In contemporary human brain mapping, it is commonly assumed that the “mind is what the brain does”. Based on that assumption, task-based imaging studies of the last three decades measured differences in brain activity that are thought to reflect the exercise of human mental capacities (e.g., perception, attention, memory). With the advancement of resting state studies, tractography and graph theory in the last decade, however, it became possible to study human brain connectivity without relying on cognitive tasks or constructs. It (...) therefore is currently an open question whether the assumption that “the mind is what the brain does” is an indispensable working hypothesis in human brain mapping. This paper argues that the hypothesis is, in fact, dispensable. If it is dropped, researchers can “meet the brain on its own terms” by searching for new, more adequate concepts to describe human brain organization. Neuroscientists can establish such concepts by conducting exploratory experiments that do not test particular cognitive hypotheses. The paper provides a systematic account of exploratory neuroscientific research that would allow researchers to form new concepts and formulate general principles of brain connectivity, and to combine connectivity studies with manipulation methods to identify neural entities in the brain. These research strategies would be most fruitful if applied to the mesoscopic scale of neuronal assemblies, since the organizational principles at this scale are currently largely unknown. This could help researchers to link microscopic and macroscopic evidence to provide a more comprehensive understanding of the human brain. The paper concludes by comparing this account of exploratory neuroscientific experiments to recent proposals for large-scale, discovery-based studies of human brain connectivity. (shrink)

Model organisms are a living form of scientific models. Despite the widespread use of model organisms in scientific research, the actual representational relationship between model organisms and their target species is often poorly characterized in the context of cross-species research. Many model organisms do not represent the target species adequately, let alone accurately. This is partly due to the complex and emergent life phenomena in the organism, and partly due to the fact that a model organism is always taken to (...) represent a broad range of diverse organisms. More often than not, model organisms are taken as a reference point for an extrapolation to be made to the unknown characteristics of other species. I propose to view model organisms as analogue simulators which represent the emergent phenomenon in the context of cross-species research. A model organism represents a wide range of species by simulating their molecular microstates which underlie various emergent phenomena. I show that although model organisms represent the target species inadequately at many levels of complexity, they have epistemic values as a simulator in virtue of which the emergent phenomenon can be modeled dynamically, a virtue that is hardly attainable by non-dynamic models. (shrink)

This paper aims to identify the key characteristics of model organisms that make them a specific type of model within the contemporary life sciences: in particular, we argue that the term “model organism” does not apply to all organisms used for the purposes of experimental research. We explore the differences between experimental and model organisms in terms of their material and epistemic features, and argue that it is essential to distinguish between their representational scope and representational target. We also examine (...) the characteristics of the communities who use these two types of models, including their research goals, disciplinary affiliations, and preferred practices to show how these have contributed to the conceptualization of a model organism. We conclude that model organisms are a specific subgroup of organisms that have been standardized to fit an integrative and comparative mode of research, and that it must be clearly distinguished from the broader class of experimental organisms. In addition, we argue that model organisms are the key components of a unique and distinctively biological way of doing research using models.Keywords: Experimental organism; Genetics; Model organism; Modeling; Philosophy of biology; Representation. (shrink)

Through an examination of the actual research strategies and assumptions underlying the Human Genome Project, it is argued that the epistemic basis of the initial model organism programs is not best understood as reasoning via causal analog models. In order to answer a series of questions about what is being modeled and what claims about the models are warranted, a descriptive epistemological method is employed that uses historical techniques to develop detailed accounts which, in turn, help to reveal forms of (...) reasoning that are explicit, or more often implicit, in the practice of a particular field of scientific study. It is suggested that a more valid characterization of the reasoning structure at work here is a form of case-based reasoning. This conceptualization of the role of model organisms can guide our understanding and assessment of these research programs, their knowledge claims and progress, and their limitations, as well as how we educate the public about this type of biomedical research. (shrink)

This article unpacks a particular use of ‘cases’ within developmental biology, namely as a means of describing the typical or canonical patterns of phenomena. The article explores how certain cases have come to be established within the field and argues that although they were initially selected for reasons of convenience or ease of experimental manipulation, these cases come to serve as key reference points within the field because of the epistemological structures imposed on them by the scientists using them and, (...) hence, become usable in a wider variety of circumstances including future theory development. (shrink)

Berichte zur Wissenschaftsgeschichte, Volume 45, Issue 3, Page 344-354, September 2022.

