1
|
Newman SA. Form, function, mind: What doesn't compute (and what might). Biochem Biophys Res Commun 2024; 721:150141. [PMID: 38781663 DOI: 10.1016/j.bbrc.2024.150141] [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: 10/24/2023] [Revised: 03/07/2024] [Accepted: 05/17/2024] [Indexed: 05/25/2024]
Abstract
The applicability of computational and dynamical systems models to organisms is scrutinized, using examples from developmental biology and cognition. Developmental morphogenesis is dependent on the inherent material properties of developing animal (metazoan) tissues, a non-computational modality, but cell differentiation, which utilizes chromatin-based revisable memory banks and program-like function-calling, via the developmental gene co-expression system unique to the metazoans, has a quasi-computational basis. Multi-attractor dynamical models are argued to be misapplied to global properties of development, and it is suggested that along with computationalism, classic forms of dynamicism are similarly unsuitable to accounting for cognitive phenomena. Proposals are made for treating brains and other nervous tissues as novel forms of excitable matter with inherent properties which enable the intensification of cell-based basal cognition capabilities present throughout the tree of life. Finally, some connections are drawn between the viewpoint described here and active inference models of cognition, such as the Free Energy Principle.
Collapse
|
2
|
Gómez-Márquez J. The Lithbea Domain. Adv Biol (Weinh) 2024; 8:e2300679. [PMID: 38386280 DOI: 10.1002/adbi.202300679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 02/09/2024] [Indexed: 02/23/2024]
Abstract
The tree of life is the evolutionary metaphor for the past and present connections of all cellular organisms. Today, to speak of biodiversity is not only to speak of archaea, bacteria, and eukaryotes, but they should also consider the "new biodiversity" that includes viruses and synthetic organisms, which represent the new forms of life created in laboratories. There is even a third group of artificial entities that, although not living systems, pretend to imitate the living. To embrace and organize all this new biodiversity, I propose the creation of a new domain, with the name Lithbea (from life-on-the-border entites) The criteria for inclusion as members of Lithbea are: i) the acellular nature of the living system, ii) its origin in laboratory manipulation, iii) showing new biological traits, iv) the presence of exogenous genetic elements, v) artificial or inorganic nature. Within Lithbea there are two subdomains: Virworld (from virus world) which includes all viruses, regarded as lifeless living systems, and classified according to the International Committee on Taxonomy of Viruses (ICTV), and ii) Humade (from human-made) which includes all synthetic organisms and artificial entities. The relationships of Lithbea members to the three classical woesian domains and their implications are briefly discussed.
Collapse
Affiliation(s)
- Jaime Gómez-Márquez
- Department of Biochemistry and Molecular Biology, University of Santiago de Compostela, Santiago de Compostela, Galicia, 15782, Spain
| |
Collapse
|
3
|
Dong H, Hu F, Ma X, Yang J, Pan L, Xu J. Collective Cell Radial Ordered Migration in Spatial Confinement. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2307487. [PMID: 38520715 PMCID: PMC11132034 DOI: 10.1002/advs.202307487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 03/04/2024] [Indexed: 03/25/2024]
Abstract
Collective cells, a typical active matter system, exhibit complex coordinated behaviors fundamental for various developmental and physiological processes. The present work discovers a collective radial ordered migration behavior of NIH3T3 fibroblasts that depends on persistent top-down regulation with 2D spatial confinement. Remarkably, individual cells move in a weak-oriented, diffusive-like rather than strong-oriented ballistic manner. Despite this, the collective movement is spatiotemporal heterogeneous and radial ordering at supracellular scale, manifesting as a radial ordered wavefront originated from the boundary and propagated toward the center of pattern. Combining bottom-up cell-to-extracellular matrix (ECM) interaction strategy, numerical simulations based on a developed mechanical model well reproduce and explain above observations. The model further predicts the independence of geometric features on this ordering behavior, which is validated by experiments. These results together indicate such radial ordered collective migration is ascribed to the couple of top-down regulation with spatial restriction and bottom-up cellular endogenous nature.
Collapse
Affiliation(s)
- Hao Dong
- The Key Laboratory of Weak‐Light Nonlinear Photonics of Education MinistrySchool of Physics and TEDA Institute of Applied PhysicsNankai UniversityTianjin300071China
| | - Fen Hu
- The Key Laboratory of Weak‐Light Nonlinear Photonics of Education MinistrySchool of Physics and TEDA Institute of Applied PhysicsNankai UniversityTianjin300071China
| | - Xuehe Ma
- The Key Laboratory of Weak‐Light Nonlinear Photonics of Education MinistrySchool of Physics and TEDA Institute of Applied PhysicsNankai UniversityTianjin300071China
| | - Jianyu Yang
- The Key Laboratory of Weak‐Light Nonlinear Photonics of Education MinistrySchool of Physics and TEDA Institute of Applied PhysicsNankai UniversityTianjin300071China
| | - Leiting Pan
- The Key Laboratory of Weak‐Light Nonlinear Photonics of Education MinistrySchool of Physics and TEDA Institute of Applied PhysicsNankai UniversityTianjin300071China
- State Key Laboratory of Medicinal Chemical BiologyFrontiers Science Center for Cell ResponsesCollege of Life SciencesNankai UniversityTianjin300071China
- Shenzhen Research Institute of Nankai UniversityShenzhenGuangdong518083China
- Collaborative Innovation Center of Extreme OpticsShanxi UniversityTaiyuanShanxi030006China
| | - Jingjun Xu
- The Key Laboratory of Weak‐Light Nonlinear Photonics of Education MinistrySchool of Physics and TEDA Institute of Applied PhysicsNankai UniversityTianjin300071China
- Shenzhen Research Institute of Nankai UniversityShenzhenGuangdong518083China
| |
Collapse
|
4
|
Witkowski O, Schwitzgebel E. The Ethics of Life as It Could Be: Do We Have Moral Obligations to Artificial Life? ARTIFICIAL LIFE 2024; 30:193-215. [PMID: 38656414 DOI: 10.1162/artl_a_00436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
The field of Artificial Life studies the nature of the living state by modeling and synthesizing living systems. Such systems, under certain conditions, may come to deserve moral consideration similar to that given to nonhuman vertebrates or even human beings. The fact that these systems are nonhuman and evolve in a potentially radically different substrate should not be seen as an insurmountable obstacle to their potentially having rights, if they are sufficiently sophisticated in other respects. Nor should the fact that they owe their existence to us be seen as reducing their status as targets of moral concern. On the contrary, creators of Artificial Life may have special obligations to their creations, resembling those of an owner to their pet or a parent to their child. For a field that aims to create artificial life-forms with increasing levels of sophistication, it is crucial to consider the possible ethical implications of our activities, with an eye toward assessing potential moral obligations for which we should be prepared. If Artificial Life is larger than life, then the ethics of artificial beings should be larger than human ethics.
