Much research in the philosophy of psychiatry has been devoted to the characterization of the normal and the pathological. In this article, we identify and deconstruct two postulates that have held sway in the philosophy of psychiatry. The first postulate concerns the belief that clinicians would benefit from conceiving of psychiatric disorders as stable entities with clear boundaries. By relying on a symptom-based approach, we support a conception of psychiatric disorders whose symptoms are the products of many activated mechanisms in (...) mutual interactions. The second postulate concerns the way in which the philosophy of psychiatry has approached the question of harm. We posit that clinicians perceive harms primarily through networks of clinical manifestations. The identification and deconstruction of these two postulates leads us to propose a practical definition of a psychiatric disorder that is useful for the clinician, while adopting a principle of prudential conservatism that does not exclude other theoretical definitions of psychiatric disorder that are useful as an epistemic hub. Thus, we propose the following definition of a psychiatric disorder that is relevant to clinical practice: “a set of clinical manifestations belonging to the prototypical central core of psychiatry, organized in a causal network, involving at least one harm, and whose set of harms exceeds the traditional threshold of significance for a given psychiatric disorder, directly related to an activated mechanism. Such a network composed of clinical manifestations is frozen in a state that is unable to allow the deactivation of these manifestations spontaneously without a therapeutic intervention”. (shrink)

According to the free energy principle, life is an “inevitable and emergent property of any random dynamical system at non-equilibrium steady state that possesses a Markov blanket” :20130475, 2013). Formulating a principle for the life sciences in terms of concepts from statistical physics, such as random dynamical system, non-equilibrium steady state and ergodicity, places substantial constraints on the theoretical and empirical study of biological systems. Thus far, however, the physics foundations of the free energy principle have received hardly any attention. (...) Here, we start to fill this gap and analyse some of the challenges raised by applications of statistical physics for modelling biological targets. Based on our analysis, we conclude that model-building grounded in the free energy principle exacerbates a trade-off between generality and realism, because of a fundamental mismatch between its physics assumptions and the properties of actual biological targets. (shrink)

The increasing application of network models to interpret biological systems raises a number of important methodological and epistemological questions. What novel insights can network analysis provide in biology? Are network approaches an extension of or in conflict with mechanistic research strategies? When and how can network and mechanistic approaches interact in productive ways? In this paper we address these questions by focusing on how biological networks are represented and analyzed in a diverse class of case studies. Our examples span from (...) the investigation of organizational properties of biological networks using tools from graph theory to the application of dynamical systems theory to understand the behavior of complex biological systems. We show how network approaches support and extend traditional mechanistic strategies but also offer novel strategies for dealing with biological complexity. (shrink)

Several philosophers have recently argued that phenomenology is well-suited to help understand the concepts of health, disease, and illness. The general claim is that by better analysing how illness appears to or is experienced by ill individuals—incorporating the first-person perspective—some limitations of what is seen as the currently dominant third-person or ‘naturalistic’ approaches to understand health and disease can be overcome. In this article, after discussing some of the main insights and benefits of the phenomenological approach, I develop three general (...) critiques of it. First, I show that what is often referred to as naturalism tends to be misunderstood and/or misrepresented, resulting in straw-man arguments. Second, the concept of normality is often problematically employed such that some aspects of naturalism are actually presupposed by many phenomenologists of medicine. Third, several of the key phenomenological insights and concepts, e.g. having vs. being a body, the alienation of illness, the epistemic role of the first-person perspective, and the idea of health within illness, each bring with them new problems that limit their utility. While acknowledging the possible contributions of phenomenology, these criticisms point to some severe limitations of bringing phenomenological insights to bear on the problems facing philosophy of medicine that should be addressed if phenomenology is to add anything substantially new to its debates. (shrink)

Systems biology has provided new resources for discovering and reasoning about mechanisms. In addition to generating databases of large bodies of data, systems biologists have introduced platforms such as Cytoscape to represent protein–protein interactions, gene interactions, and other data in networks. Networks are inherently flat structures. One can identify clusters of highly connected nodes, but network representations do not represent these clusters as at a higher level than their constituents. Mechanisms, however, are hierarchically organized: they can be decomposed into their (...) parts and their activities can be decomposed into component operations. A potent bridge between flat networks and hierarchical mechanisms is provided by biological ontologies, both those curated by hand such as Gene Ontology and those extracted directly from databases such as Network Extracted Ontology. I examine several examples in which by applying ontologies to networks, systems biologists generate new hypotheses about mechanisms and characterize these novel strategies for developing mechanistic explanations. (shrink)