد. مشــخص شــد کــه ســلول های تیمــار شــده بــا میدان هــای شــعوری (ط) توانســتند کــه مقــدار بســیار بیــش از انتظــار زیســتی ATP تولیــد کننــد. ایــن انــرژی در بــازه ی زمانــی کوتــاه تیمــار (در محــدوده ی دقیقــه و کمتــر از یــک ســاعت) بــدون گلوکــز مکفــی، ســوخت کربنــی مــورد نیــاز ســلول ها، آزاد شــد. پژوهــش جــاری اثرگــذاری میدان هــای شــعوری (ط) را بــا محاســبه ی میــزان اطلاعــات معاوضــه شــده حیــن دو آزمایــش قبلــی بررســی می کنــد. طبــق تئــوری میدان هــای شــعوری (ط)، دریافــت اطلاعــات از میدان هــای شــعوری (ط) نیازمنــد کالبــد ذهنــی اســت. بــه بیــان دیگــر، رفتــار مولکول هــای آب و رده ســلول انســانی تحــت تاثیــر ایــن میدان هــای شــعوری (ط) تغییــر می کنــد کــه در نتیجــه ی دریافــت اطلاعــات از طریــق کالبــد ذهنــی آنهــا اســت. عــلاوه بــر ایــن، زمــان و منابــع انــدک بــه منظــور تولیــد ATP درســلول های تحــت تاثیــر میدان هــای شــعوری (ط) قویــا پیشــنهاد می کنــد کــه جــدا از مســیر زیســتی تولیــد انــرژی، مســیری جایگزیــن بــرای افزایــش ATP در زمــان فــوری وجــود دارد کــه بــا افزایــش اطلاعــات و کاهــش آنتروپــی سیســتم همــراه اســت. ایــن نــوع انــرژی توســط محمدعلــی طاهــری، " انــرژی تاریــک زیســتی" معرفــی و نامگــذاری شــده اســت.
One of the great frontiers of consciousness science is understanding how early consciousness arises in the development of the human infant. The reciprocal relationship between the default mode network and fronto-parietal networks-the dorsal attention and executive control network-is thought to facilitate integration of information across the brain and its availability for a wide set of conscious mental operations. It remains unknown whether the brain mechanism of conscious awareness is instantiated in infants from birth. To address this gap, we investigated the development of the default mode and fronto-parietal networks and of their reciprocal relationship in neonates. To understand the effect of early neonate age on these networks, we also assessed neonates born prematurely or before term-equivalent age. We used the Developing Human Connectome Project, a unique Open Science dataset which provides a large sample of neonatal functional MRI data with high temporal and spatial resolution. Resting state functional MRI data for full-term neonates (n = 282, age 41.2 weeks ± 12 days) and preterm neonates scanned at term-equivalent age (n = 73, 40.9 weeks ± 14.5 days), or before term-equivalent age (n = 73, 34.6 weeks ± 13.4 days), were obtained from the Developing Human Connectome Project, and for a reference adult group (n = 176, 22-36 years), from the Human Connectome Project. For the first time, we show that the reciprocal relationship between the default mode and dorsal attention network was present at full-term birth or term-equivalent age. Although different from the adult networks, the default mode, dorsal attention and executive control networks were present as distinct networks at full-term birth or term-equivalent age, but premature birth was associated with network disruption. By contrast, neonates before term-equivalent age showed dramatic underdevelopment of high-order networks. Only the dorsal attention network was present as a distinct network and the reciprocal network relationship was not yet formed. Our results suggest that, at full-term birth or by term-equivalent age, infants possess key features of the neural circuitry that enables integration of information across diverse sensory and high-order functional modules, giving rise to conscious awareness. Conversely, they suggest that this brain infrastructure is not present before infants reach term-equivalent age. These findings improve understanding of the ontogeny of high-order network dynamics that support conscious awareness and of their disruption by premature birth.
A major debate about the neural correlates of conscious perception concerns its cortical organization, namely, whether it includes the prefrontal cortex (PFC), which mediates executive functions, or it is constrained within posterior cortices. It has been suggested that PFC activity during paradigms investigating conscious perception is conflated with post-perceptual processes associated with reporting the contents of consciousness or feedforward signals originating from exogenous stimulus manipulations and relayed via posterior cortical areas. We addressed this debate by simultaneously probing neuronal populations in the rhesus macaque (Macaca mulatta) PFC during a no-report paradigm, capable of instigating internally generated transitions in conscious perception, without changes in visual stimulation. We find that feature-selective prefrontal neurons are modulated concomitantly with subjective perception and perceptual suppression of their preferred stimulus during both externally induced and internally generated changes in conscious perception. Importantly, this enables reliable single-trial, population decoding of conscious contents. Control experiments confirm significant decoding of stimulus contents, even when oculomotor responses, used for inferring perception, are suppressed. These findings suggest that internally generated changes in the contents of conscious visual perception are reliably reflected within the activity of prefrontal populations in the absence of volitional reports or changes in sensory input. The role of the prefrontal cortex in conscious perception is debated because of its involvement in task relevant behaviour, such as subjective perceptual reports. Here, the authors show that prefrontal activity in rhesus macaques correlates with subjective perception and the contents of consciousness can be decoded from prefrontal population activity even without reports.
