Theories and measures of consciousness: an extended framework.
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ABSTRACT:
SUBMITTER: Seth AK
PROVIDER: S-EPMC1487169 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The scientific study of consciousness is currently undergoing a critical transition in the form of a rapidly evolving scientific debate regarding whether or not currently proposed theories can be assessed for their scientific validity. At the forefront of this debate is Integrated Information Theory (IIT), widely regarded as the preeminent theory of consciousness because it quantified subjective experience in a scalar mathematical measure called Φ that is in principle measurable. Epistemological issues in the form of the "unfolding argument" have provided a concrete refutation of IIT by demonstrating how it permits functionally identical systems to have differences in their predicted consciousness. The implication is that IIT and any other proposed theory based on a physical system's causal structure may already be falsified even in the absence of experimental refutation. However, so far many of these arguments surrounding the epistemological foundations of falsification arguments, such as the unfolding argument, are too abstract to determine the full scope of their implications. Here, we make these abstract arguments concrete, by providing a simple example of functionally equivalent machines realizable with table-top electronics that take the form of isomorphic digital circuits with and without feedback. This allows us to explicitly demonstrate the different levels of abstraction at which a theory of consciousness can be assessed. Within this computational hierarchy, we show how IIT is simultaneously falsified at the finite-state automaton level and unfalsifiable at the combinatorial-state automaton level. We use this example to illustrate a more general set of falsification criteria for theories of consciousness: to avoid being already falsified, or conversely unfalsifiable, scientific theories of consciousness must be invariant with respect to changes that leave the inference procedure fixed at a particular level in a computational hierarchy.
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Project description:A computational theory of consciousness should include a quantitative measure of consciousness, or MoC, that (i) would reveal to what extent a given system is conscious, (ii) would make it possible to compare not only different systems, but also the same system at different times, and (iii) would be graded, because so is consciousness. However, unless its design is properly constrained, such an MoC gives rise to what we call the boundary problem: an MoC that labels a system as conscious will do so for some-perhaps most-of its subsystems, as well as for irrelevantly extended systems (e.g., the original system augmented with physical appendages that contribute nothing to the properties supposedly supporting consciousness), and for aggregates of individually conscious systems (e.g., groups of people). This problem suggests that the properties that are being measured are epiphenomenal to consciousness, or else it implies a bizarre proliferation of minds. We propose that a solution to the boundary problem can be found by identifying properties that are intrinsic or systemic: properties that clearly differentiate between systems whose existence is a matter of fact, as opposed to those whose existence is a matter of interpretation (in the eye of the beholder). We argue that if a putative MoC can be shown to be systemic, this ipso facto resolves any associated boundary issues. As test cases, we analyze two recent theories of consciousness in light of our definitions: the Integrated Information Theory and the Geometric Theory of consciousness.
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Project description:There is such a vast proliferation of scientific theories of consciousness 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, especially with respect to theoretical elements that do not have a clear neurobiological basis. Rather than dueling theories, an integration across theories is needed to facilitate a comprehensive view on consciousness 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 biophysical theory, MaxCon, which incorporates aspects of several of the main existing neuroscientific consciousness 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. Moreover, a computable index indicating consciousness level is presented. Derived from the level of description of the interactions among cell networks, our proposal highlights the association of consciousness with maximization of the number of configurations of neural network connections -constrained by neuroanatomy, biophysics and the environment- that is common to all consciousness theories.
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Project description:Neuroimaging studies have demonstrated functional interactions between autonomic (ANS) and brain (CNS) structures involved in higher brain functions, including attention and conscious processes. These interactions have been described by the Central Autonomic Network (CAN), a concept model based on the brain-heart two-way integrated interaction. Heart rate variability (HRV) measures proved reliable as non-invasive descriptors of the ANS-CNS function setup and are thought to reflect higher brain functions. Autonomic function, ANS-mediated responsiveness and the ANS-CNS interaction qualify as possible independent indicators for clinical functional assessment and prognosis in Disorders of Consciousness (DoC). HRV has proved helpful to investigate residual responsiveness in DoC and predict clinical recovery. Variability due to internal (e.g., homeostatic and circadian processes) and environmental factors remains a key independent variable and systematic research with this regard is warranted. The interest in bidirectional ANS-CNS interactions in a variety of physiopathological conditions is growing, however, these interactions have not been extensively investigated in DoC. In this brief review we illustrate the potentiality of brain-heart investigation by means of HRV analysis in assessing patients with DoC. The authors' opinion is that this easy, inexpensive and non-invasive approach may provide useful information in the clinical assessment of this challenging patient population.