Collapse
Affiliation(s)
- Olaf Witkowski
- Cross Compass Ltd. Cross Labs University of Tokyo College of Arts and Sciences.
| | | |
Collapse
|
5
|
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).
Collapse
Affiliation(s)
- Reshma Joy
- Indian Institute of Technology Ropar, India.
| |
Collapse
|
6
|
Gumuskaya G, Srivastava P, Cooper BG, Lesser H, Semegran B, Garnier S, Levin M. Motile Living Biobots Self-Construct from Adult Human Somatic Progenitor Seed Cells. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2303575. [PMID: 38032125 PMCID: PMC10811512 DOI: 10.1002/advs.202303575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 10/31/2023] [Indexed: 12/01/2023]
Abstract
Fundamental knowledge gaps exist about the plasticity of cells from adult soma and the potential diversity of body shape and behavior in living constructs derived from genetically wild-type cells. Here anthrobots are introduced, a spheroid-shaped multicellular biological robot (biobot) platform with diameters ranging from 30 to 500 microns and cilia-powered locomotive abilities. Each Anthrobot begins as a single cell, derived from the adult human lung, and self-constructs into a multicellular motile biobot after being cultured in extra cellular matrix for 2 weeks and transferred into a minimally viscous habitat. Anthrobots exhibit diverse behaviors with motility patterns ranging from tight loops to straight lines and speeds ranging from 5-50 microns s-1 . The anatomical investigations reveal that this behavioral diversity is significantly correlated with their morphological diversity. Anthrobots can assume morphologies with fully polarized or wholly ciliated bodies and spherical or ellipsoidal shapes, each related to a distinct movement type. Anthrobots are found to be capable of traversing, and inducing rapid repair of scratches in, cultured human neural cell sheets in vitro. By controlling microenvironmental cues in bulk, novel structures, with new and unexpected behavior and biomedically-relevant capabilities, can be discovered in morphogenetic processes without direct genetic editing or manual sculpting.
Collapse
Affiliation(s)
- Gizem Gumuskaya
- Allen Discovery Center at Tufts Universityand Department of BiologyTufts UniversityMedfordMA02155USA
- Wyss Institute for Biologically Inspired EngineeringHarvard UniversityBostonMA02115USA
| | - Pranjal Srivastava
- Allen Discovery Center at Tufts Universityand Department of BiologyTufts UniversityMedfordMA02155USA
| | - Ben G. Cooper
- Allen Discovery Center at Tufts Universityand Department of BiologyTufts UniversityMedfordMA02155USA
| | - Hannah Lesser
- Allen Discovery Center at Tufts Universityand Department of BiologyTufts UniversityMedfordMA02155USA
| | - Ben Semegran
- Allen Discovery Center at Tufts Universityand Department of BiologyTufts UniversityMedfordMA02155USA
| | - Simon Garnier
- Federated Department of Biological SciencesNew Jersey Institute of TechnologyNewarkNJ07102USA
| | - Michael Levin
- Allen Discovery Center at Tufts Universityand Department of BiologyTufts UniversityMedfordMA02155USA
- Wyss Institute for Biologically Inspired EngineeringHarvard UniversityBostonMA02115USA
| |
Collapse
|
7
|
Seifert G, Sealander A, Marzen S, Levin M. From reinforcement learning to agency: Frameworks for understanding basal cognition. Biosystems 2024; 235:105107. [PMID: 38128873 DOI: 10.1016/j.biosystems.2023.105107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 12/17/2023] [Accepted: 12/17/2023] [Indexed: 12/23/2023]
Abstract
Organisms play, explore, and mimic those around them. Is there a purpose to this behavior? Are organisms just behaving, or are they trying to achieve goals? We believe this is a false dichotomy. To that end, to understand organisms, we attempt to unify two approaches for understanding complex agents, whether evolved or engineered. We argue that formalisms describing multiscale competencies and goal-directedness in biology (e.g., TAME), and reinforcement learning (RL), can be combined in a symbiotic framework. While RL has been largely focused on higher-level organisms and robots of high complexity, TAME is naturally capable of describing lower-level organisms and minimal agents as well. We propose several novel questions that come from using RL/TAME to understand biology as well as ones that come from using biology to formulate new theory in AI. We hope that the research programs proposed in this piece shape future efforts to understand biological organisms and also future efforts to build artificial agents.
Collapse
Affiliation(s)
- Gabriella Seifert
- Department of Physics, University of Colorado, Boulder, CO 80309, USA; W. M. Keck Science Department, Pitzer, Scripps, and Claremont McKenna College, Claremont, CA 91711, USA
| | - Ava Sealander
- Department of Electrical Engineering, School of Engineering and Applied Sciences, Columbia University, New York, NY 10027, USA; W. M. Keck Science Department, Pitzer, Scripps, and Claremont McKenna College, Claremont, CA 91711, USA
| | - Sarah Marzen
- W. M. Keck Science Department, Pitzer, Scripps, and Claremont McKenna College, Claremont, CA 91711, USA.
| | - Michael Levin
- Department of Biology, Tufts University, Medford, MA 02155, USA; Allen Discovery Center at Tufts University, Medford, MA 02155, USA
| |
Collapse
|
8
|
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.