The role of the primate prefrontal cortex (PFC) in conscious perception is debated. The global neuronal workspace theory of consciousness predicts that PFC neurons should contain a detailed code of the current conscious contents. Previous research showed that PFC is indeed activated in paradigms of conscious visual perception, including no-report paradigms where no voluntary behavioral report of the percept is given, thus avoiding a conflation of signals related to visual consciousness with signals related to the report. Still, it has been argued that prefrontal modulation could reflect post-perceptual processes that may be present even in the absence of report, such as thinking about the perceived stimulus, therefore reflecting a consequence rather than a direct correlate of conscious experience. Here, we investigate these issues by recording neuronal ensemble activity from the macaque ventrolateral PFC during briefly presented visual stimuli, either in isolated trials in which stimuli were clearly perceived or in sequences of rapid serial visual presentation (RSVP) in which perception and post-perceptual processing were challenged. We report that the identity of each stimulus could be decoded from PFC population activity even in the RSVP condition. The first visual signals could be detected at 60 ms after stimulus onset and information was maximal at 150 ms. However, in the RSVP condition, 200 ms after the onset of a stimulus, the decoding accuracy quickly dropped to chance level and the next stimulus started to be decodable. Interestingly, decoding in the ventrolateral PFC was stronger compared to posterior parietal cortex for both isolated and RSVP stimuli. These results indicate that neuronal populations in the macaque PFC reliably encode visual stimuli even under conditions that have been shown to challenge conscious perception and/or substantially reduce the probability of post-perceptual processing in humans. We discuss whether the observed activation reflects conscious access, phenomenal consciousness, or merely a preconscious bottom-up wave.
Understanding how consciousness arises from neural activity remains one of the biggest challenges for neuroscience. Numerous theories have been proposed in recent years, each gaining independent empirical support. Currently, there is no comprehensive, quantitative and theory-neutral overview of the field that enables an evaluation of how theoretical frameworks interact with empirical research. We provide a bird’s eye view of studies that interpreted their findings in light of at least one of four leading neuroscientific theories of consciousness (N = 412 experiments), asking how methodological choices of the researchers might affect the final conclusions. We found that supporting a specific theory can be predicted solely from methodological choices, irrespective of findings. Furthermore, most studies interpret their findings post hoc, rather than a priori testing critical predictions of the theories. Our results highlight challenges for the field and provide researchers with an open-access website (https://ContrastDB.tau.ac.il) to further analyse trends in the neuroscience of consciousness. Yaron and colleagues collected and classified 412 experiments relating to four leading theories in consciousness research, providing a comprehensive overview of the field and unravelling trends and methodological biases.
Perception results from the interplay of sensory input and prior knowledge. Despite behavioral evidence that long-term priors powerfully shape perception, the neural mechanisms underlying these interactions remain poorly understood. We obtained direct cortical recordings in neurosurgical patients as they viewed ambiguous images that elicit constant perceptual switching. We observe top-down influences from the temporal to occipital cortex, during the preferred percept that is congruent with the long-term prior. By contrast, stronger feedforward drive is observed during the non-preferred percept, consistent with a prediction error signal. A computational model based on hierarchical predictive coding and attractor networks reproduces all key experimental findings. These results suggest a pattern of large-scale information flow change underlying long-term priors’ influence on perception and provide constraints on theories about long-term priors’ influence on perception.
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.
Recently, the mechanistic framework of active inference has been put forward as a principled foundation to develop an overarching theory of consciousness which would help address conceptual disparities in the field (Wiese 2018; Hohwy and Seth 2020). For that promise to bear out, we argue that current proposals resting on the active inference scheme need refinement to become a process theory of consciousness. One way of improving a theory in mechanistic terms is to use formalisms such as computational models that implement, attune and validate the conceptual notions put forward. Here, we examine how computational modelling approaches have been used to refine the theoretical proposals linking active inference and consciousness, with a focus on the extent and success to which they have been developed to accommodate different facets of consciousness and experimental paradigms, as well as how simulations and empirical data have been used to test and improve these computational models. While current attempts using this approach have shown promising results, we argue they remain preliminary in nature. To refine their predictive and structural validity, testing those models against empirical data is needed i.e., new and unobserved neural data. A remaining challenge for active inference to become a theory of consciousness is to generalize the model to accommodate the broad range of consciousness explananda; and in particular to account for the phenomenological aspects of experience. Notwithstanding these gaps, this approach has proven to be a valuable avenue for theory advancement and holds great potential for future research.
