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] [MESH Headings] [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
|
Yuan B, Zhang J, Lyu A, Wu J, Wang Z, Yang M, Liu K, Mou M, Cui P. Emergence and Causality in Complex Systems: A Survey of Causal Emergence and Related Quantitative Studies. ENTROPY (BASEL, SWITZERLAND) 2024; 26:108. [PMID: 38392363 PMCID: PMC10887681 DOI: 10.3390/e26020108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 01/16/2024] [Accepted: 01/18/2024] [Indexed: 02/24/2024]
Abstract
Emergence and causality are two fundamental concepts for understanding complex systems. They are interconnected. On one hand, emergence refers to the phenomenon where macroscopic properties cannot be solely attributed to the cause of individual properties. On the other hand, causality can exhibit emergence, meaning that new causal laws may arise as we increase the level of abstraction. Causal emergence (CE) theory aims to bridge these two concepts and even employs measures of causality to quantify emergence. This paper provides a comprehensive review of recent advancements in quantitative theories and applications of CE. It focuses on two primary challenges: quantifying CE and identifying it from data. The latter task requires the integration of machine learning and neural network techniques, establishing a significant link between causal emergence and machine learning. We highlight two problem categories: CE with machine learning and CE for machine learning, both of which emphasize the crucial role of effective information (EI) as a measure of causal emergence. The final section of this review explores potential applications and provides insights into future perspectives.
Collapse
Affiliation(s)
- Bing Yuan
- Swarma Research, Beijing 100085, China
| | - Jiang Zhang
- Swarma Research, Beijing 100085, China
- School of Systems Sciences, Beijing Normal University, Beijing 100875, China
| | - Aobo Lyu
- Department of Electrical and Systems Engineering, Washington University, St. Louis, MO 63130, USA
| | - Jiayun Wu
- Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
| | - Zhipeng Wang
- School of Systems Sciences, Beijing Normal University, Beijing 100875, China
| | - Mingzhe Yang
- School of Systems Sciences, Beijing Normal University, Beijing 100875, China
| | - Kaiwei Liu
- School of Systems Sciences, Beijing Normal University, Beijing 100875, China
| | - Muyun Mou
- School of Systems Sciences, Beijing Normal University, Beijing 100875, China
| | - Peng Cui
- Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
| |
Collapse
|
3
|
Wong ML, Prabhu A. Cells as the first data scientists. J R Soc Interface 2023; 20:20220810. [PMID: 36751931 PMCID: PMC9905997 DOI: 10.1098/rsif.2022.0810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 01/17/2023] [Indexed: 02/09/2023] Open
Abstract
The concepts that we generally associate with the field of data science are strikingly descriptive of the way that life, in general, processes information about its environment. The 'information life cycle', which enumerates the stages of information treatment in data science endeavours, also captures the steps of data collection and handling in biological systems. Similarly, the 'data-information-knowledge ecosystem', developed to illuminate the role of informatics in translating raw data into knowledge, can be a framework for understanding how information is constantly being transferred between life and the environment. By placing the principles of data science in a broader biological context, we see the activities of data scientists as the latest development in life's ongoing journey to better understand and predict its environment. Finally, we propose that informatics frameworks can be used to understand the similarities and differences between abiotic complex evolving systems and life.
Collapse
Affiliation(s)
- Michael L. Wong
- Earth and Planets Laboratory, Carnegie Institution for Science, Washington, DC 20015, USA
- NHFP Sagan Fellow, NASA Hubble Fellowship Program, Space Telescope Science Institute, Baltimore, MD 21218, USA
| | - Anirudh Prabhu
- Earth and Planets Laboratory, Carnegie Institution for Science, Washington, DC 20015, USA
| |
Collapse
|
4
|
Assis JEDE, Souza JRBDE, Fitzhugh K, Christoffersen ML. A new species of Euclymene (Maldanidae, Annelida) from Brazil, with new combinations, and phylogenetic implications for Euclymeninae. AN ACAD BRAS CIENC 2022; 94:e20210283. [PMID: 36541974 DOI: 10.1590/0001-3765202220210283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 06/27/2021] [Indexed: 12/23/2022] Open
Abstract
Maldanids are tube-building polychaetes, known as bamboo-worms; inhabit diverse marine regions throughout the world. The subfamily Euclymeninae was proposed to include forms with anal and cephalic plates, a funnel-shaped pygidium, and a terminal anus. Euclymene, the type genus of Euclymeninae, has about 18 valid species. Euclymene vidali sp. nov. is defined and members of the species described from Northeastern Brazil. Members of this species have 23 chaetigers, and one pre-pygidial achaetous segment; nuchal grooves extend through three quarters of the cephalic plate, and there is one acicular spine with a denticulate tip. Euclymene africana, and E. watsoni, are here recognized, respectively, as Isocirrus africana comb. nov., and I. watsoni comb. nov. Three monotypic genera are invalid: Macroclymenella, Eupraxillella, and Pseudoclyemene; their species should be recognized as Clymenella stewartensis com. nov., Praxillella antarctica com. nov., and Praxillela quadrilobata com. nov., respectively. An identification key and a comparative table for all species of Euclymene are provided. A comparative table for all genera of Euclymeninae is also furnished. The paraphyletic status of Euclymene and Euclymeninae is discussed. The taxon Maldanoplaca is not code compliant and should only be regarded as an informal name.