Collapse
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.
| |
Collapse
|
9
|
Selvam A, Aggarwal T, Mukherjee M, Verma YK. Humans and robots: Friends of the future? A bird's eye view of biomanufacturing industry 5.0. Biotechnol Adv 2023; 68:108237. [PMID: 37604228 DOI: 10.1016/j.biotechadv.2023.108237] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 07/15/2023] [Accepted: 08/18/2023] [Indexed: 08/23/2023]
Abstract
The evolution of industries have introduced versatile technologies, motivating limitless possibilities of tackling pivotal global predicaments in the arenas of medicine, environment, defence, and national security. In this direction, ardently emerges the new era of Industry 5.0 through the eyes of biomanufacturing, which integrates the most advanced systems 21st century has to offer by means of integrating artificial systems to mimic and nativize the natural milieu to substitute the deficits of nature, thence leading to a new meta world. Albeit, it questions the natural order of the living world, which necessitates certain paramount stipulations to be addressed for a successful expansion of biomanufacturing Industry 5.0. Can humans live in synergism with artificial beings? How can humans establish dominance of hierarchy with artificial counterparts? This perspective provides a bird's eye view on the plausible direction of a new meta world inquisitively. For this purpose, we propose the influence of internet of things (IoT) via new generation interfacial systems, such as, human-machine interface (HMI) and brain-computer interface (BCI) in the domain of tissue engineering and regenerative medicine, which can be extended to target modern warfare and smart healthcare.
Collapse
Affiliation(s)
- Abhyavartin Selvam
- Amity Institute of Nanotechnology, Amity University Noida, Uttar Pradesh 201303, India
| | - Tanishka Aggarwal
- Department of Biotechnology, School of Chemical and Life Sciences (SCLS) Jamia Hamdard, New Delhi 110062, India
| | - Monalisa Mukherjee
- Amity Institute of Click Chemistry Research and Studies, Amity University Noida, Uttar Pradesh 201303, India
| | - Yogesh Kumar Verma
- Stem Cell & Tissue Engineering Research Group, Institute of Nuclear Medicine and Allied Sciences, Defence Research and Development Organisation, New Delhi 110054, India.
| |
Collapse
|
10
|
Matthews D, Spielberg A, Rus D, Kriegman S, Bongard J. Efficient automatic design of robots. Proc Natl Acad Sci U S A 2023; 120:e2305180120. [PMID: 37788314 PMCID: PMC10576117 DOI: 10.1073/pnas.2305180120] [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: 03/29/2023] [Accepted: 07/22/2023] [Indexed: 10/05/2023] Open
Abstract
Robots are notoriously difficult to design because of complex interdependencies between their physical structure, sensory and motor layouts, and behavior. Despite this, almost every detail of every robot built to date has been manually determined by a human designer after several months or years of iterative ideation, prototyping, and testing. Inspired by evolutionary design in nature, the automated design of robots using evolutionary algorithms has been attempted for two decades, but it too remains inefficient: days of supercomputing are required to design robots in simulation that, when manufactured, exhibit desired behavior. Here we show de novo optimization of a robot's structure to exhibit a desired behavior, within seconds on a single consumer-grade computer, and the manufactured robot's retention of that behavior. Unlike other gradient-based robot design methods, this algorithm does not presuppose any particular anatomical form; starting instead from a randomly-generated apodous body plan, it consistently discovers legged locomotion, the most efficient known form of terrestrial movement. If combined with automated fabrication and scaled up to more challenging tasks, this advance promises near-instantaneous design, manufacture, and deployment of unique and useful machines for medical, environmental, vehicular, and space-based tasks.
Collapse
Affiliation(s)
- David Matthews
- Center for Robotics and Biosystems, Northwestern University, Evanston, IL60208
| | - Andrew Spielberg
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA02139
| | - Daniela Rus
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA02139
| | - Sam Kriegman
- Center for Robotics and Biosystems, Northwestern University, Evanston, IL60208
| | - Josh Bongard
- Department of Computer Science, University of Vermont, Burlington, VT05405
| |
Collapse
|
11
|
Lagasse E, Levin M. Future medicine: from molecular pathways to the collective intelligence of the body. Trends Mol Med 2023; 29:687-710. [PMID: 37481382 PMCID: PMC10527237 DOI: 10.1016/j.molmed.2023.06.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 06/20/2023] [Accepted: 06/22/2023] [Indexed: 07/24/2023]
Abstract
The remarkable anatomical homeostasis exhibited by complex living organisms suggests that they are inherently reprogrammable information-processing systems that offer numerous interfaces to their physiological and anatomical problem-solving capacities. We briefly review data suggesting that the multiscale competency of living forms affords a new path for biomedicine that exploits the innate collective intelligence of tissues and organs. The concept of tissue-level allostatic goal-directedness is already bearing fruit in clinical practice. We sketch a roadmap towards 'somatic psychiatry' by using advances in bioelectricity and behavioral neuroscience to design methods that induce self-repair of structure and function. Relaxing the assumption that cellular control mechanisms are static, exploiting powerful concepts from cybernetics, behavioral science, and developmental biology may spark definitive solutions to current biomedical challenges.
Collapse
Affiliation(s)
- Eric Lagasse
- McGowan Institute for Regenerative Medicine and Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Michael Levin
- Allen Discovery Center, Tufts University, Medford, MA, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
| |
Collapse
|
12
|
Liu AT, Hempel M, Yang JF, Brooks AM, Pervan A, Koman VB, Zhang G, Kozawa D, Yang S, Goldman DI, Miskin MZ, Richa AW, Randall D, Murphey TD, Palacios T, Strano MS. Colloidal robotics. NATURE MATERIALS 2023:10.1038/s41563-023-01589-y. [PMID: 37620646 DOI: 10.1038/s41563-023-01589-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Accepted: 03/30/2023] [Indexed: 08/26/2023]
Abstract
Robots have components that work together to accomplish a task. Colloids are particles, usually less than 100 µm, that are small enough that they do not settle out of solution. Colloidal robots are particles capable of functions such as sensing, computation, communication, locomotion and energy management that are all controlled by the particle itself. Their design and synthesis is an emerging area of interdisciplinary research drawing from materials science, colloid science, self-assembly, robophysics and control theory. Many colloidal robot systems approach synthetic versions of biological cells in autonomy and may find ultimate utility in bringing these specialized functions to previously inaccessible locations. This Perspective examines the emerging literature and highlights certain design principles and strategies towards the realization of colloidal robots.