Championing open science, an adversarial collaboration aims to unravel the footprints of consciousness
[This corrects the article DOI: 10.1093/nc/niab011.].
The neural mechanisms underlying conscious recognition remain unclear, particularly the roles played by the prefrontal cortex, deactivated brain areas and subcortical regions. We investigated neural activity during conscious object recognition using 7 Tesla fMRI while human participants viewed object images presented at liminal contrasts. Here, we show both recognized and unrecognized images recruit widely distributed cortical and subcortical regions; however, recognized images elicit enhanced activation of visual, frontoparietal, and subcortical networks and stronger deactivation of the default-mode network. For recognized images, object category information can be decoded from all of the involved cortical networks but not from subcortical regions. Phase-scrambled images trigger strong involvement of inferior frontal junction, anterior cingulate cortex and default-mode network, implicating these regions in inferential processing under increased uncertainty. Our results indicate that content-specific activity in both activated and deactivated cortical networks and non-content-specific subcortical activity support conscious recognition.
To study consciousness, scientists need to determine when participants are conscious and when they are not. They do so with consciousness detection procedures. A recurring skeptical argument against those procedures is that they cannot be calibrated: there is no way to make sure that detection outcomes are accurate. In this article, I address two main skeptical arguments purporting to show that consciousness scientists cannot calibrate detection procedures. I conclude that there is nothing wrong with calibration in consciousness science.
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.
A central debate in philosophy and neuroscience pertains to whether PFC activity plays an essential role in the neural basis of consciousness. Neuroimaging and electrophysiology studies have revealed that the contents of conscious perceptual experience can be successfully decoded from PFC activity, but these findings might be confounded by postperceptual cognitive processes, such as thinking, reasoning, and decision-making, that are not necessary for consciousness. To clarify the involvement of the PFC in consciousness, we present a synthesis of research that has used intracranial electrical stimulation (iES) for the causal modulation of neural activity in the human PFC. This research provides compelling evidence that iES of only certain prefrontal regions (i.e., orbitofrontal cortex and anterior cingulate cortex) reliably perturbs conscious experience. Conversely, stimulation of anterolateral prefrontal sites, often considered crucial in higher-order and global workspace theories of consciousness, seldom elicits any reportable alterations in consciousness. Furthermore, the wide variety of iES-elicited effects in the PFC (e.g., emotions, thoughts, and olfactory and visual hallucinations) exhibits no clear relation to the immediate environment. Therefore, there is no evidence for the kinds of alterations in ongoing perceptual experience that would be predicted by higher-order or global workspace theories. Nevertheless, effects in the orbitofrontal and anterior cingulate cortices suggest a specific role for these PFC subregions in supporting emotional aspects of conscious experience. Overall, this evidence presents a challenge for higher-order and global workspace theories, which commonly point to the PFC as the basis for conscious perception based on correlative and possibly confounded information.
This paper addresses what we consider to be the most pressing challenge for the emerging science of consciousness: the measurement problem of consciousness. That is, by what methods can we determine the presence of and properties of consciousness? Most methods are currently developed through evaluation of the presence of consciousness in humans and here we argue that there are particular problems in application of these methods to non-human cases - what we call the indicator validity problem and the extrapolation problem. The first is a problem with the application of indicators developed using the differences in conscious and unconscious processing in humans to the identification of other conscious vs. non-conscious organisms or systems. The second is a problem in extrapolating any indicators developed in humans or other organisms to artificial systems. However, while pressing ethical concerns add urgency in the attribution of consciousness and its attendant moral status to non-human animals and intelligent machines, we cannot wait for certainty and we advocate the use of a precautionary principle to avoid doing unintentional harm. We also intend that the considerations and limitations discussed in this paper can be used to further analyse and refine the methods of consciousness science with the hope that one day we may be able to solve the measurement problem of consciousness.