Collapse
Affiliation(s)
- José Eriberto DE Assis
- Prefeitura Municipal de Bayeux, Departamento de Educação Básica, Rua Santa Tereza, 600, 58306-070 Bayeux, PB, Brazil
| | - José Roberto Botelho DE Souza
- Universidade Federal de Pernambuco, Centro de Biociências, Departamento de Zoologia, Av. Prof. Morais Rego, 1235, 50670-901 Recife, PE, Brazil
| | - Kirk Fitzhugh
- Natural History Museum of Los Angeles County, 900 Exposition Blvd, 90007 Los Angeles, California, USA
| | - Martin Lindsey Christoffersen
- Universidade Federal da Paraíba, Centro de Ciências Exatas e da Natureza, Departamento de Sistemática e Ecologia, Cidade Universitária, 58059-900 João Pessoa, PB, Brazil
| |
Collapse
|
5
|
Döbereiner HG. On the Nature of Information: How FAIR Digital Objects are Building-up Semantic Space. RESEARCH IDEAS AND OUTCOMES 2022. [DOI: 10.3897/rio.8.e95119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
In this paper, we are concerned about the nature of information and how to gather and compose data with the help of so called FAIR digital objects (FDOs) in order to transform them to knowledge. FDOs are digital surrogates of real objects. The nature of information is intrinsically linked to the kind of questions one is asking. One might not ask a question or get philosophical about it. Answers depend on the data different disciplines gather about their objects of study. In Statistical Physics, classical Shannon entropy measures system order which in equilibrium just equals the heat exchanged with the environment. In cell biology, each protein carries certain functions which create specific information. Cognitive science describes how organisms perceive their environment via functional sensors and control behavior accordingly. Note that one can have function and control without meaning. In contrast, psychology is concerned with the assessment of our perceptions by assigning meaning and ensuing actions. Finally, philosophy builds logical constructs and formulates principles, in effect transforming facts into complex knowledge. All these statements make sense, but there is an even more concise way. Indeed, Luciano Floridi provides a precise and thorough classification of information in his central oeuvre On the Philosophy of Information (Floridi 2013). Especially, he performs a sequential construction to develop the attributes which data need to have in order to count as knowledge. Semantic information is necessarily well-formed, meaningful and truthful. Well-formed data becomes meaningful by action based-semantics of an autonomous-agent solving the symbol grounding problem (Taddeo and Floridi 2005) interacting with the environment. Knowledge is created then by being informed through relevant data accounted for. We notice that the notion of agency is crucial for defining meaning. The apparent gap between Sciences and Humanities (Bawden and Robinson 2020) is created by the very existence of meaning. Further, meaning depends on interactions & connotations which are commensurate with the effective complexity of the environment of a particular agent resulting in an array of possible definitions.
In his classical paper More is different (Anderson 1972) discussed verbatim the hierarchical nature of science. Each level is made of and obeys the laws of its constituents from one level below with the higher-level exhibiting emergent properties like wetness of water assignable only to the whole system. As we rise through the hierarchies, there is a branch of science for each level of complexity; on each complexity level there are objects for which it is appropriate and fitting to build up vocabulary for the respective levels of description leading to formation of disciplinary languages. It is the central idea of causal emergence that on each level there is an optimal degree of coarse graining to define those objects in such a way that causality becomes maximal between them. This means there is emergence of informative higher scales in complex materials extending to biological systems and into the brain with its neural networks representing our thoughts in a hierarchy of neural correlates. A computational toolkit for optimal level prediction and control has been developed (Hoel and Levin 2020) which was conceptually extended to integrated information theory of consciousness (Albantakis et al. 2019). The large gap between sciences and humanities discussed above exhibits itself in a series of small gaps connected to the emergence of informative higher scales. It has been suggested that the origin of life may be identified as a transition in causal structure and information flow (Walker 2014). Integrated information measures globally how much the causal mechanisms of a system reduce the uncertainty about the possible causes for a given state. A measure of “information flow” that accurately captures causal effects has been proposed (Ay and Polani 2008). The state of the art is presented in (Ay et al. 2022) where the link between information and complexity is discussed. Ay et al single out hierarchical systems and interlevel causation. Even further, (Rosas et al. 2020) reconcile conflicting views of emergence via an exact information-theoretic approach to identify causal emergence in multivariate data. As information becomes differentially richer one eventually needs complexity measures beyond {Rn}. One may define generalized metrices on these spaces (Pirró 2009) measuring information complexity on ever higher hierarchical levels of information. As one rises through hierarchies, information on higher scale is usually gained by coarse graining to arrive at an effective, nevertheless exact description, on the higher scale. It is repeated coarse graining of syntactically well-ordered information layers which eventually leads to semantic information in a process which I conjecture to be reminiscent of renormalization group flow leading to a universal classification scheme. Thus, we identify scientific disciplines and their corresponding data sets as dual universality classes of physical and epistemic structure formation, respectively. Above the semantic gap, we may call this process quantification of the qualitative by semantic metrics. Indeed, (Kolchinsky and Wolpert 2018) explored for the first time quantitative semantic concepts in Physics in their 2018 seminal paper entitled Semantic information, autonomous agency and non-equilibrium statistical physics. Their measures are numeric variants of entropy. Semantic information is identified with ‘the information that a physical system has about its environment that is causally necessary for the system to maintain its own existence over time’.