The discovery of RNA interference in 1998 has made a lasting impact on biological research. Identifying the regulatory role of small RNAs changed the modes of molecular biological inquiry as well as biologists' understanding of genetic regulation. This article examines the early years of small RNA biology's success story. I query which factors had to come together so that small RNA research came into life in the blink of an eye. I primarily look at scientific repertoires as facilitators of rapid (...) scientific change. I show that for a short period of time, between the years 1998 and 2002, different model organism communities, investigative strategies, technological innovations, and research interests could be successfully aligned to take small RNA research off the ground. I discuss how the keystone discoveries were situated in specific experimental traditions and what strategies were employed to establish these discoveries as more general phenomena. Providing thus a practice-based approach of rapid scientific change, I ask how to relate the change in propositional bits of scientific knowledge with changes in scientific practice. (shrink)

Early in his career Thomas Hunt Morgan was interested in embryology and dedicated his research to studying organisms that could regenerate. Widely regarded as a regeneration expert, Morgan was invited to deliver a series of lectures on the topic that he developed into a book, Regeneration. In addition to presenting experimental work that he had conducted and supervised, Morgan also synthesized and critiqued a great deal of work by his peers and predecessors. This essay probes into the history of regeneration (...) studies by looking in depth at Regeneration and evaluating Morgan’s contribution. Although famous for his work with fruit fly genetics, studying Regeneration illuminates Morgan’s earlier scientific approach which emphasized the importance of studying a diversity of organisms. Surveying a broad range of regenerative phenomena allowed Morgan to institute a standard scientific terminology that continues to inform regeneration studies today. Most importantly, Morgan argued that regeneration was a fundamental aspect of the growth process and therefore should be accounted for within developmental theory. Establishing important similarities between regeneration and development allowed Morgan to make the case that regeneration could act as a model of development. The nature of the relationship between embryogenesis and regeneration remains an active area of research. (shrink)

In a military-sponsored research project begun during the Second World War, inmates of the Stateville Penitentiary in Illinois were infected with malaria and treated with experimental drugs that sometimes had vicious side effects. They were made into reservoirs for the disease and they provided a food supply for the mosquito cultures. They acted as secretaries and technicians, recording data on one another, administering malarious mosquito bites and experimental drugs to one another, and helping decide who was admitted to the project (...) and who became eligible for early parole as a result of his participation. Thus, the prisoners were not simply research subjects; they were deeply constitutive of the research project. Because a prisoner’s time on the project was counted as part of his sentence, and because serving on the project could shorten one’s sentence, the project must be seen as simultaneously serving the functions of research and punishment. Michel Foucault wrote about such ‘mixed mechanisms’ in his Discipline and punish. His shining example of such a ‘transparent’ and subtle style of punishment was the panopticon, Jeremy Bentham’s architectural invention of prison cellblocks arrayed around a central guard tower. Stateville prison was designed on Bentham’s model; Foucault featured it in his own discussion. This paper, then, explores the power relations in this highly idiosyncratic experimental system, in which the various roles of model organism, reagent, and technician are all occupied by sentient beings who move among them fluidly. This, I argue, created an environment in the Stateville hospital wing more panoptic than that in the cellblocks. Research and punishment were completely interpenetrating, and mutually reinforcing. (shrink)

In 2013, Gail Davies and Helen Scalway launched Micespace.org, an interactive web-based art and research project that uses the platform of a mock mouse model repository to visualize the complex spa...

Is knowledge in the natural sciences discovered or constructed? For objectivists, scientific knowledge is discovered through investigations into a mind-independent, natural world. For constructivists, such knowledge is produced through negotiations among members of a professional guild. I examine the clash between the two positions and propose that scientific knowledge is the concurrent outcome from investigations into a natural world and from consensus reached through negotiations of a professional guild. Specifically, I introduce the general methodological notion, instituting science, which incorporates both (...) the discovery and the construction processes in the generation of scientific knowledge. To that end, I use a case study from the biomedical sciences to illustrate the notion. I conclude with a discussion of how this methodological notion helps to address the debate between objectivists and constructivists over the generation of scientific knowledge, and of how it compares with others who have also attempted to address the debate. (shrink)

Model organismism—the over-reliance on model organisms without sufficient attention to the adequacy of the models—continues to hobble our understanding of human brains and behaviors. I outline the problem of model organismism in contemporary biology and biomedicine, and discuss the virtues of a genuinely comparative biology for understanding ourselves, our evolutionary history, and our place in nature.