An outstanding challenge for consciousness research is to characterize the neural signature of conscious access independently of any decisional processes. Here we present a model-based approach that uses inter-trial variability to identify the brain dynamics associated with stimulus processing. We demonstrate that, even in the absence of any task or behavior, the electroencephalographic response to auditory stimuli shows bifurcation dynamics around 250–300 milliseconds post-stimulus. Namely, the same stimulus gives rise to late sustained activity on some trials, and not on others. This late neural activity is predictive of task-related reports, and also of reports of conscious contents that are randomly sampled during task-free listening. Source localization further suggests that task-free conscious access recruits the same neural networks as those associated with explicit report, except for frontal executive components. Studying brain dynamics through variability could thus play a key role for identifying the core signatures of conscious access, independent of report.
The search for the neural correlates of consciousness is in need of a systematic, principled foundation that can endow putative neural correlates with greater predictive and explanatory value. Here, we propose the predictive processing framework for brain function as a promising candidate for providing this systematic foundation. The proposal is motivated by that framework’s ability to address three general challenges to identifying the neural correlates of consciousness, and to satisfy two constraints common to many theories of consciousness. Implementing the search for neural correlates of consciousness through the lens of predictive processing delivers strong potential for predictive and explanatory value through detailed, systematic mappings between neural substrates and phenomenological structure. We conclude that the predictive processing framework, precisely because it at the outset is not itself a theory of consciousness, has significant potential for advancing the neuroscience of consciousness.
At present, the science of consciousness is structured around the search for the neural correlates of consciousness (the NCCs). One of the alleged advantages of the NCCs framework is its metaphysical neutrality—the fact that it begs no contested questions with respect to debates about the fundamental nature of consciousness. Here, we argue that even if the NCC framework is metaphysically neutral, it is structurally committed, for it presupposes a certain model—what we call the Lite-Brite model—of consciousness. This, we argue, represents a serious liability for the NCC framework for the plausibility of the Lite-Brite model is very much an open question, and the science of consciousness would be better served by a framework that does not presuppose it. Drawing on interventionist ideas in the philosophy of science, we suggest that the Difference-Maker framework can provide just such an alternative. Instead of searching for the neural correlates of consciousness (NCCs), we ought to be searching for the difference makers of consciousness (DMCs). We detail how a shift to searching DMCs will change both the practice of consciousness science and the interpretation of existing results.
A key aspect of consciousness is that it represents bound or integrated information, prompting an increasing conviction that the physical substrate of consciousness must be capable of encoding integrated information in the brain. However, as Ralph Landauer insisted, ‘information is physical’ so integrated information must be physically integrated. I argue here that nearly all examples of so-called ‘integrated information’, including neuronal information processing and conventional computing, are only temporally integrated in the sense that outputs are correlated with multiple inputs: the information integration is implemented in time, rather than space, and thereby cannot correspond to physically integrated information. I point out that only energy fields are capable of integrating information in space. I describe the conscious electromagnetic information (cemi) field theory which has proposed that consciousness is physically integrated, and causally active, information encoded in the brain’s global electromagnetic (EM) field. I here extend the theory to argue that consciousness implements algorithms in space, rather than time, within the brain’s EM field. I describe how the cemi field theory accounts for most observed features of consciousness and describe recent experimental support for the theory. I also describe several untested predictions of the theory and discuss its implications for the design of artificial consciousness. The cemi field theory proposes a scientific dualism that is rooted in the difference between matter and energy, rather than matter and spirit.
Recent breakthroughs in neurobiology indicate that the time is ripe to understand how cellular-level mechanisms are related to conscious experience. Here, we highlight the biophysical properties of pyramidal cells, which allow them to act as gates that control the evolution of global activation patterns. In conscious states, this cellular mechanism enables complex sustained dynamics within the thalamocortical system, whereas during unconscious states, such signal propagation is prohibited. We suggest that the hallmark of conscious processing is the flexible integration of bottom-up and top-down data streams at the cellular level. This cellular integration mechanism provides the foundation for Dendritic Information Theory, a novel neurobiological theory of consciousness
How does consciousness vary across the animal kingdom? Are some animals ‘more conscious’ than others? This article presents a multidimensional framework for understanding interspecies variation in states of consciousness. The framework distinguishes five key dimensions of variation: perceptual richness, evaluative richness, integration at a time, integration across time, and self-consciousness. For each dimension, existing experiments that bear on it are reviewed and future experiments are suggested. By assessing a given species against each dimension, we can construct a consciousness profile for that species. On this framework, there is no single scale along which species can be ranked as more or less conscious. Rather, each species has its own distinctive consciousness profile.
Is phenomenal consciousness constitutively related to cognitive access? Despite being a fundamental issue for any science of consciousness, its empirical study faces a severe methodological puzzle. Recent years have seen numerous attempts to address this puzzle, either in practice, by offering evidence for a positive or negative answer, or in principle, by proposing a framework for eventual resolution. The present paper critically considers these endeavours, including partial-report, metacognitive and no-report paradigms, as well as the theoretical proposal that we can make progress by studying phenomenal consciousness as a natural kind. It is argued that the methodological puzzle remains obdurately with us and that, for now, we must adopt an attitude of humility towards the phenomenal.
