1
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Noble PA, Pozhitkov A, Singh K, Woods E, Liu C, Levin M, Javan G, Wan J, Abouhashem AS, Mathew-Steiner SS, Sen CK. Unraveling the Enigma of Organismal Death: Insights, Implications, and Unexplored Frontiers. Physiology (Bethesda) 2024; 39:0. [PMID: 38624244 DOI: 10.1152/physiol.00004.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 03/21/2024] [Accepted: 04/11/2024] [Indexed: 04/17/2024] Open
Abstract
Significant knowledge gaps exist regarding the responses of cells, tissues, and organs to organismal death. Examining the survival mechanisms influenced by metabolism and environment, this research has the potential to transform regenerative medicine, redefine legal death, and provide insights into life's physiological limits, paralleling inquiries in embryogenesis.
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Affiliation(s)
- Peter A Noble
- Department of Microbiology, University of Alabama Birmingham, Birmingham, Alabama, United States
| | - Alexander Pozhitkov
- Division of Research Informatics, Beckman Research Institute, City of Hope, Duarte, California, United States
| | - Kanhaiya Singh
- Department of Surgery, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
| | - Erik Woods
- Ossium Health, Indianapolis, Indiana, United States
| | - Chunyu Liu
- Institute for Human Performance, Upstate Medical University, Syracuse, New York, United States
| | - Michael Levin
- Department of Biology, Tufts University, Medford, Massachusetts, United States
| | - Gulnaz Javan
- Department of Physical and Forensic Sciences, Alabama State University, Montgomery, Alabama, United States
| | - Jun Wan
- Department of Surgery, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
| | - Ahmed Safwat Abouhashem
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, United States
| | - Shomita S Mathew-Steiner
- Department of Surgery, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
| | - Chandan K Sen
- Department of Surgery, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
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2
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Jaeger J, Riedl A, Djedovic A, Vervaeke J, Walsh D. Naturalizing relevance realization: why agency and cognition are fundamentally not computational. Front Psychol 2024; 15:1362658. [PMID: 38984275 PMCID: PMC11231436 DOI: 10.3389/fpsyg.2024.1362658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Accepted: 05/15/2024] [Indexed: 07/11/2024] Open
Abstract
The way organismic agents come to know the world, and the way algorithms solve problems, are fundamentally different. The most sensible course of action for an organism does not simply follow from logical rules of inference. Before it can even use such rules, the organism must tackle the problem of relevance. It must turn ill-defined problems into well-defined ones, turn semantics into syntax. This ability to realize relevance is present in all organisms, from bacteria to humans. It lies at the root of organismic agency, cognition, and consciousness, arising from the particular autopoietic, anticipatory, and adaptive organization of living beings. In this article, we show that the process of relevance realization is beyond formalization. It cannot be captured completely by algorithmic approaches. This implies that organismic agency (and hence cognition as well as consciousness) are at heart not computational in nature. Instead, we show how the process of relevance is realized by an adaptive and emergent triadic dialectic (a trialectic), which manifests as a metabolic and ecological-evolutionary co-constructive dynamic. This results in a meliorative process that enables an agent to continuously keep a grip on its arena, its reality. To be alive means to make sense of one's world. This kind of embodied ecological rationality is a fundamental aspect of life, and a key characteristic that sets it apart from non-living matter.
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Affiliation(s)
- Johannes Jaeger
- Department of Philosophy, University of Vienna, Vienna, Austria
- Complexity Science Hub (CSH) Vienna, Vienna, Austria
- Ronin Institute, Essex, NJ, United States
| | - Anna Riedl
- Middle European Interdisciplinary Master's Program in Cognitive Science, University of Vienna, Vienna, Austria
| | - Alex Djedovic
- Cognitive Science Program, University of Toronto, Toronto, ON, Canada
- Institute for the History and Philosophy of Science and Technology, University of Toronto, Toronto, ON, Canada
| | - John Vervaeke
- Department of Psychology, University of Toronto, Toronto, ON, Canada
| | - Denis Walsh
- Institute for the History and Philosophy of Science and Technology, University of Toronto, Toronto, ON, Canada
- Department of Philosophy, University of Toronto, Toronto, ON, Canada
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3
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Joy R. An evaluation of the xenobotic cognitive project: Towards Stage 1 of xenobotic cognition. ENDEAVOUR 2024:100927. [PMID: 38679490 DOI: 10.1016/j.endeavour.2024.100927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 10/30/2023] [Accepted: 04/22/2024] [Indexed: 05/01/2024]
Abstract
Xenobot, the world's first biological robot, puts numerous philosophical riddles before us. One among them pertains to the cognitive status of these entities. Are these biological robots cognitive? To evaluate the cognitive status of xenobots and to resolve the puzzle of a single mind emerging from smaller sub-units, in this article, I juxtapose the cognitive capacities of xenobots with that of two other minimal models of cognition, i.e., basal cognition and nonliving active matter cognition. Further, the article underlines the essential cognitive capabilities that xenobots need to achieve to enter what I call stage 1 of xenobotic cognition. Stage 1 is characterized by numerous cognitive mechanisms, which are integral for the survival and cognition of basal organisms. Finally, I suggest that developing xenobots that can reach Stage 1 can help us achieve sophistication in the areas of evolution of the human mind, robotics, biology and medicine, and artificial intelligence (AI).
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Affiliation(s)
- Reshma Joy
- Indian Institute of Technology Ropar, India.
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4
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Tung A, Sperry MM, Clawson W, Pavuluri A, Bulatao S, Yue M, Flores RM, Pai VP, McMillen P, Kuchling F, Levin M. Embryos assist morphogenesis of others through calcium and ATP signaling mechanisms in collective teratogen resistance. Nat Commun 2024; 15:535. [PMID: 38233424 PMCID: PMC10794468 DOI: 10.1038/s41467-023-44522-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 12/17/2023] [Indexed: 01/19/2024] Open
Abstract
Information for organismal patterning can come from a variety of sources. We investigate the possibility that instructive influences for normal embryonic development are provided not only at the level of cells within the embryo, but also via interactions between embryos. To explore this, we challenge groups of embryos with disruptors of normal development while varying group size. Here, we show that Xenopus laevis embryos are much more sensitive to a diverse set of chemical and molecular-biological perturbations when allowed to develop alone or in small groups, than in large groups. Keeping per-embryo exposure constant, we find that increasing the number of exposed embryos in a cohort increases the rate of survival while incidence of defects decreases. This inter-embryo assistance effect is mediated by short-range diffusible signals and involves the P2 ATP receptor. Our data and computational model emphasize that morphogenesis is a collective phenomenon not only at the level of cells, but also of whole bodies, and that cohort size is a crucial variable in studies of ecotoxicology, teratogenesis, and developmental plasticity.