Collapse
Grants
- FA9550-15-1-0514 United States Department of Defense | United States Air Force | AFMC | Air Force Office of Scientific Research (AF Office of Scientific Research)
- FA9550-15-1-0514 United States Department of Defense | United States Air Force | AFMC | Air Force Office of Scientific Research (AF Office of Scientific Research)
- FA9550-15-1-0514 United States Department of Defense | United States Air Force | AFMC | Air Force Office of Scientific Research (AF Office of Scientific Research)
- FA9550-15-1-0514 United States Department of Defense | United States Air Force | AFMC | Air Force Office of Scientific Research (AF Office of Scientific Research)
- FA9550-15-1-0514 United States Department of Defense | United States Air Force | AFMC | Air Force Office of Scientific Research (AF Office of Scientific Research)
- FA9550-15-1-0514 United States Department of Defense | United States Air Force | AFMC | Air Force Office of Scientific Research (AF Office of Scientific Research)
- FA9550-15-1-0514 United States Department of Defense | United States Air Force | AFMC | Air Force Office of Scientific Research (AF Office of Scientific Research)
- FA9550-15-1-0514 United States Department of Defense | United States Air Force | AFMC | Air Force Office of Scientific Research (AF Office of Scientific Research)
- W911NF-19-1-0233 United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office (ARO)
- W911NF-19-1-0233 United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office (ARO)
- W911NF-19-1-0233 United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office (ARO)
- W911NF-19-1-0233 United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office (ARO)
- W911NF-19-1-0233 United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office (ARO)
- W911NF-19-1-0233 United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office (ARO)
- W911NF-19-1-0233 United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office (ARO)
- W911NF-19-1-0233 United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office (ARO)
- W911NF-19-1-0233 United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office (ARO)
- W911NF-19-1-0233 United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office (ARO)
- W911NF-19-1-0233 United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office (ARO)
- W911NF-19-1-0233 United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office (ARO)
- W911NF-19-10372 United States Department of Defense | United States Army | U.S. Army Research, Development and Engineering Command | Army Research Office (ARO)
Collapse
Affiliation(s)
- Albert Tianxiang Liu
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Marek Hempel
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jing Fan Yang
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Allan M Brooks
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ana Pervan
- Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA
| | - Volodymyr B Koman
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ge Zhang
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Daichi Kozawa
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sungyun Yang
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Daniel I Goldman
- School of Physics, Georgia Institute of Technology, Atlanta, GA, USA
| | - Marc Z Miskin
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Andréa W Richa
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, USA
| | - Dana Randall
- School of Computer Science, Georgia Institute of Technology, Atlanta, GA, USA
| | - Todd D Murphey
- Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA
| | - Tomás Palacios
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Michael S Strano
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
| |
Collapse
|
13
|
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.
Collapse
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
| |
Collapse
|
14
|
Esposito M, Baravalle L. The machine-organism relation revisited. HISTORY AND PHILOSOPHY OF THE LIFE SCIENCES 2023; 45:34. [PMID: 37439889 DOI: 10.1007/s40656-023-00587-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 06/03/2023] [Indexed: 07/14/2023]
Abstract
This article addresses some crucial assumptions that are rarely acknowledged when organisms and machines are compared. We begin by presenting a short historical reconstruction of the concept of "machine." We show that there has never been a unique and widely accepted definition of "machine" and that the extant definitions are based on specific technologies. Then we argue that, despite the concept's ambiguity, we can still defend a more robust, specific, and useful notion of machine analogy that accounts for successful strategies in connecting specific devices (or mechanisms) with particular living phenomena. For that purpose, we distinguish between what we call "generic identity" and proper "machine analogy." We suggest that "generic identity"-which, roughly stated, presumes that some sort of vague similarity might exist between organisms and machines-is a source of the confusion haunting many persistent disagreements and that, accordingly, it should be dismissed. Instead, we endorse a particular form of "machine analogy" where the relation between organic phenomena and mechanical devices is not generic but specific and grounded on the identification of shared "invariants." We propose that the machine analogy is a kind of analogy as proportion and we elucidate how this is used or might be used in scientific practices. We finally argue that while organisms are not machines in a generic sense, they might share many robust "invariants," which justify the scientists' use of machine analogies for grasping living phenomena.
Collapse
Affiliation(s)
- Maurizio Esposito
- University of Lisbon (Centro Interuniversitário de História das Ciências e da Tecnologia), 1749-016, Lisbon, Portugal.
| | - Lorenzo Baravalle
- University of Lisbon (Centro de Filosofia das Ciências da Universidade de Lisboa), 1749-016, Lisbon, Portugal
| |
Collapse
|
15
|
Friston K, Friedman DA, Constant A, Knight VB, Fields C, Parr T, Campbell JO. A Variational Synthesis of Evolutionary and Developmental Dynamics. ENTROPY (BASEL, SWITZERLAND) 2023; 25:964. [PMID: 37509911 PMCID: PMC10378262 DOI: 10.3390/e25070964] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 06/12/2023] [Accepted: 06/15/2023] [Indexed: 07/30/2023]
Abstract
This paper introduces a variational formulation of natural selection, paying special attention to the nature of 'things' and the way that different 'kinds' of 'things' are individuated from-and influence-each other. We use the Bayesian mechanics of particular partitions to understand how slow phylogenetic processes constrain-and are constrained by-fast, phenotypic processes. The main result is a formulation of adaptive fitness as a path integral of phenotypic fitness. Paths of least action, at the phenotypic and phylogenetic scales, can then be read as inference and learning processes, respectively. In this view, a phenotype actively infers the state of its econiche under a generative model, whose parameters are learned via natural (Bayesian model) selection. The ensuing variational synthesis features some unexpected aspects. Perhaps the most notable is that it is not possible to describe or model a population of conspecifics per se. Rather, it is necessary to consider populations of distinct natural kinds that influence each other. This paper is limited to a description of the mathematical apparatus and accompanying ideas. Subsequent work will use these methods for simulations and numerical analyses-and identify points of contact with related mathematical formulations of evolution.