ABSTRACT In our current moment, there is considerable interest in networks, in how people and things are connected. This essay outlines one approach that brings together insights from actor-network theory, social network analysis, and digital history to interpret past scientific activity. Multispecies network analysis (MNA) is a means of understanding the historical interactions among scientists, institutions, and preferred experimental animals. A reexamination of studies of sexual behavior funded by the Committee for Research in Problems of Sex between the 1920s and (...) the 1940s demonstrates the applicability of MNA to clarifying the relations that sustained this area of psychology. The measures of weighted degree and betweenness can highlight which nodes (whether organisms or institutions) were particularly “central” to this network. Rats featured as the animals most widely studied during this period, but the analysis also reveals distinct institutional and disciplinary cultures where different species were favored as either surrogates for humans or representatives of more general biological groups. (shrink)

The discovery and ongoing investigation of microRNAs suggest important conceptual and methodological lessons for philosophers and historians of biology. This paper provides an account of miRNA research and the shift from viewing these tiny regulatory entities as minor curiosities to seeing them as major players in the post-transcriptional regulation of genes. Conceptually, the study of miRNAs is part of a broader change in understandings of genetic regulation, in which simple switch-like mechanisms were reinterpreted as aspects of complex cellular and genome-wide (...) processes. Among them are the activities of small RNAs, previously regarded as non-functional. Methodologically, the miRNA story suggests new ways of characterizing biological research that should prove helpful to philosophers of science who seek to develop more pluralistic, pragmatic models of scientific inquiry. miRNA research displays iterative movements between multiple modes of investigation that include not only the proposal and testing of hypotheses but also exploratory, technology-oriented and question-driven modes of research. As an exemplary story of scientific discovery and development, the miRNA case illustrates transitions from genetics to genomics and systems biology, and it shows how diverse configurations of research practice are related to major scientific advances. (shrink)

Model organisms became an indispensable part of experimental systems in molecular developmental and cell biology, constructed to investigate physiological and pathological processes. They are thought to play a crucial role for the elucidation of gene function, complementing the sequencing of the genomes of humans and other organisms. Accordingly, historians and philosophers paid considerable attention to various issues concerning this aspect of experimental biology. With respect to the representational features of model organisms, that is, their status as models, the main focus (...) was on generalization of phenomena investigated in such experimental systems. Model organisms have been said to be models for other organisms or a higher taxon. This, however, presupposes a representation of the phenomenon in question. I will argue that prior to generalization, model organisms allow researchers to built generative material models of phenomena – structures, processes or the mechanisms that explain them – through their integration in experimental set-ups that carve out the phenomena from the whole organism and thus represent them. I will use the history of zebrafish biology to show how model organism systems, from around 1970 on, were developed to construct material models of molecular mechanisms explaining developmental or physiological processes. (shrink)

Scholars in science and technology studies, as well as economics and innovation studies, utilize the trajectory metaphor in describing a technology’s maturation. Impetus and purpose may differ, but the trajectory serves as a shared tool for assessing social change either in society at large or within a market sector, a firm, or a discipline. In reverse, the lens of a technology trajectory can be a basis for assessing technology, estimating economic growth, and selecting among plausible product development pathways. Emerging technologies (...) pose a challenge in that the promissory claims that attracted investment may also challenge social safeguards, leading to necessary, but unforeseen hurdles to later technology acceptance. The experiences with biotechnology and nanotechnology demonstrate that knowledge gained in the intervening years was to have tempered exaggerations and addressed the criteria and the responsibilities of those who would later be deciding on product acceptability. In particular, the promissory claim for nanotechnology, unique phenomena, challenged regulatory practice, while claims for biotechnology products were often the fruition of themes found in the educational experience common to both the biotechnology researcher and the regulator. The social science and humanities literature mirrored these points as did the responses of civil society organizations. A prospective trajectory for artificial intelligence is developed using the example of driverless cars and then qualitatively compared to the retrospective trajectories for nanotechnology and biotechnology. Experience with automation, algorithm transparency, and computational modeling of biological mechanisms are identified as pertinent to responsible AI development. (shrink)

Multiscale modeling techniques have attracted increasing attention by philosophers of science, but the resulting discussions have almost exclusively focused on issues surrounding explanation (e.g., reduction and emergence). In this paper, I argue that besides explanation, multiscale techniques can serve important exploratory functions when scientists model systems whose organization at different scales is ill-understood. My account distinguishes explanatory and descriptive multiscale modeling based on which epistemic goal scientists aim to achieve when using multiscale techniques. In explanatory multiscale modeling, scientists use multiscale (...) techniques to select information that is relevant to explain a particular type of behavior of the target system. In descriptive multiscale modeling scientists use multiscale techniques to explore lower-scale features which could be explanatorily relevant to many different types of behavior, and to determine which features of a target system an upper-scale data pattern could refer to. Using multiscale models from data-driven neuroscience as a case study, I argue that descriptive multiscale models have an exploratory function because they are a sources of potential explanations and serve as tools to reassess our conception of the target system. (shrink)

