Maël Lemoine

Following the neurophenomenological approach, we propose a model of emotional emergence that identifies the experimental structures of time involved in emotional experience and their plausible components in terms of cognition, physiology, and neuroscience. We argue that surprise, as a lived experience, and its physiological correlates of the startle reflex and cardiac defense are the core of the dynamic, and that the heart system sets temporally in motion the dynamic of emotional emergence. Finally, in reference to Craig’s model of emotion, we propose an integrative model of the temporal dynamic of emotional emergence that allows emotions to be distinguished depending on each temporal phase and that involves the following three systems: the brain , the consciousness , and the doubled-sided continuum of the body-heart context, with the heart as the focus within the body during emotion. This model provides the framework for future developments in 1st- and 3rd-person approaches for an integrative understanding of the science of emotion, including the fields of psychophysiology and psychopathology

La conception traditionnelle des théories scientifiques en philosophie de langue anglaise, qu’on appelle la « received view », et qui culmine au début des années 1960, posait de nombreux obstacles à une conception des théories scientifiques en biologie et en médecine. La conception sémantique des théories scientifiques qui lui succéda permit de lever ces obstacles, mais pas de différencier les théories en biologie expérimentale et en médecine. Le présent article met en évidence comment, en s’appuyant sur cette conception, Schaffner établit la spécificité des théories biologiques et médicales par rapport aux théories physiques, comment Thompson établit que c’est le savoir biologique et non le savoir clinique qui, véritablement théorique, fonde le caractère proprement scientifique de la médecine, et enfin, comment Sadegh-Zadeh peut proposer à son tour des caractéristiques des théories médicales qui leur sont potentiellement spécifiques et les distinguent des théories biologiques.

En France, l'épistémologie de la médecine est facilement réduite à l'étude du magistral essai de Canguilhem, Le normal et le pathologique. Toutefois, ce livre publié il y a plus de soixante-dix ans ne reflète plus l'état des sciences médicales contemporaines, ni celui des débats poursuivis par les philosophes des sciences depuis. Le présent livre, premier du genre en langue française, a pour ambition d'introduire le lecteur à la philosophie des sciences médicales. Ses dix chapitres initieront le lecteur aux débats qui l'agitent, sans que soient requises des connaissances philosophiques ou médicales préalables. Il répond à la fois à la demande de médecins en quête d'une philosophie qui leur parle de leur discipline et de leurs pratiques, et de philosophes à la recherche d'un guide dans ce champ morcelé et dominé par la philosophie d'expression anglaise. [Payot]

Since the turn of the twenty-first century, biomedical psychiatry around the globe has embraced the so-called precision medicine paradigm, a model for medical research that uses innovative techniques for data collection and analysis to reevaluate traditional theories of disease. The goal of precision medicine is to improve diagnostics by restratifying the patient population on the basis of a deeper understanding of disease processes. This paper argues that precision is ill-fitting for psychiatry for two reasons. First, in psychiatry, unlike in fields like oncology, precision medicine has been understood as an attempt to improve medicine by casting out, rather than merely revising, traditional taxonomic tools. Second, in psychiatry the term “biomarker” is often used in reference to signs or symptoms that allow patients to be classified and then matched with treatments; however, in oncology “biomarker” usually refers to a disease mechanism that is useful not only for diagnostics, but also for discovering causal pathways that drug therapies can target. Given these differences between how the precision medicine paradigm operates in psychiatry and in other medical fields like oncology, while precision psychiatry may offer successful rhetoric, it is not a promising paradigm.

In this paper, we provide a macro level analysis of the visibility of philosophy of science in the sciences over the last four decades. Our quantitative analysis of publications and citations of philosophy of science papers, published in 17 main journals representing the discipline, contributes to the longstanding debate on the influence of philosophy of science on the sciences. It reveals the global structure of relationships that philosophy of science maintains with science, technology, engineering and mathematics and social sciences and humanities fields. Explored at the level of disciplines, journals and authors, this analysis of the relations between philosophy of science and a large and diversified array of disciplines allows us to answer several questions: what is the degree of openness of various disciplines to the specialized knowledge produced in philosophy of science? Which STEM and SSH fields and journals have privileged ties with philosophy of science? What are the characteristics, in terms of citation and publication patterns, of authors who get their philosophy of science papers cited outside their field? Complementing existing qualitative inquiries on the influence of specific authors, concepts or topics of philosophy of science, the bibliometric approach proposed in this paper offers a comprehensive portrait of the multiple relationships that links philosophy of science to the sciences.