Collapse
Affiliation(s)
- Karl Friston
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1E 6AP, UK
| | - Daniel A Friedman
- Department of Entomology and Nematology, University of California, Davis, Davis, CA 95616, USA
- Active Inference Institute, Davis, CA 95616, USA
| | - Axel Constant
- Theory and Method in Biosciences, The University of Sydney, Sydney, NSW 2006, Australia
| | - V Bleu Knight
- Active Inference Institute, Davis, CA 95616, USA
- Department of Biology, New Mexico State University, Las Cruces, NM 88003, USA
| | - Chris Fields
- Allen Discovery Center at Tufts University, Medford, MA 02155, USA
| | - Thomas Parr
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1E 6AP, UK
| | | |
Collapse
|
16
|
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".
Collapse
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
| |
Collapse
|
17
|
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.
Collapse
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.
| |
Collapse
|
18
|
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.
Collapse
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
| |
Collapse
|
19
|
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.
Collapse
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
| |
Collapse
|
20
|
Kop M. Abundance and Equality. Front Res Metr Anal 2022; 7:977684. [PMID: 36531753 PMCID: PMC9753773 DOI: 10.3389/frma.2022.977684] [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: 06/24/2022] [Accepted: 07/12/2022] [Indexed: 09/19/2023] Open
Abstract
The technology driven post-scarcity society is upon us. Ubiquitous technologies are eradicating scarcity in many industries. These macroscopic system trends are causing our economy to transition from relative scarcity to relative abundance. For many people in the world however, in both developed, developing, and underdeveloped countries, the notion of an Age of Abundance will sound utterly bizarre. There is a tension between abundance and equality. Good governance considers in what manner the state conducts public policy, manages public resources and promotes overall prosperity. This chapter connects good governance to the end of scarcity and integrates equality into abundance. The chapter critically examines the normative justifications of our scarcity based legal institutions, such as property and intellectual property (IP) systems, in light of 10 exponential, Fourth Industrial Revolution (4IR) technologies, and the post-scarcity economy. Starting point is that absolute and relative abundance are not utopian. Technology will erase scarcity in more and more economic areas in the foreseeable future, but not everywhere or for everybody. The chapter views relative scarcity and relative abundance as temporal socio-economic categories at two opposite sides of a continuum. The chapter unifies good governance with equality and abundance, by introducing a post-Rawlsian Equal Relative Abundance (ERA) principle of distributive justice. This includes defining a set of material and immaterial primary goods, warranting adequate, sufficient levels of relative abundance (which depend on technological evolution), and equitable results per region or group. Crucially, ERA integrates desert-based principles to the degree that some may deserve a higher level of material goods because of inequality in contributions, i.e., their hard work, talent, luck or entrepreneurial spirit, only to the extent that their unequal rewards do also function to improve the position of the least advantaged. A society governed by the ERA principle should in theory be able to solve the poverty trap on a global level. As lifting people from poverty in Europe is a different thing than achieving ERA in the US, applying equal relative abundance techniques in Asia and Africa each have their own specific challenges and dimensions.
Collapse
Affiliation(s)
- Mauritz Kop
- AIRecht, Amsterdam, Netherlands
- School of Law, Stanford University, Stanford, CA, United States
| |
Collapse
|
21
|
Hasanzadeh A, Hamblin MR, Kiani J, Noori H, Hardie JM, Karimi M, Shafiee H. Could artificial intelligence revolutionize the development of nanovectors for gene therapy and mRNA vaccines? NANO TODAY 2022; 47:101665. [PMID: 37034382 PMCID: PMC10081506 DOI: 10.1016/j.nantod.2022.101665] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Gene therapy enables the introduction of nucleic acids like DNA and RNA into host cells, and is expected to revolutionize the treatment of a wide range of diseases. This growth has been further accelerated by the discovery of CRISPR/Cas technology, which allows accurate genomic editing in a broad range of cells and organisms in vitro and in vivo. Despite many advances in gene delivery and the development of various viral and non-viral gene delivery vectors, the lack of highly efficient non-viral systems with low cellular toxicity remains a challenge. The application of cutting-edge technologies such as artificial intelligence (AI) has great potential to find new paradigms to solve this issue. Herein, we review AI and its major subfields including machine learning (ML), neural networks (NNs), expert systems, deep learning (DL), computer vision and robotics. We discuss the potential of AI-based models and algorithms in the design of targeted gene delivery vehicles capable of crossing extracellular and intracellular barriers by viral mimicry strategies. We finally discuss the role of AI in improving the function of CRISPR/Cas systems, developing novel nanobots, and mRNA vaccine carriers.
