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Shirbache K, Liaghat A, Saeifar S, Nezameslami A, Shirbacheh A, Nasri H, Namazi H. Ultra-overt therapy: a novel medical approach centered on patient consciousness. Front Integr Neurosci 2024; 18:1457936. [PMID: 39220208 PMCID: PMC11363186 DOI: 10.3389/fnint.2024.1457936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2024] [Accepted: 08/01/2024] [Indexed: 09/04/2024] Open
Abstract
Within the realms of human and artificial intelligence, the concepts of consciousness and comprehension are fundamental distinctions. In the clinical sphere, patient awareness regarding medication and its physiological processes plays a crucial role in determining drug efficacy and outcomes. This article introduces a novel perspective on prescription practices termed "Ultra-Overt Therapy" (UOT). A review of current supporting evidence was conducted through a non-systematic search in PubMed and Google Scholar, focusing on concepts such as the "mind-body relationship," "placebo response," "neuroscience," and "complementary medicine." Our findings, rooted in the mechanisms of the "placebo effect," the intricacies of "intersubjective therapy," the potency of "interoceptive awareness," and other domains of medical science, suggest that UOT holds theoretical promise. Future research endeavors focusing on these areas may elucidate the global impact of this method on medical treatment and patient care.
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Affiliation(s)
| | - Amirreza Liaghat
- Immunology from Concepts and Experiments to Translation, CNRS UMR 5164, Université Bordeaux Montaigne, Bordeaux, France
| | - Sanam Saeifar
- Buchmann Institute for Molecular Life Sciences (BMLS), Cluster of Excellence Frankfurt Macromolecular Complexes (CEF-MC), Goethe University Frankfurt am Main, Frankfurt am Main, Germany
| | | | - Ali Shirbacheh
- Centre Hospitalier de l’agglomération de Nevers, Nevers, France
| | | | - Hamidreza Namazi
- Department of Medical Ethics, School of Medicine, Medical Ethics and History of Medicine Research Center, Tehran University of Medical Science, Tehran, Iran
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Bukh AV, Rybalova EV, Shepelev IA, Vadivasova TE. Classification of musical intervals by spiking neural networks: Perfect student in solfége classes. CHAOS (WOODBURY, N.Y.) 2024; 34:063102. [PMID: 38829796 DOI: 10.1063/5.0210790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Accepted: 05/12/2024] [Indexed: 06/05/2024]
Abstract
We investigate a spike activity of a network of excitable FitzHugh-Nagumo neurons, which is under constant two-frequency auditory signals. The neurons are supplemented with linear frequency filters and nonlinear input signal converters. We show that it is possible to configure the network to recognize a specific frequency ratio (musical interval) by selecting the parameters of the neurons, input filters, and coupling between neurons. A set of appropriately configured subnetworks with different topologies and coupling strengths can serve as a classifier for musical intervals. We have found that the selective properties of the classifier are due to the presence of a specific topology of coupling between the neurons of the network.
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Affiliation(s)
- A V Bukh
- Institute of Physics, Saratov State University, 83 Astrakhanskaya Street, Saratov 410012, Russia
| | - E V Rybalova
- Institute of Physics, Saratov State University, 83 Astrakhanskaya Street, Saratov 410012, Russia
| | - I A Shepelev
- Institute of Physics, Saratov State University, 83 Astrakhanskaya Street, Saratov 410012, Russia
- Almetyevsk State Petroleum Institute, 2 Lenin Street, Almetyevsk 423462, Russia
| | - T E Vadivasova
- Institute of Physics, Saratov State University, 83 Astrakhanskaya Street, Saratov 410012, Russia
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Wei X, Yan Z, Cai L, Lu M, Yi G, Wang J, Dong Y. Aberrant temporal correlations of ongoing oscillations in disorders of consciousness on multiple time scales. Cogn Neurodyn 2023; 17:633-645. [PMID: 37265651 PMCID: PMC10229524 DOI: 10.1007/s11571-022-09852-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 05/19/2022] [Accepted: 07/06/2022] [Indexed: 11/27/2022] Open
Abstract
Changes in neural oscillation amplitude across states of consciousness has been widely reported, but little is known about the link between temporal dynamics of these oscillations on different time scales and consciousness levels. To address this question, we analyzed amplitude fluctuation of the oscillations extracted from spontaneous resting-state EEG recorded from the patients with disorders of consciousness (DOC) and healthy controls. Detrended fluctuation analysis (DFA) and measures of life-time and waiting-time were employed to characterize the temporal structure of EEG oscillations on long time scales (1-20 s) and short time scales (< 1 s), in groups with different consciousness states: patients in minimally conscious state (MCS), patients with unresponsive wakefulness syndrome (UWS) and healthy subjects. Results revealed increased DFA exponents that implies higher long-range temporal correlations (LRTC), especially in the central brain area in alpha and beta bands. On short time scales, declined bursts of oscillations were also observed. All the metrics exhibited lower individual variability in the UWS or MCS group, which may be attributed to the reduced spatial variability of oscillation dynamics. In addition, the temporal dynamics of EEG oscillations showed significant correlations with the behavioral responsiveness of patients. In summary, our findings shows that loss of consciousness is accompanied by alternation of temporal structure in neural oscillations on multiple time scales, and thus may help uncover the mechanism of underlying neuronal correlates of consciousness. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-022-09852-9.