Aging is an elusive property of life, and many important questions about aging depend on its definition. This article proposes to draw a definition from the scientific literature on aging. First, a broad review reveals five features commonly used to define aging: structural damage, functional decline, depletion, typical phenotypic changes or their cause, and increasing probability of death. Anything that can be called ‘aging’ must present one of these features. Then, although many conditions are not consensual instances of aging, aging is consensually described as a process of loss characterized by a rate and resulting from the counteraction of protective mechanisms against mechanisms that limit lifespan. Beyond such an abstract definition, no one has yet succeeded in defining aging by a specific mechanism of aging because of an explanatory gap between such a mechanism and lifespan, a consensual explanandum of a theory of aging. By contrast, a sound theoretical definition can be obtained by revisiting the evolutionary theory of aging. Based on this theory, aging evolves thanks to the impossibility that natural selection eliminates late traits that are neutral mainly due to decreasing selective pressure. Yet, the results of physiological research suggest that this theory should be revised to also account for the small number of different aging pathways and for the existence of mechanisms counteracting these pathways, that must, on the contrary, have been selected. A synthetic, but temporary definition of aging can finally be proposed.

Philosophers of science have recently focused on the scientific activity of modeling phenomena, and explicated several of its properties, as well as the activities embedded into it. A first approach to modeling has been elaborated in terms of representing a target system: yet other epistemic functions, such as producing data or detecting phenomena, are at least as relevant. Additional useful distinctions have emerged, such as the one between phenomenological and mechanistic models. In biological sciences, besides mathematical models, models now come in three forms: in vivo, in vitro and in silico. Each has been investigated separately, and many specific problems they raised have been laid out. Another relevant distinction is disciplinary: do models differ in significant ways according to the discipline involved—medicine or biology, evolutionary biology or earth science? Focusing on either this threefold distinction or the disciplinary boundaries reveals that they might not be sufficient from a philosophical perspective. On the contrary, focusing on the interaction between these various kinds of models, some interesting forms of explanation come to the fore, as is exemplified by the papers included in this issue. On the other hand, a focus on the use of models, rather than on their content, shows that the distinction between biological and medical models is theoretically sound.

According to the received view, the transportation view, animal extrapolation consists in inductive prediction of the outcome of a mechanism in a target, based on an analogical mechanism in a model. Through an analysis of the failure of preclinical studies of TGN1412, an innovative drug, to predict the tragic consequences of its first-in-man trial in 2006, the received view is challenged by a proposed view of animal extrapolation, the chimera view. According to this view, animal extrapolation is based on a hypothesis about how human organisms work, supported by the amalgamation of results drawn from various experimental organisms, and only predicting the ‘predictive grid’, that is, a global framework of the effects to be expected.

Despite its vagueness Personalized, Precision, P4, P5, individualized, stratified medicine—or p-medicine in short—has become an increasingly popular term in biomedical literature. Philosophers have attempted to analyze what these various terms involve and have discussed consequences for medical practices. In this article, I argue that an important question remains unaddressed: what has made this project of p-medicine convincing to so many? My argument is that without real achievements, it would never have been. I also make the case that these achievements stem from the domain of monoclonal antibodies, a new type of drug that justifies talks of personalized, precise, stratified, etc., medicine. In conclusion, while it may be possible to label any projection in the future of medicine as ‘p-medicine’, it is impossible to overlook mab-medicine as the spearhead.

Science starts by using terms such as ‘temperature’ or ‘fish’ or ‘gene’ to preliminarily delimitate the extension of a phenomenon, and concludes by giving most of them a technical meaning based on an explanatory model. This transforma- tion of the meaning of the term is an essential part of its naturalization. Debating on the definition of ‘disease’, what most philosophers of medicine have examined is the pre-naturalized meaning of the term: for that reason they have focused on the task of delimiting disease and non-disease (health), mainly used conceptual analysis as a method of choice, and considered the nosological level of ‘disease judgments’ rather than the pathophysiological or psychopathological level of disease mechanisms, thus making them impervious to most scientific discoveries. By focusing instead on the naturalized concept of disease and following some suggestions by philosophers of biology and scientists in cutting-edge fields of biomedical research, they could gar- ner results from a comparison of the mechanisms of diseases. This would ultimately result in a general theory of disease linked with our most general theories on living beings, among them, systems biology and network medicine. Before undertaking such a task, preliminary questions arise: is it likely that there are biological features common to different types of disease? Is it a philosopher’s job to determine what they consist in? What use would such a general theoretical definition of disease be?

Contrairement aux idées reçues, Hegel n’est pas un précurseur de la pensée totalitaire, auquel on pourrait opposer un Bergson républicain et démocrate. Tous deux parlent de la communauté politique comme d’un organisme, doctrine affectionnée du totalitarisme. Ni chez l’un, ni chez l’autre, on ne peut atténuer la portée de l’affirmation en invoquant un usage métaphorique : il faut entendre, chez l’un comme chez l’autre, l’organisme au sens propre mais large. L’organicité du politique, loin de la menacer, est la seule forme compatible avec la liberté des individus, grâce à la distinction que l’on peut faire entre organisation toute faite et organisation se faisant : si la première traite les individus en rouages d’un mécanisme, la seconde est l’expression immédiate de l’épanouissement de leurs libertés.Popper wrote that Hegel, as a thinker, is a forerunner of totalitarianism ; on the other hand, one cannot but regard Bergson as a true democrat. Both however considered the politic body as an organism, a doctrine supporters of the totalitarian state favoured. The assertion must not be underrated : neither thinker intended to use a metaphorical expression, hence a broad meaning of « organism ». As a matter of fact the organicity of a politic body, far from threatening individual freedom, is the only form that proves compatible with individuality. The important thing is to distinguish all-made « organized organisation » from selfmaking « organizing organisation » : the former treats individuals as mechanical entities, while the latter is the result of the self-development of their freedom