Collapse
Affiliation(s)
- Akbar Hasanzadeh
- Cellular and Molecular Research Center, Iran University of Medical Sciences, Tehran 1449614535, Iran
- Department of Medical Nanotechnology, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran 1449614535, Iran
| | - Michael R Hamblin
- Laser Research Centre, Faculty of Health Science, University of Johannesburg, Doornfontein 2028, South Africa
- Radiation Biology Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Jafar Kiani
- Oncopathology Research Center, Iran University of Medical Sciences, Tehran 1449614535, Iran
- Department of Molecular Medicine, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Hamid Noori
- Cellular and Molecular Research Center, Iran University of Medical Sciences, Tehran 1449614535, Iran
- Department of Medical Nanotechnology, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran 1449614535, Iran
| | - Joseph M. Hardie
- Division of Engineering in Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 02139 USA
| | - Mahdi Karimi
- Cellular and Molecular Research Center, Iran University of Medical Sciences, Tehran 1449614535, Iran
- Department of Medical Nanotechnology, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran 1449614535, Iran
- Oncopathology Research Center, Iran University of Medical Sciences, Tehran 1449614535, Iran
- Research Center for Science and Technology in Medicine, Tehran University of Medical Sciences, Tehran 141556559, Iran
- Applied Biotechnology Research Centre, Tehran Medical Science, Islamic Azad University, Tehran 1584743311, Iran
| | - Hadi Shafiee
- Division of Engineering in Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 02139 USA
| |
Collapse
|
22
|
Womack MC, Steigerwald E, Blackburn DC, Cannatella DC, Catenazzi A, Che J, Koo MS, McGuire JA, Ron SR, Spencer CL, Vredenburg VT, Tarvin RD. State of the Amphibia 2020: A Review of Five Years of Amphibian Research and Existing Resources. ICHTHYOLOGY & HERPETOLOGY 2022. [DOI: 10.1643/h2022005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Molly C. Womack
- Department of Biology, Utah State University, Logan, Utah 84322; . ORCID: 0000-0002-3346-021X
| | - Emma Steigerwald
- Museum of Vertebrate Zoology, University of California, Berkeley, Berkeley, California 94720; (ES) ; (MSK) ; (JAM) ; (CS) ; (VTV) ; and (RDT)
| | - David C. Blackburn
- Department of Natural History, Florida Museum of Natural History, University of Florida, Gainesville, Florida 32611; . ORCID: 0000-0002-1810-9886
| | - David C. Cannatella
- Department of Integrative Biology, University of Texas at Austin, Austin, Texas 78712; . ORCID: 0000-0001-8675-0520
| | | | - Jing Che
- State Key Laboratory of Genetic Resources and Evolution & Yunnan Key Laboratory of Biodiversity and Ecological Security of Gaoligong Mountain, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; . ORCID: 0000-0003-4246-6
| | - Michelle S. Koo
- Museum of Vertebrate Zoology, University of California, Berkeley, Berkeley, California 94720; (ES) ; (MSK) ; (JAM) ; (CS) ; (VTV) ; and (RDT)
| | - Jimmy A. McGuire
- Museum of Vertebrate Zoology, University of California, Berkeley, Berkeley, California 94720; (ES) ; (MSK) ; (JAM) ; (CS) ; (VTV) ; and (RDT)
| | - Santiago R. Ron
- Museo de Zoología, Escuela de Biología, Pontificia Universidad Católica del Ecuador, Quito, Ecuador; . ORCID: 0000-0001-6300-9350
| | - Carol L. Spencer
- Museum of Vertebrate Zoology, University of California, Berkeley, Berkeley, California 94720; (ES) ; (MSK) ; (JAM) ; (CS) ; (VTV) ; and (RDT)
| | - Vance T. Vredenburg
- Museum of Vertebrate Zoology, University of California, Berkeley, Berkeley, California 94720; (ES) ; (MSK) ; (JAM) ; (CS) ; (VTV) ; and (RDT)
| | - Rebecca D. Tarvin
- Museum of Vertebrate Zoology, University of California, Berkeley, Berkeley, California 94720; (ES) ; (MSK) ; (JAM) ; (CS) ; (VTV) ; and (RDT)
| |
Collapse
|
23
|
Glykofrydis F, Elfick A. Exploring standards for multicellular mammalian synthetic biology. Trends Biotechnol 2022; 40:1299-1312. [PMID: 35803769 DOI: 10.1016/j.tibtech.2022.06.001] [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: 02/01/2022] [Revised: 05/16/2022] [Accepted: 06/02/2022] [Indexed: 01/21/2023]
Abstract
Synthetic biology is moving towards bioengineering multicellular mammalian systems that are poised to advance tissue engineering, biomedicine, and the food industry. Despite progress, the field lacks a framework of standards that could greatly accelerate further development. Here, we explore the landscape of standards for multicellular mammalian synthetic biology. We discuss the limits of current technical standards and categorise unaddressed parameters into an abstraction hierarchy. We then define the concept of a 'synthetic multicellular mammalian system' and apply our standard hierarchy framework to illustrate how it could aid bioengineering endeavours. We conclude with promising areas that could shape the future of the field, flagging the need for a critical and holistic consideration of standards that requires cross-disciplinary dialogue.
Collapse
Affiliation(s)
- Fokion Glykofrydis
- Institute for Bioengineering, School of Engineering, University of Edinburgh, King's Buildings, Edinburgh, EH9 3BF, UK; UK Centre for Mammalian Synthetic Biology, University of Edinburgh, King's Buildings, Edinburgh, EH9 3BD, UK
| | - Alistair Elfick
- Institute for Bioengineering, School of Engineering, University of Edinburgh, King's Buildings, Edinburgh, EH9 3BF, UK; UK Centre for Mammalian Synthetic Biology, University of Edinburgh, King's Buildings, Edinburgh, EH9 3BD, UK.
| |
Collapse
|
24
|
Rorot W. Counting with Cilia: The Role of Morphological Computation in Basal Cognition Research. ENTROPY (BASEL, SWITZERLAND) 2022; 24:1581. [PMID: 36359671 PMCID: PMC9689127 DOI: 10.3390/e24111581] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 10/15/2022] [Accepted: 10/26/2022] [Indexed: 06/16/2023]
Abstract
"Morphological computation" is an increasingly important concept in robotics, artificial intelligence, and philosophy of the mind. It is used to understand how the body contributes to cognition and control of behavior. Its understanding in terms of "offloading" computation from the brain to the body has been criticized as misleading, and it has been suggested that the use of the concept conflates three classes of distinct processes. In fact, these criticisms implicitly hang on accepting a semantic definition of what constitutes computation. Here, I argue that an alternative, mechanistic view on computation offers a significantly different understanding of what morphological computation is. These theoretical considerations are then used to analyze the existing research program in developmental biology, which understands morphogenesis, the process of development of shape in biological systems, as a computational process. This important line of research shows that cognition and intelligence can be found across all scales of life, as the proponents of the basal cognition research program propose. Hence, clarifying the connection between morphological computation and morphogenesis allows for strengthening the role of the former concept in this emerging research field.
Collapse
Affiliation(s)
- Wiktor Rorot
- Human Interactivity and Language Lab, Faculty of Psychology, University of Warsaw, 00-927 Warszawa, Poland
| |
Collapse
|
25
|
Newman SA. Inherency and agency in the origin and evolution of biological functions. Biol J Linn Soc Lond 2022. [DOI: 10.1093/biolinnean/blac109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Abstract
Although discussed by 20th century philosophers in terms drawn from the sciences of non-living systems, in recent decades biological function has been considered in relationship to organismal capability and purpose. Bringing two phenomena generally neglected in evolutionary theory (i.e. inherency and agency) to bear on questions of function leads to a rejection of the adaptationist ‘selected effects’ notion of biological function. I review work showing that organisms such as the placozoans can thrive with almost no functional embellishments beyond those of their constituent cells and physical properties of their simple tissues. I also discuss work showing that individual tissue cells and their artificial aggregates exhibit agential behaviours that are unprecedented in the histories of their respective lineages. I review findings on the unique metazoan mechanism of developmental gene expression that has recruited, during evolution, inherent ancestral cellular functionalities into specialized cell types and organs of the different animal groups. I conclude that most essential functions in animal species are inherent to the cells from which they evolved, not selected effects, and that many of the others are optional ‘add-ons’, a status inimical to fitness-based models of evolution positing that traits emerge from stringent cycles of selection to meet external challenges.