Emphatic claims of a “microbiome revolution” aside, the study of the gut microbiota and its role in organismal development and evolution is a central feature of so-called postgenomics; namely, a conceptual and/or practical turn in contemporary life sciences, which departs from genetic determinism and reductionism to explore holism, emergentism and complexity in biological knowledge-production. This paper analyses the making of postgenomic knowledge about developmental symbiosis in Drosophila melanogaster by a specific group of microbiome scientists. Drawing from both practical philosophy of (...) science and Science and Technology Studies, the paper documents epistemological questions of artefactuality and representativeness of model organisms as they emerge in the day-to-day labour producing and being produced by the “microbiome revolution." Specifically, the paper builds on all the written and editorial exchanges involved in the troubled publication of a research paper studying the symbiotic role of the microbiota in the flies’ development. These written materials permit us to delimit the network of justifications, evidence, standards of knowledge-production, trust in the tools and research designs that make up the conditions of possibility of a postgenomic fact. More than reframing the organism as a radically novel multiplicity of reactive genomes, we conclude, doing postgenomic research on the microbiota and symbiosis means producing a story that deviates from the scripts embedded into the sociotechnical experimental systems of post-Human Genome Project life sciences. (shrink)

Despite the importance of network analysis in biological practice, dominant models of scientific explanation do not account satisfactorily for how this family of explanations gain their explanatory power in every specific application. This insufficiency is particularly salient in the study of the ecology of the microbiome. Drawing on Coyte et al. (2015) study of the ecology of the microbiome, Deulofeu et al. (2021) argue that these explanations are neither mechanistic, nor purely mathematical, yet they are substantially empirical. Building on their (...) criticisms, in the present work we make a step further elucidating this kind of explanations with a general analytical framework according to which scientific explanations are ampliative, specialized embeddings (ASE), which has recently been successfully applied to other biological subfields. We use ASE to reconstruct in detail the Coyte et al.’s case study and on its basis, we claim that network explanations of the ecology of the microbiome, and other similar explanations in ecology, gain their epistemological force in virtue of their capacity to embed biological phenomena in non-accidental generalizations that are simultaneously ampliative and specialized. (shrink)

Mechanist philosophers have examined several strategies scientists use for discovering causal mechanisms in neuroscience. Findings about the anatomical organization of the brain play a central role in several such strategies. Little attention has been paid, however, to the use of network analysis and causal modeling techniques for mechanism discovery. In particular, mechanist philosophers have not explored whether and how these strategies incorporate information about the anatomical organization of the brain. This paper clarifies these issues in the light of the distinction (...) between structural, functional and effective connectivity. Specifically, we examine two quantitative strategies currently used for causal discovery from functional neuroimaging data: dynamic causal modeling and probabilistic graphical modeling. We show that dynamic causal modeling uses findings about the brain’s anatomical organization to improve the statistical estimation of parameters in an already specified causal model of the target brain mechanism. Probabilistic graphical modeling, in contrast, makes no appeal to the brain’s anatomical organization, but lays bare the conditions under which correlational data suffice to license reliable inferences about the causal organization of a target brain mechanism. The question of whether findings about the anatomical organization of the brain can and should constrain the inference of causal networks remains open, but we show how the tools supplied by graphical modeling methods help to address it. (shrink)

A striking characteristic of the highly successful techniques in molecular biology is that they are derived from natural systems. RNA interference, for example, utilises a mechanism that evolved in eukaryotes to destroy foreign nucleic acid. Other examples include restriction enzymes, the polymerase chain reaction, green fluorescent protein and CRISPR-Cas. I propose that biologists exploit natural molecular mechanisms for their effectors’ activity and biological specificity. I also show that the developmental trajectory of novel techniques in molecular biology, such as RNAi, is (...) four characteristic phases. The first phase is discovery of a biological phenomenon, typically as curiosity driven research. The second is identification of the mechanism’s trigger, the effector and biological specificity. The third is the application of the technique. The final phase is the maturation and refinement of the molecular biology technique. The development of new molecular biology techniques from nature is crucial for biological research. These techniques transform scientific knowledge and generate new knowledge. (shrink)