This article is part of the theme issue ‘Perceptual consciousness and cognitive access’.
The Dream Catcher test defines the criteria for a genuine discovery of the neural constituents of phenomenal consciousness. Passing the test implies that some patterns of purely brain-based data directly correspond to the subjective features of phenomenal experience, which would help to bridge the explanatory gap between consciousness and brain. Here, we conducted the Dream Catcher test for the first time in a step-wise and simplified form, capturing its core idea. The Dream Catcher experiment involved a Data Team, which measured participants’ brain activity during sleep and collected dream reports, and a blinded Analysis Team, which was challenged to predict, based solely on brain measurements, whether or not a participant had a dream experience. Using a serial-awakening paradigm, the Data Team prepared 54 1-min polysomnograms of non-rapid eye movement sleep—27 of dreamful sleep and 27 of dreamless sleep (three of each condition from each of the nine participants)—redacting from them all associated participant and dream information. The Analysis Team attempted to classify each recording as either dreamless or dreamful using an unsupervised machine learning classifier, based on hypothesis-driven, extracted features of electroencephalography (EEG) spectral power and electrode location. The procedure was repeated over five iterations with a gradual removal of blindness. At no level of blindness did the Analysis Team perform significantly better than chance, suggesting that EEG spectral power could not be utilized to detect signatures specific to phenomenal consciousness in these data. This study marks the first step towards realizing the Dream Catcher test in practice.
Information processing in neural systems can be described and analyzed at multiple spatiotemporal scales. Generally, information at lower levels is more fine-grained but can be coarse-grained at higher levels. However, only information processed at specific scales of coarse-graining appears to be available for conscious awareness. We do not have direct experience of information available at the scale of individual neurons, which is noisy and highly stochastic. Neither do we have experience of more macro-scale interactions, such as interpersonal communications. Neurophysiological evidence suggests that conscious experiences co-vary with information encoded in coarse-grained neural states such as the firing pattern of a population of neurons. In this article, we introduce a new informational theory of consciousness: Information Closure Theory of Consciousness (ICT). We hypothesize that conscious processes are processes which form non-trivial informational closure (NTIC) with respect to the environment at certain coarse-grained scales. This hypothesis implies that conscious experience is confined due to informational closure from conscious processing to other coarse-grained scales. Information Closure Theory of Consciousness (ICT) proposes new quantitative definitions of both conscious content and conscious level. With the parsimonious definitions and a hypothesize, ICT provides explanations and predictions of various phenomena associated with consciousness. The implications of ICT naturally reconcile issues in many existing theories of consciousness and provides explanations for many of our intuitions about consciousness. Most importantly, ICT demonstrates that information can be the common language between consciousness and physical reality.
This article discusses a hypothesis recently put forward by Kanai et al., according to which information generation constitutes a functional basis of, and a sufficient condition for, consciousness. Information generation involves the ability to compress and subsequently decompress information, potentially after a temporal delay and adapted to current purposes. I will argue that information generation should not be regarded as a sufficient condition for consciousness, but could serve as what I will call a “minimal unifying model of consciousness.” A minimal unifying model (MUM) specifies at least one necessary feature of consciousness, characterizes it in a determinable way, and shows that it is entailed by (many) existing theories of consciousness. Information generation fulfills these requirements. A MUM of consciousness is useful, because it unifies existing theories of consciousness by highlighting their common assumptions, while enabling further developments from which empirical predictions can be derived. Unlike existing theories (which probably contain at least some false assumptions), a MUM is thus likely to be an adequate model of consciousness, albeit at a relatively general level. Assumptions embodied in such a model are less informative than assumptions made by more specific theories and hence function more in the way of guiding principles. Still, they enable further refinements, in line with new empirical results and broader theoretical and evolutionary considerations. This also allows developing the model in ways that facilitate more specific claims and predictions.
Intracranial electrical stimulation (iES) of the human brain has long been known to elicit a remarkable variety of perceptual, motor and cognitive effects, but the functional–anatomical basis of this heterogeneity remains poorly understood. We conducted a whole-brain mapping of iES-elicited effects, collecting first-person reports following iES at 1,537 cortical sites in 67 participants implanted with intracranial electrodes. We found that intrinsic network membership and the principal gradient of functional connectivity strongly predicted the type and frequency of iES-elicited effects in a given brain region. While iES in unimodal brain networks at the base of the cortical hierarchy elicited frequent and simple effects, effects became increasingly rare, heterogeneous and complex in heteromodal and transmodal networks higher in the hierarchy. Our study provides a comprehensive exploration of the relationship between the hierarchical organization of intrinsic functional networks and the causal modulation of human behaviour and experience with iES. Intracranial brain stimulation in humans elicits a large variety of perceptual, motor and cognitive effects. Fox et al. show strong links between the distribution and content of these responses and the brain’s intrinsic network architecture.