Collapse
Affiliation(s)
- Stuart A Newman
- Department of Cell Biology & Anatomy, New York Medical College , Valhalla, NY 10595 , USA
| |
Collapse
|
26
|
The Central Dogma of Information. INFORMATION 2022. [DOI: 10.3390/info13080365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
Info-autopoiesis or the self-referenced, recursive, interactive process of information self-production that engages all living beings in their efforts to satisfy their physiological and/or relational needs relies on Bateson’s difference which makes a difference. Living beings, as active manipulators/observers of their environment, derive meaning from the sensorially detected motion of matter and/or energy in the Universe. The process of info-autopoiesis in humans is found to be triadic in nature and incorporates the simultaneity of a quantitative/objective perspective with a qualitative/subjective perspective. In this process of meaningful engagement with the environment, humans create and transform endogenous semantic information into countless expressions of exogeneous syntactic information, which is synonymous with ordered material structure and artificial creation. Other humans can interpret exogeneous syntactic information and uniquely transform it into semantic information that can take multifarious forms. This asymmetrical process is the basis to postulate the central dogma of information that states ‘info-autopoiesis results in endogenous semantic information that irreversibly becomes exogeneous syntactic information’. In other words, once the artificial, syntactic world, including machines, created by humans comes into being it can only be interpreted by others, i.e., it does not necessarily convey the same intended meaning to all. Additionally, these artificial creations only recognize, extract, create, transmit, preserve, store, and utilize syntactic information, unable to transform syntactic information into semantic information. In other words, our resourceful capacity for syntactic creation does not allow for creation of artificial beings with comparable capabilities as us for meaning making. It suggests that our dreams for sentient artificial general intelligence and superintelligence are misguided and parallel the central dogma of molecular biology which states that ‘once (sequential) information has passed into protein it cannot get out again’.
Collapse
|
27
|
Gautam RD, Devarakonda B. Towards a bioinformational understanding of AI. AI & SOCIETY 2022. [DOI: 10.1007/s00146-022-01529-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
|
28
|
Clawson WP, Levin M. Endless forms most beautiful 2.0: teleonomy and the bioengineering of chimaeric and synthetic organisms. Biol J Linn Soc Lond 2022. [DOI: 10.1093/biolinnean/blac073] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Abstract
The rich variety of biological forms and behaviours results from one evolutionary history on Earth, via frozen accidents and selection in specific environments. This ubiquitous baggage in natural, familiar model species obscures the plasticity and swarm intelligence of cellular collectives. Significant gaps exist in our understanding of the origin of anatomical novelty, of the relationship between genome and form, and of strategies for control of large-scale structure and function in regenerative medicine and bioengineering. Analysis of living forms that have never existed before is necessary to reveal deep design principles of life as it can be. We briefly review existing examples of chimaeras, cyborgs, hybrots and other beings along the spectrum containing evolved and designed systems. To drive experimental progress in multicellular synthetic morphology, we propose teleonomic (goal-seeking, problem-solving) behaviour in diverse problem spaces as a powerful invariant across possible beings regardless of composition or origin. Cybernetic perspectives on chimaeric morphogenesis erase artificial distinctions established by past limitations of technology and imagination. We suggest that a multi-scale competency architecture facilitates evolution of robust problem-solving, living machines. Creation and analysis of novel living forms will be an essential testbed for the emerging field of diverse intelligence, with numerous implications across regenerative medicine, robotics and ethics.
Collapse
Affiliation(s)
| | - Michael Levin
- Allen Discovery Center at Tufts University , Medford, MA , USA
- Wyss Institute for Biologically Inspired Engineering at Harvard University , Boston, MA , USA
| |
Collapse
|
29
|
Gupta A, Soni S, Chauhan N, Khanuja M, Jain U. Nanobots-based advancement in targeted drug delivery and imaging: An update. J Control Release 2022; 349:97-108. [PMID: 35718213 DOI: 10.1016/j.jconrel.2022.06.020] [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: 03/21/2022] [Revised: 06/11/2022] [Accepted: 06/12/2022] [Indexed: 10/17/2022]
Abstract
Manipulation and targeted navigation of nanobots in complex biological conditions can be achieved by chemical reactions, by applying external forces, and via motile cells. Several studies have applied fuel-based and fuel-free propulsion mechanisms for nanobots movements in environmental sciences and robotics. However, their applications in biomedical sciences are still in the budding phase. Therefore, the current review introduces the fundamentals of different propulsion strategies based on the advantageous features of applied nanomaterials or cellular components. Furthermore, the recent developments reported in various literatures on next-generation nanobots, such as Xenobots with applications of in-vitro and in-vivo drug delivery and imaging were also explored in detail. The challenges and the future prospects are also highlighted with corresponding advantages and limitations of nanobots in biomedical applications. This review concludes that with ever booming research enthusiasm in this field and increasing multidisciplinary cooperation, micro-/nanorobots with intelligence and multifunctions will emerge in the near future, which would have a profound impact on the treatment of diseases.