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Affiliation(s)
- Angela Tung
- Allen Discovery Center at Tufts University, Medford, MA, 02155, USA
| | - Megan M Sperry
- Allen Discovery Center at Tufts University, Medford, MA, 02155, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, 02115, USA
| | - Wesley Clawson
- Allen Discovery Center at Tufts University, Medford, MA, 02155, USA
| | - Ananya Pavuluri
- Allen Discovery Center at Tufts University, Medford, MA, 02155, USA
| | - Sydney Bulatao
- Allen Discovery Center at Tufts University, Medford, MA, 02155, USA
| | - Michelle Yue
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, 02115, USA
| | - Ramses Martinez Flores
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, 02115, USA
| | - Vaibhav P Pai
- Allen Discovery Center at Tufts University, Medford, MA, 02155, USA
| | - Patrick McMillen
- Allen Discovery Center at Tufts University, Medford, MA, 02155, USA
| | - Franz Kuchling
- Allen Discovery Center at Tufts University, Medford, MA, 02155, USA
| | - Michael Levin
- Allen Discovery Center at Tufts University, Medford, MA, 02155, USA.
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, 02115, USA.
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5
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Ciaunica A, Levin M, Rosas FE, Friston K. Nested Selves: Self-Organization and Shared Markov Blankets in Prenatal Development in Humans. Top Cogn Sci 2023. [PMID: 38158882 DOI: 10.1111/tops.12717] [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: 05/17/2023] [Revised: 12/05/2023] [Accepted: 12/06/2023] [Indexed: 01/03/2024]
Abstract
The immune system is a central component of organismic function in humans. This paper addresses self-organization of biological systems in relation to-and nested within-other biological systems in pregnancy. Pregnancy constitutes a fundamental state for human embodiment and a key step in the evolution and conservation of our species. While not all humans can be pregnant, our initial state of emerging and growing within another person's body is universal. Hence, the pregnant state does not concern some individuals but all individuals. Indeed, the hierarchical relationship in pregnancy reflects an even earlier autopoietic process in the embryo by which the number of individuals in a single blastoderm is dynamically determined by cell- interactions. The relationship and the interactions between the two self-organizing systems during pregnancy may play a pivotal role in understanding the nature of biological self-organization per se in humans. Specifically, we consider the role of the immune system in biological self-organization in addition to neural/brain systems that furnish us with a sense of self. We examine the complex case of pregnancy, whereby two immune systems need to negotiate the exchange of resources and information in order to maintain viable self-regulation of nested systems. We conclude with a proposal for the mechanisms-that scaffold the complex relationship between two self-organising systems in pregnancy-through the lens of the Active Inference, with a focus on shared Markov blankets.
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Affiliation(s)
- Anna Ciaunica
- Centre for Philosophy of Science (CFCUL), University of Lisbon
- Institute of Cognitive Neuroscience, University College London
| | - Michael Levin
- Department of Biology and Allen Discovery Center, Tufts University
| | - Fernando E Rosas
- Department of Informatics, University of Sussex
- Centre for Complexity Science, Imperial College London
- Department of Brain Sciences, Imperial College London
- Centre for Eudaimonia and Human Flourishing, University of Oxford
| | - Karl Friston
- Welcome Centre for Human Neuroimaging, University College London
- VERSES AI Research Lab
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6
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Watson R. Agency, Goal-Directed Behavior, and Part-Whole Relationships in Biological Systems. BIOLOGICAL THEORY 2023; 19:22-36. [PMID: 38463532 PMCID: PMC10920425 DOI: 10.1007/s13752-023-00447-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 08/17/2023] [Indexed: 03/12/2024]
Abstract
In this essay we aim to present some considerations regarding a minimal but concrete notion of agency and goal-directed behavior that are useful for characterizing biological systems at different scales. These considerations are a particular perspective, bringing together concepts from dynamical systems, combinatorial problem-solving, and connectionist learning with an emphasis on the relationship between parts and wholes. This perspective affords some ways to think about agents that are concrete and quantifiable, and relevant to some important biological issues. Instead of advocating for a strict definition of minimally agential characteristics, we focus on how (even for a modest notion of agency) the agency of a system can be more than the sum of the agency of its parts. We quantify this in terms of the problem-solving competency of a system with respect to resolution of the frustrations between its parts. This requires goal-directed behavior in the sense of delayed gratification, i.e., taking dynamical trajectories that forego short-term gains (or sustain short-term stress or frustration) in favor of long-term gains. In order for this competency to belong to the system (rather than to its parts or given by its construction or design), it can involve distributed systemic knowledge that is acquired through experience, i.e., changes in the organization of the relationships among its parts (without presupposing a system-level reward function for such changes). This conception of agency helps us think about the ways in which cells, organisms, and perhaps other biological scales, can be agential (i.e., more agential than their parts) in a quantifiable sense, without denying that the behavior of the whole depends on the behaviors of the parts in their current organization.
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Affiliation(s)
- Richard Watson
- Institute for Life Sciences/Electronics and Computer Science, University of Southampton, Southampton, UK
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7
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Levin M. Bioelectric networks: the cognitive glue enabling evolutionary scaling from physiology to mind. Anim Cogn 2023; 26:1865-1891. [PMID: 37204591 PMCID: PMC10770221 DOI: 10.1007/s10071-023-01780-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 04/12/2023] [Accepted: 04/24/2023] [Indexed: 05/20/2023]
Abstract
Each of us made the remarkable journey from mere matter to mind: starting life as a quiescent oocyte ("just chemistry and physics"), and slowly, gradually, becoming an adult human with complex metacognitive processes, hopes, and dreams. In addition, even though we feel ourselves to be a unified, single Self, distinct from the emergent dynamics of termite mounds and other swarms, the reality is that all intelligence is collective intelligence: each of us consists of a huge number of cells working together to generate a coherent cognitive being with goals, preferences, and memories that belong to the whole and not to its parts. Basal cognition is the quest to understand how Mind scales-how large numbers of competent subunits can work together to become intelligences that expand the scale of their possible goals. Crucially, the remarkable trick of turning homeostatic, cell-level physiological competencies into large-scale behavioral intelligences is not limited to the electrical dynamics of the brain. Evolution was using bioelectric signaling long before neurons and muscles appeared, to solve the problem of creating and repairing complex bodies. In this Perspective, I review the deep symmetry between the intelligence of developmental morphogenesis and that of classical behavior. I describe the highly conserved mechanisms that enable the collective intelligence of cells to implement regulative embryogenesis, regeneration, and cancer suppression. I sketch the story of an evolutionary pivot that repurposed the algorithms and cellular machinery that enable navigation of morphospace into the behavioral navigation of the 3D world which we so readily recognize as intelligence. Understanding the bioelectric dynamics that underlie construction of complex bodies and brains provides an essential path to understanding the natural evolution, and bioengineered design, of diverse intelligences within and beyond the phylogenetic history of Earth.