An increasing number of studies highlight common brain regions and processes in mediating conscious sensory experience. While most studies have been performed in the visual modality, it is implicitly assumed that similar processes are involved in other sensory modalities. However, the existence of supramodal neural processes related to conscious perception has not been convincingly shown so far. Here, we aim to directly address this issue by investigating whether neural correlates of conscious perception in one modality can predict conscious perception in a different modality. In two separate experiments, we presented participants with successive blocks of near-threshold tasks involving subjective reports of tactile, visual, or auditory stimuli during the same magnetoencephalography (MEG) acquisition. Using decoding analysis in the poststimulus period between sensory modalities, our first experiment uncovered supramodal spatiotemporal neural activity patterns predicting conscious perception of the feeble stimulation. Strikingly, these supramodal patterns included activity in primary sensory regions not directly relevant to the task (e.g., neural activity in visual cortex predicting conscious perception of auditory near-threshold stimulation). We carefully replicate our results in a control experiment that furthermore show that the relevant patterns are independent of the type of report (i.e., whether conscious perception was reported by pressing or withholding a button press). Using standard paradigms for probing neural correlates of conscious perception, our findings reveal a common signature of conscious access across sensory modalities and illustrate the temporally late and widespread broadcasting of neural representations, even into task-unrelated primary sensory processing regions.
Humans have the ability to report the contents of their subjective experience—we can say to each other, ‘I am aware of X’. The decision processes that support these reports about mental contents remain poorly understood. In this article, I propose a computational framework that characterizes awareness reports as metacognitive decisions (inference) about a generative model of perceptual content. This account is motivated from the perspective of how flexible hierarchical state spaces are built during learning and decision-making. Internal states supporting awareness reports, unlike those covarying with perceptual contents, are simple and abstract, varying along a 1D continuum from absent to present. A critical feature of this architecture is that it is both higher-order and asymmetric: a vast number of perceptual states is nested under ‘present’, but a much smaller number of possible states nested under ‘absent’. Via simulations, I show that this asymmetry provides a natural account of observations of ‘global ignition’ in brain imaging studies of awareness reports.
Predictive processing (PP) is now a prominent theoretical framework in the philosophy of mind and cognitive science. This review focuses on PP research with a relatively philosophical focus, taking stock of the framework and discussing new directions. The review contains an introduction that describes the full PP toolbox; an exploration of areas where PP has advanced understanding of perceptual and cognitive phenomena; a discussion of PP's impact on foundational issues in cognitive science; and a consideration of the philosophy of science of PP. The overall picture is that PP is a fruitful framework, with exciting new directions awaiting exploration.
There is no agreement on whether any invertebrates are conscious and no agreement on a methodology that could settle the issue. How can the debate move forward? I distinguish three broad types of approach: theory-heavy, theory-neutral and theory-light. Theory-heavy and theory-neutral approaches face serious problems, motivating a middle path: the theory-light approach. At the core of the theory-light approach is a minimal commitment about the relation between phenomenal consciousness and cognition that is compatible with many specific theories of consciousness: the hypothesis that phenomenally conscious perception of a stimulus facilitates, relative to unconscious perception, a cluster of cognitive abilities in relation to that stimulus. This “facilitation hypothesis” can productively guide inquiry into invertebrate consciousness. What is needed? At this stage, not more theory, and not more undirected data gathering. What is needed is a systematic search for consciousness-linked cognitive abilities, their relationships to each other, and their sensitivity to masking.
Ordinary human experience is embedded in a web of causal relations that link the brain to the body and the wider environment. However, there might be conditions in which brain activity supports consciousness even when that activity is fully causally isolated from the body and its environment. Such cases would involve what we call islands of awareness: conscious states that are neither shaped by sensory input nor able to be expressed by motor output. This opinion article considers conditions in which such islands might occur, including ex cranio brains, hemispherotomy, and in cerebral organoids. We examine possible methods for detecting islands of awareness, and consider their implications for ethics and for the nature of consciousness.