Collapse
Affiliation(s)
- Abhinandan Gupta
- Amity Institute of Nanotechnology (AINT), Amity University Uttar Pradesh (AUUP), Sector-125, Noida 201313, India
| | - Shringika Soni
- Amity Institute of Nanotechnology (AINT), Amity University Uttar Pradesh (AUUP), Sector-125, Noida 201313, India
| | - Nidhi Chauhan
- Amity Institute of Nanotechnology (AINT), Amity University Uttar Pradesh (AUUP), Sector-125, Noida 201313, India
| | - Manika Khanuja
- Centre for Nanoscience & Nanotechnology, Jamia Millia Islamia (A Central University), New Delhi 110025, India
| | - Utkarsh Jain
- Amity Institute of Nanotechnology (AINT), Amity University Uttar Pradesh (AUUP), Sector-125, Noida 201313, India.
| |
Collapse
|
30
|
Fields C, Levin M. Competency in Navigating Arbitrary Spaces as an Invariant for Analyzing Cognition in Diverse Embodiments. ENTROPY 2022; 24:e24060819. [PMID: 35741540 PMCID: PMC9222757 DOI: 10.3390/e24060819] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 05/26/2022] [Accepted: 06/08/2022] [Indexed: 12/20/2022]
Abstract
One of the most salient features of life is its capacity to handle novelty and namely to thrive and adapt to new circumstances and changes in both the environment and internal components. An understanding of this capacity is central to several fields: the evolution of form and function, the design of effective strategies for biomedicine, and the creation of novel life forms via chimeric and bioengineering technologies. Here, we review instructive examples of living organisms solving diverse problems and propose competent navigation in arbitrary spaces as an invariant for thinking about the scaling of cognition during evolution. We argue that our innate capacity to recognize agency and intelligence in unfamiliar guises lags far behind our ability to detect it in familiar behavioral contexts. The multi-scale competency of life is essential to adaptive function, potentiating evolution and providing strategies for top-down control (not micromanagement) to address complex disease and injury. We propose an observer-focused viewpoint that is agnostic about scale and implementation, illustrating how evolution pivoted similar strategies to explore and exploit metabolic, transcriptional, morphological, and finally 3D motion spaces. By generalizing the concept of behavior, we gain novel perspectives on evolution, strategies for system-level biomedical interventions, and the construction of bioengineered intelligences. This framework is a first step toward relating to intelligence in highly unfamiliar embodiments, which will be essential for progress in artificial intelligence and regenerative medicine and for thriving in a world increasingly populated by synthetic, bio-robotic, and hybrid beings.
Collapse
Affiliation(s)
- Chris Fields
- Allen Discovery Center at Tufts University, Science and Engineering Complex, 200 College Ave., Medford, MA 02155, USA;
| | - Michael Levin
- Allen Discovery Center at Tufts University, Science and Engineering Complex, 200 College Ave., Medford, MA 02155, USA;
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA 02115, USA
- Correspondence:
| |
Collapse
|
31
|
Chowdhury F, Huang B, Wang N. Forces in stem cells and cancer stem cells. Cells Dev 2022; 170:203776. [DOI: 10.1016/j.cdev.2022.203776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 02/26/2022] [Accepted: 03/22/2022] [Indexed: 10/18/2022]
|
32
|
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.
Collapse
|
33
|
Spector L. Editorial introduction. GENETIC PROGRAMMING AND EVOLVABLE MACHINES 2022; 23:1-2. [PMID: 35250372 PMCID: PMC8886196 DOI: 10.1007/s10710-022-09428-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 02/15/2022] [Accepted: 02/16/2022] [Indexed: 06/14/2023]
Affiliation(s)
- Lee Spector
- Department of Computer Science, Amherst College, Amherst, MA 01002 USA
| |
Collapse
|
34
|
Mertz L. New Biomed-Tech Advances Poised to Change the Future. IEEE Pulse 2022; 13:2-7. [PMID: 35213300 DOI: 10.1109/mpuls.2022.3145605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Biomedical and health technology is progressing at breakneck speed. From specialty pharmacies to general discount shops, store shelves are packed with a vast assortment of wearable medical devices that measure glucose levels, heart rate, and other health metrics; and over-the-counter test kits are helping to check for a wide array of infections. At the same time, electronic health records and other data-sharing platforms have smoothed the mass shift from in-person to virtual office visits over the past two years, and new imaging technologies are allowing earlier disease detection so treatments can begin sooner when they are more effective.
Collapse
|
35
|
Levin M, Djamgoz MB. Bioelectricity: From Endogenous Mechanisms to Opportunities in Synthetic Bioengineering. Bioelectricity 2022. [DOI: 10.1089/bioe.2022.0003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- Michael Levin
- Department of Biology, Allen Discovery Center, Tufts University, Medford, Massachusetts, USA
| | | |
Collapse
|
36
|
Minimal Developmental Computation: A Causal Network Approach to Understand Morphogenetic Pattern Formation. ENTROPY 2022; 24:e24010107. [PMID: 35052133 PMCID: PMC8774453 DOI: 10.3390/e24010107] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 01/05/2022] [Accepted: 01/07/2022] [Indexed: 12/22/2022]
Abstract
What information-processing strategies and general principles are sufficient to enable self-organized morphogenesis in embryogenesis and regeneration? We designed and analyzed a minimal model of self-scaling axial patterning consisting of a cellular network that develops activity patterns within implicitly set bounds. The properties of the cells are determined by internal ‘genetic’ networks with an architecture shared across all cells. We used machine-learning to identify models that enable this virtual mini-embryo to pattern a typical axial gradient while simultaneously sensing the set boundaries within which to develop it from homogeneous conditions—a setting that captures the essence of early embryogenesis. Interestingly, the model revealed several features (such as planar polarity and regenerative re-scaling capacity) for which it was not directly selected, showing how these common biological design principles can emerge as a consequence of simple patterning modes. A novel “causal network” analysis of the best model furthermore revealed that the originally symmetric model dynamically integrates into intercellular causal networks characterized by broken-symmetry, long-range influence and modularity, offering an interpretable macroscale-circuit-based explanation for phenotypic patterning. This work shows how computation could occur in biological development and how machine learning approaches can generate hypotheses and deepen our understanding of how featureless tissues might develop sophisticated patterns—an essential step towards predictive control of morphogenesis in regenerative medicine or synthetic bioengineering contexts. The tools developed here also have the potential to benefit machine learning via new forms of backpropagation and by leveraging the novel distributed self-representation mechanisms to improve robustness and generalization.
Collapse
|
37
|
Mertz L. AI-Designed, Living Robots Can Self-Replicate. IEEE Pulse 2022; 13:8-12. [DOI: 10.1109/mpuls.2022.3145151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
|