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Project description:A productive, informative three decades of correlates of phenomenal consciousness (P-Consciousness) have delivered valuable knowledge while simultaneously locating us in a unique and unprecedented explanatory cul-de-sac. Observational correlates are demonstrated to be intrinsically very unlikely to explain or lead to a fundamental principle underlying the strongly emergent 1st-person-perspective (1PP) invisibly stowed away inside them. That lack is now solidly evidenced in practice. To escape our explanatory impasse, this article focuses on fundamental physics (the standard model of particle physics), which brings to light a foundational argument for how the brain is an essentially electromagnetic (EM) field object from the atomic level up. That is, our multitude of correlates of P-Consciousness are actually descriptions of specific EM field behaviors that are posed (hypothesized) as "the right" correlate by a particular theory of consciousness. Because of this, our 30 years of empirical progress can be reinterpreted as, in effect, the delivery of a large body of evidence that the standard model's EM quadrant can deliver a 1PP. That is, all theories of consciousness are, in the end, merely recipes that select a particular subset of the totality of EM field expression that is brain tissue. With a universal convergence on EM, the science of P-Consciousness becomes a collaborative effort between neuroscience and physics. The collaboration acts in pursuit of a unified explanation applicable to all theories of consciousness while remaining mindful that the process still contains no real explanation as to why or how EM fields deliver a 1PP. The apparent continued lack of explanation is, however, different: this time, the way forward is opened through its direct connection to fundamental physics. This is the first result (Part I). Part II posits, in general terms, a structural (epistemic) add-on/upgrade to the standard model that has the potential to deliver the missing route to an explanation of how subjectivity is delivered through EM fields. The revised standard model, under the neuroscience/physics collaboration, intimately integrates with the existing "correlates of-" paradigm, which acts as its source of empirical evidence. No existing theory of consciousness is lost or invalidated.
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Project description:Kinetic Ising models are powerful tools for studying the non-equilibrium dynamics of complex systems. As their behavior is not tractable for large networks, many mean-field methods have been proposed for their analysis, each based on unique assumptions about the system's temporal evolution. This disparity of approaches makes it challenging to systematically advance mean-field methods beyond previous contributions. Here, we propose a unifying framework for mean-field theories of asymmetric kinetic Ising systems from an information geometry perspective. The framework is built on Plefka expansions of a system around a simplified model obtained by an orthogonal projection to a sub-manifold of tractable probability distributions. This view not only unifies previous methods but also allows us to develop novel methods that, in contrast with traditional approaches, preserve the system's correlations. We show that these new methods can outperform previous ones in predicting and assessing network properties near maximally fluctuating regimes.
| S-EPMC7895831 | biostudies-literature
Project description:IntroductionRecognizing the need to teach concepts of health equity, diversity, and inclusion as a part of medical students' preclinical training, we developed a series of workshops in the first year of medical school that introduced students to issues of discrimination and inequity and their effects on health outcomes. This student-led, faculty-supported project, known as Critical Consciousness in Medicine (CCM), adopted critical consciousness as a guiding principle for student learning.MethodsOver the course of the 2018-2019 academic year, student leaders developed and delivered five 2-hour workshops to 197 first-year students, with the assistance of student facilitators and input and guidance from faculty advisors. Workshops involved a mix of whole-class presentations and small-group discussions. Session topics included identity and interpersonal relationships, privilege, health disparities, and implicit bias.ResultsPaired t-test analysis showed statistically significant growth in student self-ratings related to CCM learning objectives as measured in the end-of-year pre-/postsurvey. Student comments in year-end reflections further suggested learning, self-assessment, growth, and appreciation for the workshops' place in the preclinical curriculum.DiscussionThis project modeled a student-faculty partnership for approaching diversity, inclusion, and health equity in medical education and highlighted the role of students as leaders in educating their peers. The CCM workshop series demonstrated high acceptability as a component of preclinical medical education and may increase student engagement around social issues in health care. CCM also illustrated the promise of using critical consciousness as an approach to educating medical students about equity, diversity, and inclusion.