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Affiliation(s)
- Michael Levin
- Allen Discovery Center at Tufts University, 200 Boston Ave., Suite 4600, Medford, MA, 02155, USA.
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA.
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8
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Frank SA. Precise Traits from Sloppy Components: Perception and the Origin of Phenotypic Response. ENTROPY (BASEL, SWITZERLAND) 2023; 25:1162. [PMID: 37628192 PMCID: PMC10453304 DOI: 10.3390/e25081162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 06/12/2023] [Accepted: 08/01/2023] [Indexed: 08/27/2023]
Abstract
Organisms perceive their environment and respond. The origin of perception-response traits presents a puzzle. Perception provides no value without response. Response requires perception. Recent advances in machine learning may provide a solution. A randomly connected network creates a reservoir of perceptive information about the recent history of environmental states. In each time step, a relatively small number of inputs drives the dynamics of the relatively large network. Over time, the internal network states retain a memory of past inputs. To achieve a functional response to past states or to predict future states, a system must learn only how to match states of the reservoir to the target response. In the same way, a random biochemical or neural network of an organism can provide an initial perceptive basis. With a solution for one side of the two-step perception-response challenge, evolving an adaptive response may not be so difficult. Two broader themes emerge. First, organisms may often achieve precise traits from sloppy components. Second, evolutionary puzzles often follow the same outlines as the challenges of machine learning. In each case, the basic problem is how to learn, either by artificial computational methods or by natural selection.
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Affiliation(s)
- Steven A Frank
- Department of Ecology and Evolutionary Biology, University of California, Irvine, CA 92697-2525, USA
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9
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Blackiston D, Kriegman S, Bongard J, Levin M. Biological Robots: Perspectives on an Emerging Interdisciplinary Field. Soft Robot 2023; 10:674-686. [PMID: 37083430 PMCID: PMC10442684 DOI: 10.1089/soro.2022.0142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/22/2023] Open
Abstract
Advances in science and engineering often reveal the limitations of classical approaches initially used to understand, predict, and control phenomena. With progress, conceptual categories must often be re-evaluated to better track recently discovered invariants across disciplines. It is essential to refine frameworks and resolve conflicting boundaries between disciplines such that they better facilitate, not restrict, experimental approaches and capabilities. In this essay, we address specific questions and critiques which have arisen in response to our research program, which lies at the intersection of developmental biology, computer science, and robotics. In the context of biological machines and robots, we explore changes across concepts and previously distinct fields that are driven by recent advances in materials, information, and life sciences. Herein, each author provides their own perspective on the subject, framed by their own disciplinary training. We argue that as with computation, certain aspects of developmental biology and robotics are not tied to specific materials; rather, the consilience of these fields can help to shed light on issues of multiscale control, self-assembly, and relationships between form and function. We hope new fields can emerge as boundaries arising from technological limitations are overcome, furthering practical applications from regenerative medicine to useful synthetic living machines.
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Affiliation(s)
- Douglas Blackiston
- Department of Biology, Allen Discovery Center at Tufts University, Medford, Massachusetts, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA
- Institute for Computationally Designed Organisms, Massachusetts and Vermont, USA
| | - Sam Kriegman
- Institute for Computationally Designed Organisms, Massachusetts and Vermont, USA
- Center for Robotics and Biosystems, Northwestern University, Evanston, Illinois, USA
- Center for Synthetic Biology, Northwestern University, Evanston, Illinois, USA
| | - Josh Bongard
- Institute for Computationally Designed Organisms, Massachusetts and Vermont, USA
- Department of Computer Science, University of Vermont, Burlington, Vermont, USA
| | - Michael Levin
- Department of Biology, Allen Discovery Center at Tufts University, Medford, Massachusetts, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA
- Institute for Computationally Designed Organisms, Massachusetts and Vermont, USA
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10
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Fields C, Levin M. Regulative development as a model for origin of life and artificial life studies. Biosystems 2023; 229:104927. [PMID: 37211257 DOI: 10.1016/j.biosystems.2023.104927] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 05/03/2023] [Accepted: 05/08/2023] [Indexed: 05/23/2023]
Abstract
Using the formal framework of the Free Energy Principle, we show how generic thermodynamic requirements on bidirectional information exchange between a system and its environment can generate complexity. This leads to the emergence of hierarchical computational architectures in systems that operate sufficiently far from thermal equilibrium. In this setting, the environment of any system increases its ability to predict system behavior by "engineering" the system towards increased morphological complexity and hence larger-scale, more macroscopic behaviors. When seen in this light, regulative development becomes an environmentally-driven process in which "parts" are assembled to produce a system with predictable behavior. We suggest on this basis that life is thermodynamically favorable and that, when designing artificial living systems, human engineers are acting like a generic "environment".
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Affiliation(s)
- Chris Fields
- Allen Discovery Center at Tufts University, Medford, MA, 02155, USA.
| | - Michael Levin
- Allen Discovery Center at Tufts University, Medford, MA, 02155, USA; Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, 02115, USA
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11
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Ciaunica A, Shmeleva EV, Levin M. The brain is not mental! coupling neuronal and immune cellular processing in human organisms. Front Integr Neurosci 2023; 17:1057622. [PMID: 37265513 PMCID: PMC10230067 DOI: 10.3389/fnint.2023.1057622] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 04/18/2023] [Indexed: 06/03/2023] Open
Abstract
Significant efforts have been made in the past decades to understand how mental and cognitive processes are underpinned by neural mechanisms in the brain. This paper argues that a promising way forward in understanding the nature of human cognition is to zoom out from the prevailing picture focusing on its neural basis. It considers instead how neurons work in tandem with other type of cells (e.g., immune) to subserve biological self-organization and adaptive behavior of the human organism as a whole. We focus specifically on the immune cellular processing as key actor in complementing neuronal processing in achieving successful self-organization and adaptation of the human body in an ever-changing environment. We overview theoretical work and empirical evidence on "basal cognition" challenging the idea that only the neuronal cells in the brain have the exclusive ability to "learn" or "cognize." The focus on cellular rather than neural, brain processing underscores the idea that flexible responses to fluctuations in the environment require a carefully crafted orchestration of multiple cellular and bodily systems at multiple organizational levels of the biological organism. Hence cognition can be seen as a multiscale web of dynamic information processing distributed across a vast array of complex cellular (e.g., neuronal, immune, and others) and network systems, operating across the entire body, and not just in the brain. Ultimately, this paper builds up toward the radical claim that cognition should not be confined to one system alone, namely, the neural system in the brain, no matter how sophisticated the latter notoriously is.