FDOs are employed in these processes in two fundamental ways. For practical implementations of FDO technology, see accompanying abstract (Wittenburg et al. 2022). First, the FAIR principles (Wilkinson et al. 2016) ensure that unconnected pieces of data may be percolated into an integrated data space. Percolation creates the information density needed to feed AI-driven built up of semantic space. Without FDOs we wouldn't have the gravity for this to occur. Second, the very structure of FDOs, capable of symmetry preserving or breaking fusion events into composed entities, makes them homologous to mathematical categories. This will proof to be a powerful tool to unravel the nature of information via analyzing its topological structure algebraically, especially when considering our conjecture concerning universality, classes of information and their possible instantiations on vastly different length and time scales, in effect explaining analogous structure formation.
Collapse
|
6
|
Bartlett S, Louapre D. Provenance of life: Chemical autonomous agents surviving through associative learning. Phys Rev E 2022; 106:034401. [PMID: 36266823 DOI: 10.1103/physreve.106.034401] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 06/21/2022] [Indexed: 06/16/2023]
Abstract
We present a benchmark study of autonomous, chemical agents exhibiting associative learning of an environmental feature. Associative learning systems have been widely studied in cognitive science and artificial intelligence but are most commonly implemented in highly complex or carefully engineered systems, such as animal brains, artificial neural networks, DNA computing systems, and gene regulatory networks, among others. The ability to encode environmental information and use it to make simple predictions is a benchmark of biological resilience and underpins a plethora of adaptive responses in the living hierarchy, spanning prey animal species anticipating the arrival of predators to epigenetic systems in microorganisms learning environmental correlations. Given the ubiquitous and essential presence of learning behaviors in the biosphere, we aimed to explore whether simple, nonliving dissipative structures could also exhibit associative learning. Inspired by previous modeling of associative learning in chemical networks, we simulated simple systems composed of long- and short-term memory chemical species that could encode the presence or absence of temporal correlations between two external species. The ability to learn this association was implemented in Gray-Scott reaction-diffusion spots, emergent chemical patterns that exhibit self-replication and homeostasis. With the novel ability of associative learning, we demonstrate that simple chemical patterns can exhibit a broad repertoire of lifelike behavior, paving the way for in vitro studies of autonomous chemical learning systems, with potential relevance to artificial life, origins of life, and systems chemistry. The experimental realization of these learning behaviors in protocell or coacervate systems could advance a new research direction in astrobiology, since our system significantly reduces the lower bound on the required complexity for autonomous chemical learning.
Collapse
Affiliation(s)
- Stuart Bartlett
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California 91125, USA and Earth-Life Science Institute, Tokyo Institute of Technology, Tokyo 152-8550, Japan
| | - David Louapre
- Ubisoft Entertainment, 94160 Saint-Mandé, France and Science Étonnante, 75014 Paris, France†
| |
Collapse
|
7
|
Cronin L, Kitson PJ. Selection of assembly complexity in a space of tetrapeptides. Chem 2022. [DOI: 10.1016/j.chempr.2022.06.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
|
8
|
Finding or Creating a Living Organism? Past and Future Thought Experiments in Astrobiology Applied to Artificial Intelligence. Acta Biotheor 2022; 70:13. [PMID: 35482102 DOI: 10.1007/s10441-022-09438-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Revised: 04/15/2022] [Accepted: 04/21/2022] [Indexed: 11/01/2022]
Abstract
This is a digest of how various researchers in biology and astrobiology have explored questions of what defines living organisms-definitions based on functions or structures observed in organisms, or on systems terms, or on mathematical conceptions like closure, chirality, quantum mechanics and thermodynamics, or on biosemiotics, or on Darwinian evolution-to clarify the field and make it easier for endeavors in artificial intelligence to make progress. Current ideas are described to promote work between astrobiologists and computer scientists, each concerned with living organisms. A four-parameter framework is presented as a scaffold that is later developed into what machines lack to be considered alive: systems, evolution, energy and consciousness, and includes Jagers operators and the idea of dual closure. A novel definition of consciousness is developed which describes mental objects both with and without communicable properties, and this helps to clarify how consciousness in machines may be studied as an emergent process related to choice functions in systems. A perspective on how quantization, acting on nucleic acids, sets up natural limits to system behavior is offered as a partial address to the problem of biogenesis.