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Affiliation(s)
- Xile Wei
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Zhuang Yan
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Lihui Cai
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Meili Lu
- School of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin, 300222 China
| | - Guosheng Yi
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Jiang Wang
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Yueqing Dong
- Xincheng Hospital of Tianjin University, Tianjin, China
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Yurchenko SB. A systematic approach to brain dynamics: cognitive evolution theory of consciousness. Cogn Neurodyn 2023; 17:575-603. [PMID: 37265655 PMCID: PMC10229528 DOI: 10.1007/s11571-022-09863-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 06/29/2022] [Accepted: 07/21/2022] [Indexed: 12/18/2022] Open
Abstract
The brain integrates volition, cognition, and consciousness seamlessly over three hierarchical (scale-dependent) levels of neural activity for their emergence: a causal or 'hard' level, a computational (unconscious) or 'soft' level, and a phenomenal (conscious) or 'psyche' level respectively. The cognitive evolution theory (CET) is based on three general prerequisites: physicalism, dynamism, and emergentism, which entail five consequences about the nature of consciousness: discreteness, passivity, uniqueness, integrity, and graduation. CET starts from the assumption that brains should have primarily evolved as volitional subsystems of organisms, not as prediction machines. This emphasizes the dynamical nature of consciousness in terms of critical dynamics to account for metastability, avalanches, and self-organized criticality of brain processes, then coupling it with volition and cognition in a framework unified over the levels. Consciousness emerges near critical points, and unfolds as a discrete stream of momentary states, each volitionally driven from oldest subcortical arousal systems. The stream is the brain's way of making a difference via predictive (Bayesian) processing. Its objective observables could be complexity measures reflecting levels of consciousness and its dynamical coherency to reveal how much knowledge (information gain) the brain acquires over the stream. CET also proposes a quantitative classification of both disorders of consciousness and mental disorders within that unified framework.
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Signorelli CM, Boils JD, Tagliazucchi E, Jarraya B, Deco G. From Brain-Body Function to Conscious Interactions. Neurosci Biobehav Rev 2022; 141:104833. [PMID: 36037978 DOI: 10.1016/j.neubiorev.2022.104833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/06/2022] [Accepted: 08/18/2022] [Indexed: 11/15/2022]
Abstract
In this review, we discuss empirical results inspiring the introduction of a formal mathematical multilayer model for the biological neuroscience of conscious experience. First, we motivate the discussion through evidence regarding the dynamic brain. Second, we review different brain-body couplings associated with conscious experience and its potential role in driving brain dynamics. Third, we introduce the machinery of multilayer networks to account for several types of interactions in brain-body systems. Then, a multilayer structure consists of two main generalizations: a formal semantic to study biological systems, and an integrative account for several signatures and models of consciousness. Finally, under this framework, we define composition of layers to account for entangled features of brain-body systems related to conscious experience. As such, a multilayer mathematical framework is highly integrative and thus may be more complete than other models. In this short review, we discuss a variety of empirical results inspiring the introduction of a formal mathematical multilayer model for the biological neuroscience of conscious experience.
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Affiliation(s)
- Camilo Miguel Signorelli
- Department of Computer Science, University of Oxford, Oxford, 7 Parks Rd, OxfordOX1 3QG, United Kingdom; Physiology of Cognition, GIGA-CRC In Vivo Imaging, Allée du 6 Août, 8 (B30), 4000 Sart Tilman, University of Liège, Belgium; Cognitive Neuroimaging Unit, INSERM, CEA, CNRS, Université Paris-Saclay, NeuroSpin center, 91191 Gif/Yvette, France; Computational Neuroscience Group, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain.
| | - Joaquín Díaz Boils
- Universidad Internacional de La Rioja, Avda La Paz, 137, Logroño, La Rioja, Spain
| | - Enzo Tagliazucchi
- Physics Department, University of Buenos Aires, Buenos Aires, Argentina
| | - Bechir Jarraya
- Cognitive Neuroimaging Unit, INSERM, CEA, CNRS, Université Paris-Saclay, NeuroSpin center, 91191 Gif/Yvette, France
| | - Gustavo Deco
- Computational Neuroscience Group, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain
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Reasoning about conscious experience with axiomatic and graphical mathematics. Conscious Cogn 2021; 95:103168. [PMID: 34627099 DOI: 10.1016/j.concog.2021.103168] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 06/02/2021] [Accepted: 06/29/2021] [Indexed: 02/01/2023]
Abstract
We cast aspects of consciousness in axiomatic mathematical terms, using the graphical calculus of general process theories (a.k.a symmetric monoidal categories and Frobenius algebras therein). This calculus exploits the ontological neutrality of process theories. A toy example using the axiomatic calculus is given to show the power of this approach, recovering other aspects of conscious experience, such as external and internal subjective distinction, privacy or unreadability of personal subjective experience, and phenomenal unity, one of the main issues for scientific studies of consciousness. In fact, these features naturally arise from the compositional nature of axiomatic calculus.