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Affiliation(s)
- Anna Ciaunica
- Centre for Philosophy of Science, Faculty of Science, University of Lisbon, Lisbon, Portugal
- Faculty of Brain Sciences, Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - Evgeniya V. Shmeleva
- Department of Biology, Tufts University, Medford, MA, United States
- Allen Discovery Center, Tufts University, Medford, MA, United States
| | - Michael Levin
- Department of Biology, Tufts University, Medford, MA, United States
- Allen Discovery Center, Tufts University, Medford, MA, United States
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12
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Levin M. Darwin's agential materials: evolutionary implications of multiscale competency in developmental biology. Cell Mol Life Sci 2023; 80:142. [PMID: 37156924 PMCID: PMC10167196 DOI: 10.1007/s00018-023-04790-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Revised: 04/24/2023] [Accepted: 04/27/2023] [Indexed: 05/10/2023]
Abstract
A critical aspect of evolution is the layer of developmental physiology that operates between the genotype and the anatomical phenotype. While much work has addressed the evolution of developmental mechanisms and the evolvability of specific genetic architectures with emergent complexity, one aspect has not been sufficiently explored: the implications of morphogenetic problem-solving competencies for the evolutionary process itself. The cells that evolution works with are not passive components: rather, they have numerous capabilities for behavior because they derive from ancestral unicellular organisms with rich repertoires. In multicellular organisms, these capabilities must be tamed, and can be exploited, by the evolutionary process. Specifically, biological structures have a multiscale competency architecture where cells, tissues, and organs exhibit regulative plasticity-the ability to adjust to perturbations such as external injury or internal modifications and still accomplish specific adaptive tasks across metabolic, transcriptional, physiological, and anatomical problem spaces. Here, I review examples illustrating how physiological circuits guiding cellular collective behavior impart computational properties to the agential material that serves as substrate for the evolutionary process. I then explore the ways in which the collective intelligence of cells during morphogenesis affect evolution, providing a new perspective on the evolutionary search process. This key feature of the physiological software of life helps explain the remarkable speed and robustness of biological evolution, and sheds new light on the relationship between genomes and functional anatomical phenotypes.
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Affiliation(s)
- Michael Levin
- Allen Discovery Center at Tufts University, 200 Boston Ave. 334 Research East, Medford, MA, 02155, USA.
- Wyss Institute for Biologically Inspired Engineering at Harvard University, 3 Blackfan St., Boston, MA, 02115, USA.
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13
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Bongard J, Levin M. There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-Scale Machines. Biomimetics (Basel) 2023; 8:biomimetics8010110. [PMID: 36975340 PMCID: PMC10046700 DOI: 10.3390/biomimetics8010110] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 02/24/2023] [Accepted: 03/01/2023] [Indexed: 03/18/2023] Open
Abstract
The applicability of computational models to the biological world is an active topic of debate. We argue that a useful path forward results from abandoning hard boundaries between categories and adopting an observer-dependent, pragmatic view. Such a view dissolves the contingent dichotomies driven by human cognitive biases (e.g., a tendency to oversimplify) and prior technological limitations in favor of a more continuous view, necessitated by the study of evolution, developmental biology, and intelligent machines. Form and function are tightly entwined in nature, and in some cases, in robotics as well. Thus, efforts to re-shape living systems for biomedical or bioengineering purposes require prediction and control of their function at multiple scales. This is challenging for many reasons, one of which is that living systems perform multiple functions in the same place at the same time. We refer to this as “polycomputing”—the ability of the same substrate to simultaneously compute different things, and make those computational results available to different observers. This ability is an important way in which living things are a kind of computer, but not the familiar, linear, deterministic kind; rather, living things are computers in the broad sense of their computational materials, as reported in the rapidly growing physical computing literature. We argue that an observer-centered framework for the computations performed by evolved and designed systems will improve the understanding of mesoscale events, as it has already done at quantum and relativistic scales. To develop our understanding of how life performs polycomputing, and how it can be convinced to alter one or more of those functions, we can first create technologies that polycompute and learn how to alter their functions. Here, we review examples of biological and technological polycomputing, and develop the idea that the overloading of different functions on the same hardware is an important design principle that helps to understand and build both evolved and designed systems. Learning to hack existing polycomputing substrates, as well as to evolve and design new ones, will have massive impacts on regenerative medicine, robotics, and computer engineering.
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Affiliation(s)
- Joshua Bongard
- Department of Computer Science, University of Vermont, Burlington, VT 05405, USA
| | - Michael Levin
- Allen Discovery Center at Tufts University, 200 Boston Ave., Suite 4600, Medford, MA 02155, USA
- Correspondence: ; Tel.: +(617)-627-6161
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14
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Morales J. Tracing the origins of consciousness. PHILOSOPHICAL PSYCHOLOGY 2023. [DOI: 10.1080/09515089.2023.2176746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Affiliation(s)
- Jorge Morales
- Department of Philosophy, Northeastern University, Huntington Ave, Boston, MA
- Department of Psychology, Northeastern University, Huntington Ave, Boston, MA
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15
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Dodig-Crnkovic G, Miłkowski M. Discussion on the Relationship between Computation, Information, Cognition, and Their Embodiment. ENTROPY (BASEL, SWITZERLAND) 2023; 25:310. [PMID: 36832676 PMCID: PMC9955108 DOI: 10.3390/e25020310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 01/27/2023] [Accepted: 02/03/2023] [Indexed: 06/18/2023]
Abstract
Three special issues of Entropy journal have been dedicated to the topics of "Information-Processing and Embodied, Embedded, Enactive Cognition". They addressed morphological computing, cognitive agency, and the evolution of cognition. The contributions show the diversity of views present in the research community on the topic of computation and its relation to cognition. This paper is an attempt to elucidate current debates on computation that are central to cognitive science. It is written in the form of a dialog between two authors representing two opposed positions regarding the issue of what computation is and could be, and how it can be related to cognition. Given the different backgrounds of the two researchers, which span physics, philosophy of computing and information, cognitive science, and philosophy, we found the discussions in the form of Socratic dialogue appropriate for this multidisciplinary/cross-disciplinary conceptual analysis. We proceed as follows. First, the proponent (GDC) introduces the info-computational framework as a naturalistic model of embodied, embedded, and enacted cognition. Next, objections are raised by the critic (MM) from the point of view of the new mechanistic approach to explanation. Subsequently, the proponent and the critic provide their replies. The conclusion is that there is a fundamental role for computation, understood as information processing, in the understanding of embodied cognition.