Collapse
|
9
|
A Mutation Threshold for Cooperative Takeover. Life (Basel) 2022; 12:life12020254. [PMID: 35207541 PMCID: PMC8874834 DOI: 10.3390/life12020254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 01/27/2022] [Accepted: 01/29/2022] [Indexed: 11/17/2022] Open
Abstract
One of the leading theories for the origin of life includes the hypothesis according to which life would have evolved as cooperative networks of molecules. Explaining cooperation—and particularly, its emergence in favoring the evolution of life-bearing molecules—is thus a key element in describing the transition from nonlife to life. Using agent-based modeling of the iterated prisoner’s dilemma, we investigate the emergence of cooperative behavior in a stochastic and spatially extended setting and characterize the effects of inheritance and variability. We demonstrate that there is a mutation threshold above which cooperation is—counterintuitively—selected, which drives a dramatic and robust cooperative takeover of the whole system sustained consistently up to the error catastrophe, in a manner reminiscent of typical phase transition phenomena in statistical physics. Moreover, our results also imply that one of the simplest conditional cooperative strategies, “Tit-for-Tat”, plays a key role in the emergence of cooperative behavior required for the origin of life.
Collapse
|
10
|
Manicka S, Levin M. Minimal Developmental Computation: A Causal Network Approach to Understand Morphogenetic Pattern Formation. ENTROPY (BASEL, SWITZERLAND) 2022; 24:107. [PMID: 35052133 PMCID: PMC8774453 DOI: 10.3390/e24010107] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [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
Affiliation(s)
| | - Michael Levin
- Allen Discovery Center, Tufts University, Medford, MA 02155, USA;
| |
Collapse
|
11
|
Gershenson C. Intelligence as Information Processing: Brains, Swarms, and Computers. Front Ecol Evol 2021. [DOI: 10.3389/fevo.2021.755981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
There is no agreed definition of intelligence, so it is problematic to simply ask whether brains, swarms, computers, or other systems are intelligent or not. To compare the potential intelligence exhibited by different cognitive systems, I use the common approach used by artificial intelligence and artificial life: Instead of studying the substrate of systems, let us focus on their organization. This organization can be measured with information. Thus, I apply an informationist epistemology to describe cognitive systems, including brains and computers. This allows me to frame the usefulness and limitations of the brain-computer analogy in different contexts. I also use this perspective to discuss the evolution and ecology of intelligence.
Collapse
|
12
|
Mortimer K, Fitzhugh K, dos Brasil AC, Lana P. Who's who in Magelona: phylogenetic hypotheses under Magelonidae Cunningham & Ramage, 1888 (Annelida: Polychaeta). PeerJ 2021; 9:e11993. [PMID: 35070516 PMCID: PMC8759375 DOI: 10.7717/peerj.11993] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 07/27/2021] [Indexed: 11/21/2022] Open
Abstract
Known as shovel head worms, members of Magelonidae comprise a group of polychaetes readily recognised by the uniquely shaped, dorso-ventrally flattened prostomium and paired ventro-laterally inserted papillated palps. The present study is the first published account of inferences of phylogenetic hypotheses within Magelonidae. Members of 72 species of Magelona and two species of Octomagelona were included, with outgroups including members of one species of Chaetopteridae and four of Spionidae. The phylogenetic inferences were performed to causally account for 176 characters distributed among 79 subjects, and produced 2,417,600 cladograms, each with 404 steps. A formal definition of Magelonidae is provided, represented by a composite phylogenetic hypothesis explaining seven synapomorphies: shovel-shaped prostomium, prostomial ridges, absence of nuchal organs, ventral insertion of palps and their papillation, presence of a burrowing organ, and unique body regionation. Octomagelona is synonymised with Magelona due to the latter being paraphyletic relative to the former. The consequence is that Magelonidae is monotypic, such that Magelona cannot be formally defined as associated with any phylogenetic hypotheses. As such, the latter name is an empirically empty placeholder, but because of the binomial name requirement mandated by the International Code of Zoological Nomenclature, the definition is identical to that of Magelonidae. Several key features for future descriptions are suggested: prostomial dimensions, presence/absence of prostomial horns, morphology of anterior lamellae, presence/absence of specialised chaetae, and lateral abdominal pouches. Additionally, great care must be taken to fully describe and illustrate all thoracic chaetigers in descriptions.
Collapse
Affiliation(s)
- Kate Mortimer
- Natural Sciences, Amgueddfa Cymru–National Museum Wales, Cardiff, Wales, United Kingdom
| | - Kirk Fitzhugh
- Natural History Museum of Los Angeles County, Los Angeles, CA, United States of America
| | - Ana Claudia dos Brasil
- Departamento de Biologia Animal, Instituto de Ciências Biológicas e da Saúde, Universidade Federal Rural do Rio de Janeiro, Seropédica, Rio de Janeiro, Brazil
| | - Paulo Lana
- Centro de Estudos do Mar, Universidade Federal do Paraná, Pontal do Sul, Paraná, Brazil
| |
Collapse
|
13
|
Neidhöfer C. On the Evolution of the Biological Framework for Insight. PHILOSOPHIES 2021; 6:43. [DOI: 10.3390/philosophies6020043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/05/2023]
Abstract
The details of abiogenesis, to date, remain a matter of debate and constitute a key mystery in science and philosophy. The prevailing scientific hypothesis implies an evolutionary process of increasing complexity on Earth starting from (self-) replicating polymers. Defining the cut-off point where life begins is another moot point beyond the scope of this article. We will instead walk through the known evolutionary steps that led from these first exceptional polymers to the vast network of living biomatter that spans our world today, focusing in particular on perception, from simple biological feedback mechanisms to the complexity that allows for abstract thought. We will then project from the well-known to the unknown to gain a glimpse into what the universe aims to accomplish with living matter, just to find that if the universe had ever planned to be comprehended, evolution still has a long way to go.