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Project description:Unknown to most Western psychologists, ancient Indian scriptures contain very rich, empirically derived psychological theories that are, however, intertwined with religious and philosophical content. This article represents our attempt to extract the psychological theory of cognition and consciousness from a prominent ancient Indian thought system: Samkhya-Yoga. We derive rather broad hypotheses from this approach that may complement and extend Western mainstream theorizing. These hypotheses address an ancient personality theory, the effects of practicing the applied part of Samkhya-Yoga on normal and extraordinary cognition, as well as different ways of perceiving reality. We summarize empirical evidence collected (mostly without reference to the Indian thought system) in diverse fields of research that allows for making judgments about the hypotheses, and suggest more specific hypotheses to be examined in future research. We conclude that the existing evidence for the (broad) hypotheses is substantial but that there are still considerable gaps in theory and research to be filled. Theories of cognition contained in the ancient Indian systems have the potential to modify and complement existing Western mainstream accounts of cognition. In particular, they might serve as a basis for arriving at more comprehensive theories for several research areas that, so far, lack strong theoretical grounding, such as meditation research or research on aspects of consciousness.
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Project description:The Free Energy Principle and Active Inference Framework (FEP-AI) begins with the understanding that persisting systems must regulate environmental exchanges and prevent entropic accumulation. In FEP-AI, minds and brains are predictive controllers for autonomous systems, where action-driven perception is realized as probabilistic inference. Integrated Information Theory (IIT) begins with considering the preconditions for a system to intrinsically exist, as well as axioms regarding the nature of consciousness. IIT has produced controversy because of its surprising entailments: quasi-panpsychism; subjectivity without referents or dynamics; and the possibility of fully-intelligent-yet-unconscious brain simulations. Here, I describe how these controversies might be resolved by integrating IIT with FEP-AI, where integrated information only entails consciousness for systems with perspectival reference frames capable of generating models with spatial, temporal, and causal coherence for self and world. Without that connection with external reality, systems could have arbitrarily high amounts of integrated information, but nonetheless would not entail subjective experience. I further describe how an integration of these frameworks may contribute to their evolution as unified systems theories and models of emergent causation. Then, inspired by both Global Neuronal Workspace Theory (GNWT) and the Harmonic Brain Modes framework, I describe how streams of consciousness may emerge as an evolving generation of sensorimotor predictions, with the precise composition of experiences depending on the integration abilities of synchronous complexes as self-organizing harmonic modes (SOHMs). These integrating dynamics may be particularly likely to occur via richly connected subnetworks affording body-centric sources of phenomenal binding and executive control. Along these connectivity backbones, SOHMs are proposed to implement turbo coding via loopy message-passing over predictive (autoencoding) networks, thus generating maximum a posteriori estimates as coherent vectors governing neural evolution, with alpha frequencies generating basic awareness, and cross-frequency phase-coupling within theta frequencies for access consciousness and volitional control. These dynamic cores of integrated information also function as global workspaces, centered on posterior cortices, but capable of being entrained with frontal cortices and interoceptive hierarchies, thus affording agentic causation. Integrated World Modeling Theory (IWMT) represents a synthetic approach to understanding minds that reveals compatibility between leading theories of consciousness, thus enabling inferential synergy.
| S-EPMC7861340 | biostudies-literature
Project description:It has been theorized that cortical feed-forward and recurrent neural activity support unconscious and conscious cognitive processes, respectively. Here we causally tested this proposition by applying event-related transcranial magnetic stimulation (TMS) at early and late times relative to visual stimuli, together with a pulse designed to suppress conscious detection. Consistent with pre-registered hypotheses, early TMS affected residual, reportedly 'unseen' capacity. However, conscious perception also appeared critically dependent upon feed-forward processing to a greater extent than the later recurrent phase. Additional exploratory analyses suggested that these early effects dissociated from top-down criterion measures, which were most affected by later TMS. These findings are inconsistent with a simple dichotomy where feed-forward and recurrent processes correspond to unconscious and conscious mechanisms. Instead, different components of awareness may correspond to different phases of cortical dynamics in which initial processing is broadly perceptual whereas later recurrent processing might relate to decision to report.
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