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Affiliation(s)
- Gordana Dodig-Crnkovic
- Department of Computer Science and Engineering, Chalmers University of Technology, 412 96 Gothenburg, Sweden
- Division of Computer Science and Software Engineering, School of Innovation, Design and Engineering, Mälardalen University, 722 20 Västerås, Sweden
| | - Marcin Miłkowski
- Institute of Philosophy and Sociology, Polish Academy of Sciences, ul. Nowy Świat 72, 00-330 Warszawa, Poland
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16
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Rana S, Basu A, Ghosh S, Bhattacharya S. Moths exhibit strong memory among cooperative species of other taxonomic groups: An empirical study. Ecol Modell 2023. [DOI: 10.1016/j.ecolmodel.2022.110235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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17
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Shreesha L, Levin M. Cellular Competency during Development Alters Evolutionary Dynamics in an Artificial Embryogeny Model. ENTROPY (BASEL, SWITZERLAND) 2023; 25:e25010131. [PMID: 36673272 PMCID: PMC9858125 DOI: 10.3390/e25010131] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 12/23/2022] [Accepted: 12/29/2022] [Indexed: 05/25/2023]
Abstract
Biological genotypes do not code directly for phenotypes; developmental physiology is the control layer that separates genomes from capacities ascertained by selection. A key aspect is cellular competency, since cells are not passive materials but descendants of unicellular organisms with complex context-sensitive behavioral capabilities. To probe the effects of different degrees of cellular competency on evolutionary dynamics, we used an evolutionary simulation in the context of minimal artificial embryogeny. Virtual embryos consisted of a single axis of positional information values provided by cells' 'structural genes', operated upon by an evolutionary cycle in which embryos' fitness was proportional to monotonicity of the axial gradient. Evolutionary dynamics were evaluated in two modes: hardwired development (genotype directly encodes phenotype), and a more realistic mode in which cells interact prior to evaluation by the fitness function ("regulative" development). We find that even minimal ability of cells with to improve their position in the embryo results in better performance of the evolutionary search. Crucially, we observed that increasing the behavioral competency masks the raw fitness encoded by structural genes, with selection favoring improvements to its developmental problem-solving capacities over improvements to its structural genome. This suggests the existence of a powerful ratchet mechanism: evolution progressively becomes locked in to improvements in the intelligence of its agential substrate, with reduced pressure on the structural genome. This kind of feedback loop in which evolution increasingly puts more effort into the developmental software than perfecting the hardware explains the very puzzling divergence of genome from anatomy in species like planaria. In addition, it identifies a possible driver for scaling intelligence over evolutionary time, and suggests strategies for engineering novel systems in silico and in bioengineering.
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Affiliation(s)
- Lakshwin Shreesha
- UFR Fundamental and Biomedical Sciences, Université Paris Cité, 75006 Paris, France
| | - Michael Levin
- Allen Discovery Center, Tufts University, Medford, MA 02155, USA
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18
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Harrison D, Rorot W, Laukaityte U. Mind the matter: Active matter, soft robotics, and the making of bio-inspired artificial intelligence. Front Neurorobot 2022; 16:880724. [PMID: 36620483 PMCID: PMC9815774 DOI: 10.3389/fnbot.2022.880724] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 10/31/2022] [Indexed: 12/23/2022] Open
Abstract
Philosophical and theoretical debates on the multiple realisability of the cognitive have historically influenced discussions of the possible systems capable of instantiating complex functions like memory, learning, goal-directedness, and decision-making. These debates have had the corollary of undermining, if not altogether neglecting, the materiality and corporeality of cognition-treating material, living processes as "hardware" problems that can be abstracted out and, in principle, implemented in a variety of materials-in particular on digital computers and in the form of state-of-the-art neural networks. In sum, the matter in se has been taken not to matter for cognition. However, in this paper, we argue that the materiality of cognition-and the living, self-organizing processes that it enables-requires a more detailed assessment when understanding the nature of cognition and recreating it in the field of embodied robotics. Or, in slogan form, that the matter matters for cognitive form and function. We pull from the fields of Active Matter Physics, Soft Robotics, and Basal Cognition literature to suggest that the imbrication between material and cognitive processes is closer than standard accounts of multiple realisability suggest. In light of this, we propose upgrading the notion of multiple realisability from the standard version-what we call 1.0-to a more nuanced conception 2.0 to better reflect the recent empirical advancements, while at the same time averting many of the problems that have been raised for it. These fields are actively reshaping the terrain in which we understand materiality and how it enables, mediates, and constrains cognition. We propose that taking the materiality of our embodied, precarious nature seriously furnishes an important research avenue for the development of embodied robots that autonomously value, engage, and interact with the environment in a goal-directed manner, in response to existential needs of survival, persistence, and, ultimately, reproduction. Thus, we argue that by placing further emphasis on the soft, active, and plastic nature of the materials that constitute cognitive embodiment, we can move further in the direction of autonomous embodied robots and Artificial Intelligence.
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Affiliation(s)
- David Harrison
- Department of History and Philosophy of Science, University of Cambridge, Cambridge, United Kingdom,Leverhulme Centre for the Future of Intelligence, Cambridge, United Kingdom,Konrad Lorenz Institute for Evolution and Cognition Research, Vienna, Austria,*Correspondence: David Harrison
| | - Wiktor Rorot
- Human Interactivity and Language Lab, Faculty of Psychology, University of Warsaw, Warsaw, Poland,Wiktor Rorot
| | - Urte Laukaityte
- Department of Philosophy, University of California, Berkeley, Berkeley, CA, United States
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19
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Bearce EA, Irons ZH, Craig SB, Kuhns CJ, Sabazali C, Farnsworth DR, Miller AC, Grimes DT. Daw1 regulates the timely onset of cilia motility during development. Development 2022; 149:275714. [PMID: 35708608 PMCID: PMC9270974 DOI: 10.1242/dev.200017] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 05/05/2022] [Indexed: 12/15/2022]
Abstract
Motile cilia generate cell propulsion and extracellular fluid flows that are crucial for airway clearance, fertility and left-right patterning. Motility is powered by dynein arm complexes that are assembled in the cytoplasm then imported into the cilium. Studies in Chlamydomonas reinhardtii showed that ODA16 is a cofactor which promotes dynein arm import. Here, we demonstrate that the zebrafish homolog of ODA16, Daw1, facilitates the onset of robust cilia motility during development. Without Daw1, cilia showed markedly reduced motility during early development; however, motility subsequently increased to attain close to wild-type levels. Delayed motility onset led to differential effects on early and late cilia-dependent processes. Remarkably, abnormal body axis curves, which formed during the first day of development due to reduced cilia motility, self-corrected when motility later reached wild-type levels. Zebrafish larva therefore possess the ability to survey and correct body shape abnormalities. This work defines Daw1 as a factor which promotes the onset of timely cilia motility and can explain why human patients harboring DAW1 mutations exhibit significant laterality perturbations but mild airway and fertility complications. Summary: Daw1 promotes the onset of timely cilia motility for robust axial straightening during zebrafish development.