Collapse
|
14
|
Gordon R. Are we on the cusp of a new paradigm for biology? The illogic of molecular developmental biology versus Janus-faced control of embryogenesis via differentiation waves. Biosystems 2021; 203:104367. [PMID: 33515641 DOI: 10.1016/j.biosystems.2021.104367] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 01/15/2021] [Accepted: 01/15/2021] [Indexed: 01/19/2023]
Abstract
The logic of molecular developmental biology fails to explain embryogenesis. A new approach, Janus-faced control, involving both top-down control by differentiation waves and bottom-up control via the mechanical consequences of cell differentiations, may be needed. This obviates problems inherent in reductionism with an explicit, testable mechanism.
Collapse
Affiliation(s)
- Richard Gordon
- Gulf Specimen Marine Laboratory & Aquarium, 222 Clark Drive, Panacea, FL, 32346, USA; C.S. Mott Center for Human Growth & Development, Department of Obstetrics & Gynecology, Wayne State University, 275 E. Hancock, Detroit, MI, 48201, USA.
| |
Collapse
|
15
|
Farnsworth KD. An organisational systems-biology view of viruses explains why they are not alive. Biosystems 2020; 200:104324. [PMID: 33307144 DOI: 10.1016/j.biosystems.2020.104324] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 12/03/2020] [Accepted: 12/03/2020] [Indexed: 12/21/2022]
Abstract
Whether or not viruses are alive remains unsettled. Discoveries of giant viruses with translational genes and large genomes have kept the debate active. Here, a fresh approach is introduced, based on the organisational definition of life from within systems biology. It views living as a circular process of self-organisation and self-construction which is 'closed to efficient causation'. How information combines with force to fabricate and organise environmentally obtained materials, given an energy source, is here explained as a physical embodiment of informational constraint. Comparing a general virus replication cycle with Rosen's (M,R)-system shows it to be linear, rather than closed. Some viruses contribute considerable organisational information, but so far none is known to supply all required, nor the material nor energy necessary to complete their replication cycle. As a result, no known virus replication cycle is closed to efficient causation: unlike cellular obligate parasites, viruses do not match the causal structure of an (M,R)-system. Analysis based in identifying a Markov blanket in causal structure proved inconclusive, but using Integrated Information Theory on a Boolean representation, it was possible to show that the causal structure of a virocell is not different from that of the host cell.
Collapse
Affiliation(s)
- Keith D Farnsworth
- School of Biological Sciences, Queen's University Belfast, 19 Chlorine Gardens, Belfast BT95DL, UK.
| |
Collapse
|
16
|
Bartlett SJ, Beckett P. Probing complexity: thermodynamics and computational mechanics approaches to origins studies. Interface Focus 2019; 9:20190058. [PMID: 31641432 DOI: 10.1098/rsfs.2019.0058] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/06/2019] [Indexed: 12/15/2022] Open
Abstract
This paper proposes new avenues for origins research that apply modern concepts from stochastic thermodynamics, information thermodynamics and complexity science. Most approaches to the emergence of life prioritize certain compounds, reaction pathways, environments or phenomena. What they all have in common is the objective of reaching a state that is recognizably alive, usually positing the need for an evolutionary process. As with life itself, this correlates with a growth in the complexity of the system over time. Complexity often takes the form of an intuition or a proxy for a phenomenon that defies complete understanding. However, recent progress in several theoretical fields allows the rigorous computation of complexity. We thus propose that measurement and control of the complexity and information content of origins-relevant systems can provide novel insights that are absent in other approaches. Since we have no guarantee that the earliest forms of life (or alien life) used the same materials and processes as extant life, an appeal to complexity and information processing provides a more objective and agnostic approach to the search for life's beginnings. This paper gives an accessible overview of the three relevant branches of modern thermodynamics. These frameworks are not commonly applied in origins studies, but are ideally suited to the analysis of such non-equilibrium systems. We present proposals for the application of these concepts in both theoretical and experimental origins settings.