There must be a reason why an experience feels the way it does. A good place to begin addressing this question is spatial experience, because it may be more penetrable by introspection than other qualities of consciousness such as color or pain. Moreover, much of experience is spatial, from that of our body to the visual world, which appears as if painted on an extended canvas in front of our eyes. Because it is ‘right there’, we usually take space for granted and overlook its qualitative properties. However, we should realize that a great number of phenomenal distinctions and relations are required for the canvas of space to feel ‘extended’. Here we argue that, to be experienced as extended, the canvas of space must be composed of countless spots, here and there, small and large, and these spots must be related to each other in a characteristic manner through connection, fusion, and inclusion. Other aspects of the structure of spatial experience follow from extendedness: every spot can be experienced as enclosing a particular region, with its particular location, size, boundary, and distance from other spots. We then propose an account of the phenomenal properties of spatial experiences based on integrated information theory (IIT). The theory provides a principled approach for characterizing both the quantity and quality of experience by unfolding the cause-effect structure of a physical substrate. Specifically, we show that a simple simulated substrate of units connected in a grid-like manner yields a cause-effect structure whose properties can account for the main properties of spatial experience. These results uphold the hypothesis that our experience of space is supported by brain areas whose units are linked by a grid-like connectivity. They also predict that changes in connectivity, even in the absence of changes in activity, should lead to a warping of experienced space. To the extent that this approach provides an initial account of phenomenal space, it may also serve as a starting point for investigating other aspects of the quality of experience and their physical correspondents.
Prominent theories of consciousness emphasise different aspects of neurobiology, such as the integration and diversity of information processing within the brain. Here, we combine graph theory and dynamic functional connectivity to compare resting-state functional MRI data from awake volunteers, propofol-anaesthetised volunteers, and patients with disorders of consciousness, in order to identify consciousness-specific patterns of brain function. We demonstrate that cortical networks are especially affected by loss of consciousness during temporal states of high integration, exhibiting reduced functional diversity and compromised informational capacity, whereas thalamo-cortical functional disconnections emerge during states of higher segregation. Spatially, posterior regions of the brain’s default mode network exhibit reductions in both functional diversity and integration with the rest of the brain during unconsciousness. These results show that human consciousness relies on spatio-temporal interactions between brain integration and functional diversity, whose breakdown may represent a generalisable biomarker of loss of consciousness, with potential relevance for clinical practice.
I introduce an empirically-grounded version of a higher-order theory of conscious perception. Traditionally, theories of consciousness either focus on the global availability of conscious information, or take conscious phenomenology as a brute fact due to some biological or basic representational properties. Here I argue instead that the key to characterizing the consciousness lies in its connections to belief formation and epistemic justification on a subjective level.
The free energy principle, an influential framework in computational neuroscience and theoretical neurobiology, starts from the assumption that living systems ensure adaptive exchanges with their environment by minimizing the objective function of variational free energy. Following this premise, it claims to deliver a promising integration of the life sciences. In recent work, Markov Blankets, one of the central constructs of the free energy principle, have been applied to resolve debates central to philosophy (such as demarcating the boundaries of the mind). The aim of this paper is twofold. First, we trace the development of Markov blankets starting from their standard application in Bayesian networks, via variational inference, to their use in the literature on active inference. We then identify a persistent confusion in the literature between the formal use of Markov blankets as an epistemic tool for Bayesian inference, and their novel metaphysical use in the free energy framework to demarcate the physical boundary between an agent and its environment. Consequently, we propose to distinguish between ‘Pearl blankets’ to refer to the original epistemic use of Markov blankets and ‘Friston blankets’ to refer to the new metaphysical construct. Second, we use this distinction to critically assess claims resting on the application of Markov blankets to philosophical problems. We suggest that this literature would do well in differentiating between two different research programs: ‘inference with a model’ and ‘inference within a model’. Only the latter is capable of doing metaphysical work with Markov blankets, but requires additional philosophical premises and cannot be justified by an appeal to the success of the mathematical framework alone.
One of the great frontiers of consciousness science is understanding how early consciousness arises in the development of the human infant. The reciprocal relationship between the default mode network (DMN) and frontoparietal networks — the dorsal attention network (DAN) and executive control network (ECN) — is thought to facilitate integration of information across the brain and its availability for conscious access to a wide set of mental operations. It remains unknown whether the brain mechanism of conscious awareness is instated in infants from birth. To address this gap, we asked what the impact of prematurity and neonate age is on the development the default mode and fronto-parietal networks, and of their reciprocal relationship. To address these questions, we used the Developing Human Connectome Project (dHCP), a unique Open Science project which provides a large sample of neonatal functional Magnetic Resonance Imaging (fMRI) data with high temporal and spatial resolution. Resting state fMRI data for full-term neonates (N = 282, age 41.2 w ± 12 d), and preterm neonates scanned at term-equivalent age (TEA) (N = 73, 40.9 w ± 14.5 d), or before TEA (N = 73, 34.6 w ± 13.4 d) were obtained from the dHCP, and for a reference adult group (N = 176, 22 – 36 years), from the Human Connectome Project. For the first time, we show that the reciprocal relationship between the DMN and DAN was present at full-term birth or TEA. Although different from the adult networks, the DMN, DAN and ECN were present as distinct networks at full-term birth or TEA, but premature birth disrupted network development. By contrast, neonates before TEA showed dramatic underdevelopment of high-order networks. Only the DAN was present as a distinct network and the reciprocal network relationship was not yet formed. Our results suggest that, at full-term birth or by term-equivalent age, infants possess key features of the neural circuitry that enables integration of information across diverse sensory and high-order functional modules, giving rise to conscious access. Conversely, they suggest that this brain infrastructure is not present before infants reach term-equivalent age. These findings improve understanding of the ontogeny of high-order network dynamics that support conscious awareness, and of their disruption by premature birth.