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Affiliation(s)
- Elizabeth A Bearce
- Institute of Molecular Biology, Department of Biology, University of Oregon, Eugene, OR 97403, USA
| | - Zoe H Irons
- Institute of Molecular Biology, Department of Biology, University of Oregon, Eugene, OR 97403, USA
| | - Samuel B Craig
- Institute of Molecular Biology, Department of Biology, University of Oregon, Eugene, OR 97403, USA
| | - Colin J Kuhns
- Institute of Molecular Biology, Department of Biology, University of Oregon, Eugene, OR 97403, USA
| | - Cynthia Sabazali
- Institute of Molecular Biology, Department of Biology, University of Oregon, Eugene, OR 97403, USA
| | - Dylan R Farnsworth
- Institute of Neuroscience, Department of Biology, University of Oregon, Eugene, OR 97403, USA
| | - Adam C Miller
- Institute of Neuroscience, Department of Biology, University of Oregon, Eugene, OR 97403, USA
| | - Daniel T Grimes
- Institute of Molecular Biology, Department of Biology, University of Oregon, Eugene, OR 97403, USA
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20
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Fields C, Glazebrook JF, Levin M. Neurons as hierarchies of quantum reference frames. Biosystems 2022; 219:104714. [PMID: 35671840 DOI: 10.1016/j.biosystems.2022.104714] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 05/28/2022] [Accepted: 05/28/2022] [Indexed: 11/19/2022]
Abstract
Conceptual and mathematical models of neurons have lagged behind empirical understanding for decades. Here we extend previous work in modeling biological systems with fully scale-independent quantum information-theoretic tools to develop a uniform, scalable representation of synapses, dendritic and axonal processes, neurons, and local networks of neurons. In this representation, hierarchies of quantum reference frames act as hierarchical active-inference systems. The resulting model enables specific predictions of correlations between synaptic activity, dendritic remodeling, and trophic reward. We summarize how the model may be generalized to nonneural cells and tissues in developmental and regenerative contexts.
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Affiliation(s)
- Chris Fields
- 23 Rue des Lavandières, 11160 Caunes Minervois, France.
| | - James F Glazebrook
- Department of Mathematics and Computer Science, Eastern Illinois University, Charleston, IL 61920, USA; Adjunct Faculty, Department of Mathematics, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Michael Levin
- Allen Discovery Center at Tufts University, Medford, MA 02155, USA
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21
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Fields C, Friston K, Glazebrook JF, Levin M. A free energy principle for generic quantum systems. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2022; 173:36-59. [PMID: 35618044 DOI: 10.1016/j.pbiomolbio.2022.05.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 05/04/2022] [Accepted: 05/18/2022] [Indexed: 01/17/2023]
Abstract
The Free Energy Principle (FEP) states that under suitable conditions of weak coupling, random dynamical systems with sufficient degrees of freedom will behave so as to minimize an upper bound, formalized as a variational free energy, on surprisal (a.k.a., self-information). This upper bound can be read as a Bayesian prediction error. Equivalently, its negative is a lower bound on Bayesian model evidence (a.k.a., marginal likelihood). In short, certain random dynamical systems evince a kind of self-evidencing. Here, we reformulate the FEP in the formal setting of spacetime-background free, scale-free quantum information theory. We show how generic quantum systems can be regarded as observers, which with the standard freedom of choice assumption become agents capable of assigning semantics to observational outcomes. We show how such agents minimize Bayesian prediction error in environments characterized by uncertainty, insufficient learning, and quantum contextuality. We show that in its quantum-theoretic formulation, the FEP is asymptotically equivalent to the Principle of Unitarity. Based on these results, we suggest that biological systems employ quantum coherence as a computational resource and - implicitly - as a communication resource. We summarize a number of problems for future research, particularly involving the resources required for classical communication and for detecting and responding to quantum context switches.
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Affiliation(s)
- Chris Fields
- 23 Rue des Lavandières, 11160, Caunes Minervois, France.
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3AR, UK
| | - James F Glazebrook
- Department of Mathematics and Computer Science, Eastern Illinois University, Charleston, IL, 61920, USA; Adjunct Faculty, Department of Mathematics, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Michael Levin
- Allen Discovery Center at Tufts University, Medford, MA, 02155, USA
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22
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Biology, Buddhism, and AI: Care as the Driver of Intelligence. ENTROPY 2022; 24:e24050710. [PMID: 35626593 PMCID: PMC9140411 DOI: 10.3390/e24050710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 04/28/2022] [Accepted: 05/11/2022] [Indexed: 11/17/2022]
Abstract
Intelligence is a central feature of human beings’ primary and interpersonal experience. Understanding how intelligence originated and scaled during evolution is a key challenge for modern biology. Some of the most important approaches to understanding intelligence are the ongoing efforts to build new intelligences in computer science (AI) and bioengineering. However, progress has been stymied by a lack of multidisciplinary consensus on what is central about intelligence regardless of the details of its material composition or origin (evolved vs. engineered). We show that Buddhist concepts offer a unique perspective and facilitate a consilience of biology, cognitive science, and computer science toward understanding intelligence in truly diverse embodiments. In coming decades, chimeric and bioengineering technologies will produce a wide variety of novel beings that look nothing like familiar natural life forms; how shall we gauge their moral responsibility and our own moral obligations toward them, without the familiar touchstones of standard evolved forms as comparison? Such decisions cannot be based on what the agent is made of or how much design vs. natural evolution was involved in their origin. We propose that the scope of our potential relationship with, and so also our moral duty toward, any being can be considered in the light of Care—a robust, practical, and dynamic lynchpin that formalizes the concepts of goal-directedness, stress, and the scaling of intelligence; it provides a rubric that, unlike other current concepts, is likely to not only survive but thrive in the coming advances of AI and bioengineering. We review relevant concepts in basal cognition and Buddhist thought, focusing on the size of an agent’s goal space (its cognitive light cone) as an invariant that tightly links intelligence and compassion. Implications range across interpersonal psychology, regenerative medicine, and machine learning. The Bodhisattva’s vow (“for the sake of all sentient life, I shall achieve awakening”) is a practical design principle for advancing intelligence in our novel creations and in ourselves.