Collapse
Affiliation(s)
- Stuart J Bartlett
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA.,Earth-Life Science Institute, Tokyo Institute of Technology, Tokyo, Japan
| | - Patrick Beckett
- Department of Chemical Engineering, University of California Davis, Davis, CA, USA.,Department of Civil and Environmental Engineering, University of California Davis, Davis, CA, USA
| |
Collapse
|
17
|
Farnsworth KD. How Organisms Gained Causal Independence and How It Might Be Quantified. BIOLOGY 2018; 7:E38. [PMID: 29966241 PMCID: PMC6163937 DOI: 10.3390/biology7030038] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 04/30/2018] [Accepted: 06/23/2018] [Indexed: 12/20/2022]
Abstract
Two broad features are jointly necessary for autonomous agency: organisational closure and the embodiment of an objective-function providing a ‘goal’: so far only organisms demonstrate both. Organisational closure has been studied (mostly in abstract), especially as cell autopoiesis and the cybernetic principles of autonomy, but the role of an internalised ‘goal’ and how it is instantiated by cell signalling and the functioning of nervous systems has received less attention. Here I add some biological ‘flesh’ to the cybernetic theory and trace the evolutionary development of step-changes in autonomy: (1) homeostasis of organisationally closed systems; (2) perception-action systems; (3) action selection systems; (4) cognitive systems; (5) memory supporting a self-model able to anticipate and evaluate actions and consequences. Each stage is characterised by the number of nested goal-directed control-loops embodied by the organism, summarised as will-nestedness N. Organism tegument, receptor/transducer system, mechanisms of cellular and whole-organism re-programming and organisational integration, all contribute to causal independence. CONCLUSION organisms are cybernetic phenomena whose identity is created by the information structure of the highest level of causal closure (maximum N), which has increased through evolution, leading to increased causal independence, which might be quantifiable by ‘Integrated Information Theory’ measures.
Collapse
|
18
|
Four domains: The fundamental unicell and Post-Darwinian Cognition-Based Evolution. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2018; 140:49-73. [PMID: 29685747 DOI: 10.1016/j.pbiomolbio.2018.04.006] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Accepted: 04/12/2018] [Indexed: 02/07/2023]
Abstract
Contemporary research supports the viewpoint that self-referential cognition is the proper definition of life. From that initiating platform, a cohesive alternative evolutionary narrative distinct from standard Neodarwinism can be presented. Cognition-Based Evolution contends that biological variation is a product of a self-reinforcing information cycle that derives from self-referential attachment to biological information space-time with its attendant ambiguities. That information cycle is embodied through obligatory linkages among energy, biological information, and communication. Successive reiterations of the information cycle enact the informational architectures of the basic unicellular forms. From that base, inter-domain and cell-cell communications enable genetic and cellular variations through self-referential natural informational engineering and cellular niche construction. Holobionts are the exclusive endpoints of that self-referential cellular engineering as obligatory multicellular combinations of the essential Four Domains: Prokaryota, Archaea, Eukaryota and the Virome. Therefore, it is advocated that these Four Domains represent the perpetual object of the living circumstance rather than the visible macroorganic forms. In consequence, biology and its evolutionary development can be appraised as the continual defense of instantiated cellular self-reference. As the survival of cells is as dependent upon limitations and boundaries as upon any freedom of action, it is proposed that selection represents only one of many forms of cellular constraint that sustain self-referential integrity.
Collapse
|
19
|
Marshall W, Kim H, Walker SI, Tononi G, Albantakis L. How causal analysis can reveal autonomy in models of biological systems. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2017; 375:rsta.2016.0358. [PMID: 29133455 PMCID: PMC5686412 DOI: 10.1098/rsta.2016.0358] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/19/2017] [Indexed: 06/07/2023]
Abstract
Standard techniques for studying biological systems largely focus on their dynamical or, more recently, their informational properties, usually taking either a reductionist or holistic perspective. Yet, studying only individual system elements or the dynamics of the system as a whole disregards the organizational structure of the system-whether there are subsets of elements with joint causes or effects, and whether the system is strongly integrated or composed of several loosely interacting components. Integrated information theory offers a theoretical framework to (1) investigate the compositional cause-effect structure of a system and to (2) identify causal borders of highly integrated elements comprising local maxima of intrinsic cause-effect power. Here we apply this comprehensive causal analysis to a Boolean network model of the fission yeast (Schizosaccharomyces pombe) cell cycle. We demonstrate that this biological model features a non-trivial causal architecture, whose discovery may provide insights about the real cell cycle that could not be gained from holistic or reductionist approaches. We also show how some specific properties of this underlying causal architecture relate to the biological notion of autonomy. Ultimately, we suggest that analysing the causal organization of a system, including key features like intrinsic control and stable causal borders, should prove relevant for distinguishing life from non-life, and thus could also illuminate the origin of life problem.This article is part of the themed issue 'Reconceptualizing the origins of life'.