Much research on the neural correlates of consciousness (NCC) has focused on two evoked potentials, the P3b and the visual or auditory awareness negativity (VAN, AAN). Surveying a broad range of recent experimental evidence, we find that repeated failures to observe the P3b during conscious perception eliminate it as a putative NCC. Neither the VAN nor the AAN have been dissociated from consciousness; furthermore, a similar neural signal correlates with tactile consciousness. These awareness negativities can be maximal contralateral to the evoking stimulus, are likely generated in underlying sensory cortices, and point to the existence of a generalized perceptual awareness negativity (PAN) reflecting the onset of sensory consciousness.
Recent advances in deep learning have allowed artificial intelligence (AI) to reach near human-level performance in many sensory, perceptual, linguistic, and cognitive tasks. There is a growing need, however, for novel, brain-inspired cognitive architectures. The Global Workspace Theory (GWT) refers to a large-scale system integrating and distributing information among networks of specialized modules to create higher-level forms of cognition and awareness. We argue that the time is ripe to consider explicit implementations of this theory using deep-learning techniques. We propose a roadmap based on unsupervised neural translation between multiple latent spaces (neural networks trained for distinct tasks, on distinct sensory inputs and/or modalities) to create a unique, amodal Global Latent Workspace (GLW). Potential functional advantages of GLW are reviewed, along with neuroscientific implications.
Few people tackle the neural or computational basis of qualitative experience (Frith, 2019). Why? One major reason is that science and philosophy have both struggled to propose how we might even begin to start studying it. Here I propose that metacognitive computations, and the subjective feelings that go along with them, give us a solid starting point. Specifically, perceptual metacognition possesses unique properties that provide a powerful and unique opportunity for studying the neural and computational correlates of subjective experience, falling into three categories: (1) Metacognition is subjective: there is something it is like to feel ‘confident’; (2) Metacognitive processes are objectively characterizable: We can objectively observe metacognitive reports and define computational models to fit to empirical data; (3) Metacognition has multiple hierarchically-dependent “anchors”, presenting a unique computational opportunity for developing sensitive, specific models. I define this Metacognition as a Step Toward Explaining Phenomenology (M-STEP) approach to state that, given these properties, computational models of metacognition represent an empirically-tractable early step in identifying the generative process that constructs qualitative experience. By applying decades of developments in computational cognitive science and formal computational model comparisons to the specific properties of perceptual metacognition, we may reveal new and exciting insights about how the brain constructs subjective conscious experiences and the nature of those experiences themselves.
Feelings are conscious mental events that represent body states as they undergo homeostatic regulation. Feelings depend on the interoceptive nervous system (INS), a collection of peripheral and central pathways, nuclei and cortical regions which continuously sense chemical and anatomical changes in the organism. How such humoral and neural signals come to generate conscious mental states has been a major scientific question. The answer proposed here invokes (1) several distinctive and poorly known physiological features of the INS; and (2) a unique interaction between the body (the ‘object’ of interoception) and the central nervous system (which generates the 'subject' of interoception). The atypical traits of the INS and the direct interactions between neural and non‐neural physiological compartments of the organism, neither of which is present in exteroceptive systems, plausibly explain the qualitative and subjective aspects of feelings, thus accounting for their conscious nature.
Local theories of consciousness state that one is conscious of a feature if it is adequately represented and processed in sensory brain areas, given some background conditions. We challenge the core prediction of local theories based on long‐lasting postdictive effects demonstrating that features can be represented for hundreds of milliseconds in perceptual areas without being consciously perceived. Unlike previous empirical data aimed against local theories, localists cannot explain these effects away by conjecturing that subjects are phenomenally conscious of features that they cannot report. We also discuss alternative explanations that localists could offer.