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Signorelli CM, Szczotka J, Prentner R. Explanatory profiles of models of consciousness - towards a systematic classification. Neurosci Conscious 2021; 2021:niab021. [PMID: 34457353 PMCID: PMC8396118 DOI: 10.1093/nc/niab021] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 05/27/2021] [Accepted: 08/18/2021] [Indexed: 11/14/2022] Open
Abstract
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.
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Affiliation(s)
- Camilo Miguel Signorelli
- Cognitive Neuroimaging Unit, INSERM U992, NeuroSpin, CEA, Gif sur Yvette F-91191, France
- Department of Computer Science, University of Oxford, 15 Parks Rd, Oxford OX1 3QD, UK
- Center for Brain and Cognition, Universitat Pompeu Fabra, Edifici Merce Rodereda, Carrer de Ramon Trias Fargas, 25, Barcelona 08018, Spain
| | - Joanna Szczotka
- Center for Sleep and Consciousness, University of Wisconsin-Madison, 6001 Research Park Blvd, Madison WI 53719, USA
- Consciousness Lab, Institute of Psychology, Jagiellonian University, 6 Ingardena, Kraków 30-060, Poland
| | - Robert Prentner
- Department of Cognitive Sciences, University of California, 3151 Social Science Plaza, Irvine CA 92697-5100, USA
- Center for the Future Mind, Florida Atlantic University, 777 Glades Road - SO 283, Boca Raton FL 33431-0991, USA
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Steel M. Modelling aspects of consciousness: A topological perspective. J Theor Biol 2021; 523:110713. [PMID: 33862094 DOI: 10.1016/j.jtbi.2021.110713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 04/06/2021] [Accepted: 04/09/2021] [Indexed: 10/21/2022]
Abstract
Attention Schema Theory (AST) is a recent proposal to provide a scientific explanation for the basis of subjective awareness. In AST, the brain constructs a representation of attention taking place in its own (and others') mind ('the attention schema'). Moreover, this representation is incomplete for efficiency reasons. This inherent incompleteness of the attention schema results in the inability of humans to understand how their own subjective awareness arises (related to the so-called 'hard problem' of consciousness). Given this theory, the present paper asks whether a mind (either human or machine-based) that incorporates attention, and that contains a representation of its own attention, can ever have a complete representation. Using a simple yet general model and a mathematical argument based on classical topology, we show that a complete representation of attention is not possible, since it cannot faithfully represent streams of attention. In this way, the study supports one of the core aspects of AST, that the brain's representation of its own attention is necessarily incomplete.
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Affiliation(s)
- Mike Steel
- Biomathematics Research Centre, University of Canterbury, Christchurch, New Zealand.
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Signorelli CM, Wang Q, Khan I. A Compositional Model of Consciousness Based on Consciousness-Only. ENTROPY (BASEL, SWITZERLAND) 2021; 23:308. [PMID: 33807697 PMCID: PMC8000262 DOI: 10.3390/e23030308] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 02/20/2021] [Accepted: 02/24/2021] [Indexed: 11/17/2022]
Abstract
Scientific studies of consciousness rely on objects whose existence is assumed to be independent of any consciousness. On the contrary, we assume consciousness to be fundamental, and that one of the main features of consciousness is characterized as being other-dependent. We set up a framework which naturally subsumes this feature by defining a compact closed category where morphisms represent conscious processes. These morphisms are a composition of a set of generators, each being specified by their relations with other generators, and therefore co-dependent. The framework is general enough and fits well into a compositional model of consciousness. Interestingly, we also show how our proposal may become a step towards avoiding the hard problem of consciousness, and thereby address the combination problem of conscious experiences.
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Affiliation(s)
- Camilo Miguel Signorelli
- Department of Computer Science, University of Oxford, 15 Parks Rd., Oxford OX1 3QD, UK
- Cognitive Neuroimaging Unit, INSERM U992, NeuroSpin, 91191 Gif-sur-Yvette, France
| | - Quanlong Wang
- Cambridge Quantum Computing Ltd., Cambridge CB2 1UB, UK; (Q.W.); (I.K.)
| | - Ilyas Khan
- Cambridge Quantum Computing Ltd., Cambridge CB2 1UB, UK; (Q.W.); (I.K.)
- St Edmund’s College, University of Cambridge, Cambridge CB3 0BN, UK
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