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23
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Kuchling F, Fields C, Levin M. Metacognition as a Consequence of Competing Evolutionary Time Scales. ENTROPY 2022; 24:e24050601. [PMID: 35626486 PMCID: PMC9141326 DOI: 10.3390/e24050601] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 04/15/2022] [Accepted: 04/19/2022] [Indexed: 12/24/2022]
Abstract
Evolution is full of coevolving systems characterized by complex spatio-temporal interactions that lead to intertwined processes of adaptation. Yet, how adaptation across multiple levels of temporal scales and biological complexity is achieved remains unclear. Here, we formalize how evolutionary multi-scale processing underlying adaptation constitutes a form of metacognition flowing from definitions of metaprocessing in machine learning. We show (1) how the evolution of metacognitive systems can be expected when fitness landscapes vary on multiple time scales, and (2) how multiple time scales emerge during coevolutionary processes of sufficiently complex interactions. After defining a metaprocessor as a regulator with local memory, we prove that metacognition is more energetically efficient than purely object-level cognition when selection operates at multiple timescales in evolution. Furthermore, we show that existing modeling approaches to coadaptation and coevolution—here active inference networks, predator–prey interactions, coupled genetic algorithms, and generative adversarial networks—lead to multiple emergent timescales underlying forms of metacognition. Lastly, we show how coarse-grained structures emerge naturally in any resource-limited system, providing sufficient evidence for metacognitive systems to be a prevalent and vital component of (co-)evolution. Therefore, multi-scale processing is a necessary requirement for many evolutionary scenarios, leading to de facto metacognitive evolutionary outcomes.
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Affiliation(s)
- Franz Kuchling
- Department of Biology, Allen Discovery Center at Tufts University, Medford, MA 02155, USA;
| | - Chris Fields
- 23 Rue des Lavandières, 11160 Caunes Minervois, France;
| | - Michael Levin
- Department of Biology, Allen Discovery Center at Tufts University, Medford, MA 02155, USA;
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02138, USA
- Correspondence:
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24
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Levin M. Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework for Understanding Diverse Bodies and Minds. Front Syst Neurosci 2022; 16:768201. [PMID: 35401131 PMCID: PMC8988303 DOI: 10.3389/fnsys.2022.768201] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 01/24/2022] [Indexed: 12/11/2022] Open
Abstract
Synthetic biology and bioengineering provide the opportunity to create novel embodied cognitive systems (otherwise known as minds) in a very wide variety of chimeric architectures combining evolved and designed material and software. These advances are disrupting familiar concepts in the philosophy of mind, and require new ways of thinking about and comparing truly diverse intelligences, whose composition and origin are not like any of the available natural model species. In this Perspective, I introduce TAME-Technological Approach to Mind Everywhere-a framework for understanding and manipulating cognition in unconventional substrates. TAME formalizes a non-binary (continuous), empirically-based approach to strongly embodied agency. TAME provides a natural way to think about animal sentience as an instance of collective intelligence of cell groups, arising from dynamics that manifest in similar ways in numerous other substrates. When applied to regenerating/developmental systems, TAME suggests a perspective on morphogenesis as an example of basal cognition. The deep symmetry between problem-solving in anatomical, physiological, transcriptional, and 3D (traditional behavioral) spaces drives specific hypotheses by which cognitive capacities can increase during evolution. An important medium exploited by evolution for joining active subunits into greater agents is developmental bioelectricity, implemented by pre-neural use of ion channels and gap junctions to scale up cell-level feedback loops into anatomical homeostasis. This architecture of multi-scale competency of biological systems has important implications for plasticity of bodies and minds, greatly potentiating evolvability. Considering classical and recent data from the perspectives of computational science, evolutionary biology, and basal cognition, reveals a rich research program with many implications for cognitive science, evolutionary biology, regenerative medicine, and artificial intelligence.
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Affiliation(s)
- Michael Levin
- Allen Discovery Center at Tufts University, Medford, MA, United States
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Cambridge, MA, United States
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25
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Josipovic Z. Implicit-explicit gradient of nondual awareness or consciousness as such. Neurosci Conscious 2021; 2021:niab031. [PMID: 34646576 PMCID: PMC8500298 DOI: 10.1093/nc/niab031] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 06/29/2021] [Accepted: 08/19/2021] [Indexed: 01/04/2023] Open
Abstract
Consciousness is multi-dimensional but is most often portrayed with a two-dimensional (2D) map that has global levels or states on one axis and phenomenal contents on the other. On this map, awareness is conflated either with general alertness or with phenomenal content. This contributes to ongoing difficulties in the scientific understanding of consciousness. Previously, I have proposed that consciousness as such or nondual awareness-a basic non-conceptual, non-propositional awareness in itself free of subject-object fragmentation-is a unique kind that cannot be adequately specified by this 2D map of states and contents. Here, I propose an implicit-explicit gradient of nondual awareness to be added as the z-axis to the existing 2D map of consciousness. This gradient informs about the degree to which nondual awareness is manifest in any experience, independent of the specifics of global state or local content. Alternatively, within the multi-dimensional state space model of consciousness, nondual awareness can be specified by several vectors, each representing one of its properties. In the first part, I outline nondual awareness or consciousness as such in terms of its phenomenal description, its function and its neural correlates. In the second part, I explore the implicit-explicit gradient of nondual awareness and how including it as an additional axis clarifies certain features of everyday dualistic experiences and is especially relevant for understanding the unitary and nondual experiences accessed via different contemplative methods, mind-altering substances or spontaneously.
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Affiliation(s)
- Zoran Josipovic
- Psychology Department, Graduate School of Arts & Sciences, New York University, New York, NY 10003, USA
- Nonduality Institute, Woodstock, NY 12498, USA
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26
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Fields C, Glazebrook JF, Levin M. Minimal physicalism as a scale-free substrate for cognition and consciousness. Neurosci Conscious 2021; 2021:niab013. [PMID: 34345441 PMCID: PMC8327199 DOI: 10.1093/nc/niab013] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 04/04/2021] [Accepted: 04/05/2021] [Indexed: 12/14/2022] Open
Abstract
Theories of consciousness and cognition that assume a neural substrate automatically regard phylogenetically basal, nonneural systems as nonconscious and noncognitive. Here, we advance a scale-free characterization of consciousness and cognition that regards basal systems, including synthetic constructs, as not only informative about the structure and function of experience in more complex systems but also as offering distinct advantages for experimental manipulation. Our "minimal physicalist" approach makes no assumptions beyond those of quantum information theory, and hence is applicable from the molecular scale upwards. We show that standard concepts including integrated information, state broadcasting via small-world networks, and hierarchical Bayesian inference emerge naturally in this setting, and that common phenomena including stigmergic memory, perceptual coarse-graining, and attention switching follow directly from the thermodynamic requirements of classical computation. We show that the self-representation that lies at the heart of human autonoetic awareness can be traced as far back as, and serves the same basic functions as, the stress response in bacteria and other basal systems.