Collapse
Affiliation(s)
- William Marshall
- Department of Psychiatry, University of Wisconsin, 6001 Research Park Blvd, Madison, WI 53719, USA
| | - Hyunju Kim
- BEYOND: Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ, USA
- School of Earth and Space Exploration, Arizona State University, Tempe, AZ, USA
| | - Sara I Walker
- BEYOND: Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ, USA
- School of Earth and Space Exploration, Arizona State University, Tempe, AZ, USA
| | - Giulio Tononi
- Department of Psychiatry, University of Wisconsin, 6001 Research Park Blvd, Madison, WI 53719, USA
| | - Larissa Albantakis
- Department of Psychiatry, University of Wisconsin, 6001 Research Park Blvd, Madison, WI 53719, USA
| |
Collapse
|
20
|
C G N, LaBar T, Hintze A, Adami C. Origin of life in a digital microcosm. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2017; 375:rsta.2016.0350. [PMID: 29133448 PMCID: PMC5686406 DOI: 10.1098/rsta.2016.0350] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/31/2017] [Indexed: 05/09/2023]
Abstract
While all organisms on Earth share a common descent, there is no consensus on whether the origin of the ancestral self-replicator was a one-off event or whether it only represented the final survivor of multiple origins. Here, we use the digital evolution system Avida to study the origin of self-replicating computer programs. By using a computational system, we avoid many of the uncertainties inherent in any biochemical system of self-replicators (while running the risk of ignoring a fundamental aspect of biochemistry). We generated the exhaustive set of minimal-genome self-replicators and analysed the network structure of this fitness landscape. We further examined the evolvability of these self-replicators and found that the evolvability of a self-replicator is dependent on its genomic architecture. We also studied the differential ability of replicators to take over the population when competed against each other, akin to a primordial-soup model of biogenesis, and found that the probability of a self-replicator outcompeting the others is not uniform. Instead, progenitor (most-recent common ancestor) genotypes are clustered in a small region of the replicator space. Our results demonstrate how computational systems can be used as test systems for hypotheses concerning the origin of life.This article is part of the themed issue 'Reconceptualizing the origins of life'.
Collapse
Affiliation(s)
- Nitash C G
- Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA
- BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI 48824, USA
| | - Thomas LaBar
- BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI 48824, USA
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824, USA
- Program in Ecology, Evolutionary Biology and Behavior, Michigan State University, East Lansing, MI 48824, USA
| | - Arend Hintze
- Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA
- BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI 48824, USA
- Program in Ecology, Evolutionary Biology and Behavior, Michigan State University, East Lansing, MI 48824, USA
- Department of Integrative Biology, Michigan State University, East Lansing, MI 48824, USA
| | - Christoph Adami
- BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI 48824, USA
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824, USA
- Program in Ecology, Evolutionary Biology and Behavior, Michigan State University, East Lansing, MI 48824, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, MI 48824, USA
| |
Collapse
|
21
|
Walker SI. Origins of life: a problem for physics, a key issues review. REPORTS ON PROGRESS IN PHYSICS. PHYSICAL SOCIETY (GREAT BRITAIN) 2017; 80:092601. [PMID: 28593934 DOI: 10.1088/1361-6633/aa7804] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
The origins of life stands among the great open scientific questions of our time. While a number of proposals exist for possible starting points in the pathway from non-living to living matter, these have so far not achieved states of complexity that are anywhere near that of even the simplest living systems. A key challenge is identifying the properties of living matter that might distinguish living and non-living physical systems such that we might build new life in the lab. This review is geared towards covering major viewpoints on the origin of life for those new to the origin of life field, with a forward look towards considering what it might take for a physical theory that universally explains the phenomenon of life to arise from the seemingly disconnected array of ideas proposed thus far. The hope is that a theory akin to our other theories in fundamental physics might one day emerge to explain the phenomenon of life, and in turn finally permit solving its origins.
Collapse
Affiliation(s)
- Sara Imari Walker
- School of Earth and Space Exploration and Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ, United States of America. Blue Marble Space Institute of Science, Seattle, WA, United States of America
| |
Collapse
|
22
|
|
23
|
Rosslenbroich B. Properties of Life: Toward a Coherent Understanding of the Organism. Acta Biotheor 2016; 64:277-307. [PMID: 27485949 DOI: 10.1007/s10441-016-9284-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2015] [Accepted: 07/22/2016] [Indexed: 12/18/2022]
Abstract
The question of specific properties of life compared to nonliving things accompanied biology throughout its history. At times this question generated major controversies with largely diverging opinions. Basically, mechanistic thinkers, who tried to understand organismic functions in terms of nonliving machines, were opposed by those who tried to describe specific properties or even special forces being active within living entities. As this question included the human body, these controversies always have been of special relevance to our self-image and also touched practical issues of medicine. During the second half of the twentieth century, it seemed to be resolved that organisms are explainable basically as physicochemical machines. Especially from the perspective of molecular biology, it seemed to be clear that organisms need to be explained solely by the chemical functions of their component parts, although some resistance to this view never ceased. This research program has been working quite successfully, so that science today knows a lot about the physiological and chemical processes within organisms. However, again new doubts arise questioning whether the mere continuation of this analytical approach will finally generate a fundamental understanding of living entities. At the beginning of the twenty-first century the quest for a new synthesis actually comes from analytical empiricists themselves. The hypothesis of the present paper is that empirical research has been developed far enough today, that it reveals by itself the materials and the prerequisites to understand more of the specific properties of life. Without recourse to mysterious forces, it is possible to generate answers to this age-old question, just using recent, empirically generated knowledge. This view does not contradict the results of reductionistic research, but rather grants them meaning within the context of organismic systems and also may increase their practical usefulness. Although several of these properties have been discussed before, different authors usually concentrated on a single one or some of them. The paper describes ten specific properties of living entities as they can be deduced from contemporary science. The aim is to demonstrate that the results of empirical research show both the necessity as well as the possibility of the development of a new conception of life to build a coherent understanding of organismic functions.