Conceptual analysis of health and disease is portrayed as consisting in the confrontation of a set of criteria—a “definition”—with a set of cases, called instances of either “health” or “ disease.” Apart from logical counter-arguments, there is no other way to refute an opponent’s definition than by providing counter-cases. As resorting to intensional stipulation is not forbidden, several contenders can therefore be deemed to have succeeded. This implies that conceptual analysis alone is not likely to decide between naturalism and normativism. An alternative to this approach would be to examine whether the concept of disease can be naturalized

Philosophers of science have recently focused on the scientific activity of modeling phenomena, and explicated several of its properties, as well as the activities embedded into it. A first approach to modeling has been elaborated in terms of representing a target system: yet other epistemic functions, such as producing data or detecting phenomena, are at least as relevant. Additional useful distinctions have emerged, such as the one between phenomenological and mechanistic models. In biological sciences, besides mathematical models, models now come in three forms: in vivo, in vitro and in silico. Each has been investigated separately, and many specific problems they raised have been laid out. Another relevant distinction is disciplinary: do models differ in significant ways according to the discipline involved—medicine or biology, evolutionary biology or earth science? Focusing on either this threefold distinction or the disciplinary boundaries reveals that they might not be sufficient from a philosophical perspective. On the contrary, focusing on the interaction between these various kinds of models, some interesting forms of explanation come to the fore, as is exemplified by the papers included in this issue. On the other hand, a focus on the use of models, rather than on their content, shows that the distinction between biological and medical models is theoretically sound.

If the healthy and the pathological are not merely judgments qualifiers, but real phenomena, it must be possible to define both of them positively, which, in this context, means as factual contraries. On the other hand, only a privative definition, either of the pathological as 'non-healthy', or of the healthy as 'non-pathological', can rationally circumscribe all possible states of an organism. This fluctuation between two meanings of the 'healthy'-'pathological' opposition, factual vs. rational, characterizes the ordinary usage of these concepts and puts all philosophical definitions in a hopeless situation. Although a scientific definition may conceal this equivocation by adequately setting out the terms of the problem of discriminating between the 'healthy' and the 'pathological', it could explain some of the difficulties met in determining 'gold standards', in the choice of separators, and in the assessment of the diagnostic qualities of tests.

Philosophers of biology usually distinguish historical and systemic accounts of functions. In many areas of experimental biology the "systemic" account is often the most relevant. Yet there are problems this account does admittedly not face up to very well. My contention is that, though two minor problems are irredeemably unsolvable for the systemic account of function, the major ones can be solved by assuming that 'function' denotes (directly) a causal role in a model and (indirectly) the corresponding process in nature. I try to show this through the analysis of the hypothalamus-pituitary-adrenal axis of stress.

La médecine ne se contente pas de diagnostiquer et de traiter des maladies : elle vise aussi à les expliquer. En cela, elle prend pied de plein droit dans le domaine de la science. En quoi consistent les explications médicales, et qu'est-ce qui les singularise au sein des explications en biologie? La première caractéristique des explications médicales est leur pluralité. La médecine semble en effet réunir sous un même label des explications très diverses, voire hétérogènes, unies seulement par l'objet d'application et la visée thérapeutique. Le propre de l'explication scientifique médicale, c'est sa pluridisciplinarité.Un canevas théorique est nécessaire pour mettre en évidence ce qui, dans une explication scientifique, peut permettre une telle diversité des explications. Celui-ci est fourni par la notion de " valeur explicative " : une croyance, injustifiable, mais bien fondée, en l'exhaustivité des conditions initiales dont une explication doit tenir compte. Bien qu'elle tende par elle-même à tout expliquer sans reste, et qu'elle exclut du domaine disciplinaire qu'elle définit ainsi tout autre type d'explication, une valeur explicative n'exclut jamais en droit la possibilité d'explications scientifiques d'autres types. Un nombre indéfini de valeurs explicatives, exclusives les unes des autres, fondatrices de domaines scientifiques distincts, est donc possible. La médecine présente ainsi la particularité de rassembler plusieurs valeurs explicatives différentes et qui plus est, de les contraindre à la convergence ou à la collaboration. Quelques-unes des principales valeurs explicatives de la médecine sont présentées, de même que les enjeux de leur confrontation. Clinique, épidémiologique, mécanique, génétique, cytologique, infectiologique, pharmacologique, l'explication médicale se fonde à chaque fois sur une manière différente de considérer le phénomène pathologique.