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Affiliation(s)
- Chris Fields
- 23 Rue des Lavandières, 11160 Caunes Minervois, France
| | - James F Glazebrook
- Department of Mathematics and Computer Science, Eastern Illinois University, 600 Lincoln Ave, Charleston, IL 61920 USA
- Department of Mathematics, Adjunct Faculty, University of Illinois at Urbana–Champaign, 1409 W. Green Street, Urbana, IL 61801, USA
| | - Michael Levin
- Allen Discovery Center, Tufts University, 200 College Avenue, Medford, MA 02155, USA
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27
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Safron A. The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again. ENTROPY (BASEL, SWITZERLAND) 2021; 23:783. [PMID: 34202965 PMCID: PMC8234656 DOI: 10.3390/e23060783] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 05/12/2021] [Accepted: 05/27/2021] [Indexed: 11/24/2022]
Abstract
Drawing from both enactivist and cognitivist perspectives on mind, I propose that explaining teleological phenomena may require reappraising both "Cartesian theaters" and mental homunculi in terms of embodied self-models (ESMs), understood as body maps with agentic properties, functioning as predictive-memory systems and cybernetic controllers. Quasi-homuncular ESMs are suggested to constitute a major organizing principle for neural architectures due to their initial and ongoing significance for solutions to inference problems in cognitive (and affective) development. Embodied experiences provide foundational lessons in learning curriculums in which agents explore increasingly challenging problem spaces, so answering an unresolved question in Bayesian cognitive science: what are biologically plausible mechanisms for equipping learners with sufficiently powerful inductive biases to adequately constrain inference spaces? Drawing on models from neurophysiology, psychology, and developmental robotics, I describe how embodiment provides fundamental sources of empirical priors (as reliably learnable posterior expectations). If ESMs play this kind of foundational role in cognitive development, then bidirectional linkages will be found between all sensory modalities and frontal-parietal control hierarchies, so infusing all senses with somatic-motoric properties, thereby structuring all perception by relevant affordances, so solving frame problems for embodied agents. Drawing upon the Free Energy Principle and Active Inference framework, I describe a particular mechanism for intentional action selection via consciously imagined (and explicitly represented) goal realization, where contrasts between desired and present states influence ongoing policy selection via predictive coding mechanisms and backward-chained imaginings (as self-realizing predictions). This embodied developmental legacy suggests a mechanism by which imaginings can be intentionally shaped by (internalized) partially-expressed motor acts, so providing means of agentic control for attention, working memory, imagination, and behavior. I further describe the nature(s) of mental causation and self-control, and also provide an account of readiness potentials in Libet paradigms wherein conscious intentions shape causal streams leading to enaction. Finally, I provide neurophenomenological handlings of prototypical qualia including pleasure, pain, and desire in terms of self-annihilating free energy gradients via quasi-synesthetic interoceptive active inference. In brief, this manuscript is intended to illustrate how radically embodied minds may create foundations for intelligence (as capacity for learning and inference), consciousness (as somatically-grounded self-world modeling), and will (as deployment of predictive models for enacting valued goals).
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Affiliation(s)
- Adam Safron
- Center for Psychedelic and Consciousness Research, Johns Hopkins University School of Medicine, Baltimore, MD 21218, USA;
- Kinsey Institute, Indiana University, Bloomington, IN 47405, USA
- Cognitive Science Program, Indiana University, Bloomington, IN 47405, USA
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28
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Abstract
Increased control of biological growth and form is an essential gateway to transformative medical advances. Repairing of birth defects, restoring lost or damaged organs, normalizing tumors, all depend on understanding how cells cooperate to make specific, functional large-scale structures. Despite advances in molecular genetics, significant gaps remain in our understanding of the meso-scale rules of morphogenesis. An engineering approach to this problem is the creation of novel synthetic living forms, greatly extending available model systems beyond evolved plant and animal lineages. Here, we review recent advances in the emerging field of synthetic morphogenesis, the bioengineering of novel multicellular living bodies. Emphasizing emergent self-organization, tissue-level guided self-assembly, and active functionality, this work is the essential next generation of synthetic biology. Aside from useful living machines for specific functions, the rational design and analysis of new, coherent anatomies will greatly increase our understanding of foundational questions in evolutionary developmental and cell biology.
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Affiliation(s)
- Mo R. Ebrahimkhani
- Department of Pathology, School of Medicine, University of Pittsburgh, A809B Scaife Hall, 3550 Terrace Street, Pittsburgh, PA 15261, USA
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA, USA
- McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Michael Levin
- Allen Discovery Center at Tufts University, 200 Boston Avenue, Suite 4600, Medford, MA 02155, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA
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29
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Bongard J, Levin M. Living Things Are Not (20th Century) Machines: Updating Mechanism Metaphors in Light of the Modern Science of Machine Behavior. Front Ecol Evol 2021. [DOI: 10.3389/fevo.2021.650726] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
One of the most useful metaphors for driving scientific and engineering progress has been that of the “machine.” Much controversy exists about the applicability of this concept in the life sciences. Advances in molecular biology have revealed numerous design principles that can be harnessed to understand cells from an engineering perspective, and build novel devices to rationally exploit the laws of chemistry, physics, and computation. At the same time, organicists point to the many unique features of life, especially at larger scales of organization, which have resisted decomposition analysis and artificial implementation. Here, we argue that much of this debate has focused on inessential aspects of machines – classical properties which have been surpassed by advances in modern Machine Behavior and no longer apply. This emerging multidisciplinary field, at the interface of artificial life, machine learning, and synthetic bioengineering, is highlighting the inadequacy of existing definitions. Key terms such as machine, robot, program, software, evolved, designed, etc., need to be revised in light of technological and theoretical advances that have moved past the dated philosophical conceptions that have limited our understanding of both evolved and designed systems. Moving beyond contingent aspects of historical and current machines will enable conceptual tools that embrace inevitable advances in synthetic and hybrid bioengineering and computer science, toward a framework that identifies essential distinctions between fundamental concepts of devices and living agents. Progress in both theory and practical applications requires the establishment of a novel conception of “machines as they could be,” based on the profound lessons of biology at all scales. We sketch a perspective that acknowledges the remarkable, unique aspects of life to help re-define key terms, and identify deep, essential features of concepts for a future in which sharp boundaries between evolved and designed systems will not exist.
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Abstract
Meaning has traditionally been regarded as a problem for philosophers and psychologists. Advances in cognitive science since the early 1960s, however, broadened discussions of meaning, or more technically, the semantics of perceptions, representations, and/or actions, into biology and computer science. Here, we review the notion of “meaning” as it applies to living systems, and argue that the question of how living systems create meaning unifies the biological and cognitive sciences across both organizational and temporal scales.
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