Collapse
|
24
|
Cabrol NA. Alien Mindscapes-A Perspective on the Search for Extraterrestrial Intelligence. ASTROBIOLOGY 2016; 16:661-76. [PMID: 27383691 PMCID: PMC5111820 DOI: 10.1089/ast.2016.1536] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2016] [Accepted: 05/23/2016] [Indexed: 05/15/2023]
Abstract
UNLABELLED Advances in planetary and space sciences, astrobiology, and life and cognitive sciences, combined with developments in communication theory, bioneural computing, machine learning, and big data analysis, create new opportunities to explore the probabilistic nature of alien life. Brought together in a multidisciplinary approach, they have the potential to support an integrated and expanded Search for Extraterrestrial Intelligence (SETI (1) ), a search that includes looking for life as we do not know it. This approach will augment the odds of detecting a signal by broadening our understanding of the evolutionary and systemic components in the search for extraterrestrial intelligence (ETI), provide more targets for radio and optical SETI, and identify new ways of decoding and coding messages using universal markers. KEY WORDS SETI-Astrobiology-Coevolution of Earth and life-Planetary habitability and biosignatures. Astrobiology 16, 661-676.
Collapse
|
25
|
Sequence Data, Phylogenetic Inference, and Implications of Downward Causation. Acta Biotheor 2016; 64:133-60. [PMID: 26961079 DOI: 10.1007/s10441-016-9277-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2015] [Accepted: 03/02/2016] [Indexed: 12/30/2022]
Abstract
Framing systematics as a field consistent with scientific inquiry entails that inferences of phylogenetic hypotheses have the goal of producing accounts of past causal events that explain differentially shared characters among organisms. Linking observations of characters to inferences occurs by way of why-questions implied by data matrices. Because of their form, why-questions require the use of common-cause theories. Such theories in phylogenetic inferences include natural selection and genetic drift. Selection or drift can explain 'morphological' characters but selection cannot be causally applied to sequences since fitness differences cannot be directly associated with individual nucleotides or amino acids. The relation of selection to sequence data is by way of downward or top-down causation from those phenotypes upon which selection occurs. The application of phylogenetic inference to explain sequence data is thus restricted to instances where drift is the relevant theory; those nucleotides or amino acids that can be explained via downward causation are precluded from inclusion in the data matrix. The restrictions on the inclusion of sequence data in phylogenetic inferences equally apply to species hypotheses, precluding the more restrictive approach known as DNA barcoding. Not being able to discern drift and selection as relevant causal mechanisms can severely constrain the inclusion and explanations of sequence data. Implications of such exclusion are discussed in relation to the requirement of total evidence.
Collapse
|
26
|
Kim H, Davies P, Walker SI. New scaling relation for information transfer in biological networks. J R Soc Interface 2015; 12:20150944. [PMID: 26701883 PMCID: PMC4707865 DOI: 10.1098/rsif.2015.0944] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2015] [Accepted: 11/24/2015] [Indexed: 12/19/2022] Open
Abstract
We quantify characteristics of the informational architecture of two representative biological networks: the Boolean network model for the cell-cycle regulatory network of the fission yeast Schizosaccharomyces pombe (Davidich et al. 2008 PLoS ONE 3, e1672 (doi:10.1371/journal.pone.0001672)) and that of the budding yeast Saccharomyces cerevisiae (Li et al. 2004 Proc. Natl Acad. Sci. USA 101, 4781-4786 (doi:10.1073/pnas.0305937101)). We compare our results for these biological networks with the same analysis performed on ensembles of two different types of random networks: Erdös-Rényi and scale-free. We show that both biological networks share features in common that are not shared by either random network ensemble. In particular, the biological networks in our study process more information than the random networks on average. Both biological networks also exhibit a scaling relation in information transferred between nodes that distinguishes them from random, where the biological networks stand out as distinct even when compared with random networks that share important topological properties, such as degree distribution, with the biological network. We show that the most biologically distinct regime of this scaling relation is associated with a subset of control nodes that regulate the dynamics and function of each respective biological network. Information processing in biological networks is therefore interpreted as an emergent property of topology (causal structure) and dynamics (function). Our results demonstrate quantitatively how the informational architecture of biologically evolved networks can distinguish them from other classes of network architecture that do not share the same informational properties.
Collapse
Affiliation(s)
- Hyunju Kim
- BEYOND: Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ, USA
| | - Paul Davies
- BEYOND: Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ, USA
| | - Sara Imari Walker
- BEYOND: Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ, USA School of Earth and Space Exploration, Arizona State University, Tempe, AZ, USA ASU-SFI Center for Biosocial Complex Systems, Arizona State University, Tempe, AZ, USA Blue Marble Space Institute of Science, Seattle, WA, USA
| |
Collapse
|
27
|
|