Although researchers in psychiatry have been trying for decades to elucidate the pathophysiology underlying mental disorders, relatively little progress has been made. One explanation for this failure is that diagnostic categories in psychiatry are unlikely to track underlying neurological mechanisms. Because of this, the US National Institutes of Mental Health has recently developed a novel ontology to guide research in biological psychiatry: the Research Domain Criteria. In this paper, I argue that while RDoC may lead to better neuroscientific explanations for (...) mental disorders, it is unlikely that this new knowledge will then lead to an improved diagnostic system. I therefore suggest that researchers in psychiatry should work toward the development of two new ontologies: one for research and one for clinical practice. (shrink)

The dominant assumption about the causal architecture of the mind is, that it is composed of a stable set of components that contribute independently to relevant observables that are employed to measure cognitive activity. This view has been called component-dominant dynamics. An alternative has been proposed, according to which the different components are not independent, but fundamentally interdependent, and are not stable basic properties of the mind, but rather an emergent feature of the mind given a particular task context. This (...) view has been called interaction-dominant dynamics. In this paper, we review evidence for interaction-dominant dynamics as the causal architecture of the mind. We point out, that such an architecture is consistent with problems of convergence in research on the level of results and theorizing. Moreover, we point out that if interaction-dominant dynamics as the causal architecture of the mind were to be true, this would naturally lead to problems with generalization and replicability in sciences of the mind and brain, and would probably warrant changes in the scientific practice with regard to study-design and data analysis. (shrink)

A significant portion of the scholarship in analytic philosophy of psychiatry has been devoted to the problem of what kind of kind psychiatric disorders are. Efforts have included descriptive projects, which aim to identify what psychiatrists in fact refer to when they diagnose, and prescriptive ones, which argue over that to which diagnostic categories should refer. In other words, philosophers have occupied themselves with what I call “diagnostic kinds”. However, the pride of place traditionally given to diagnostic kinds in psychiatric (...) research has recently come under attack, most notably by a recent initiative of the National Institute of Mental Health, the Research Domain Criteria Project, that seeks to exclude diagnostic categories from experimental designs and focus on other sorts of psychiatric kinds. I argue that philosophical accounts privileging diagnostic kinds must respond to this new line of criticism, and conclude that philosophers need to either counter psychiatrists’ growing suspicion about the hegemony of diagnostic categories in the clinic and the laboratory, or join in redirecting their efforts toward the development of robust accounts of other sorts of psychiatric objects and processes. (shrink)

The past decade has witnessed a growing awareness of conceptual and methodological hurdles within psychology and neuroscience that must be addressed for taxonomic and explanatory progress in understanding psychological functions to be possible. In this paper, I evaluate several recent knowledge-building initiatives aimed at overcoming these obstacles. I argue that while each initiative offers important insights about how to facilitate taxonomic and explanatory progress in psychology and neuroscience, only a “coordinated pluralism” that incorporates positive aspects of each initiative will have (...) the potential for success. (shrink)

Discussions of psychiatric nosology focus on a few popular examples of disorders, and on the validity of diagnostic criteria. Looking at Anorexia Nervosa, an example rarely mentioned in this literature, reveals a new problem: the DSM has a strict taxonomic structure, which assumes that disorders can only be located on one branch. This taxonomic assumption fails to fit the domain of psychopathology, resulting in obfuscation of cross-category connections. Poor outcomes for treatment of Anorexia may be due to it being pigeonholed (...) as an Eating Disorder, when a disturbance of body perception may be a more central symptom than food restriction. This paper explores the possibility of restructuring the DSM taxonomy to allow for a pluralist classification of disorders. This change could improve treatment and research without requiring any changes to diagnostic criteria. (shrink)

Neuroimaging technology is the most widely used tool to study human cognition. While originally a promising tool for mapping the content of cognitive theories onto the structures of the brain, recently developed tools for the analysis, handling and sharing of data have changed the theoretical landscape of cognitive neuroscience. Even with these advancements philosophical analyses of evidence in neuroimaging remain skeptical of the promise of neuroimaging technology. These views often treat the analysis techniques used to make sense of data produced (...) in a neuroimaging experiment as one, attributing the inferential limitations of analysis pipelines to the technology as a whole. Situated against the neuroscientists own critical assessment of their methods and the limitations of those methods, this skepticism appears based on a misunderstanding of the role data analysis techniques play in neuroimaging research. My project picks up here, examining how data analysis techniques, such as pattern classification analysis, are used to assess the evidential value of neuroimaging data. The project takes the form of three papers. In the first I identify the use of multiple data analysis techniques as an important aspect of the data interpretation process that is overlooked by critics. In the second I develop an account of inferences in neuroimaging research that is sensitive to this use of data analysis techniques, arguing that interpreting neuroimaging data is a process of isolating and explaining a variety of data patterns. In the third I argue that the development and uptake of new techniques for analyzing data must be accompanied by changes in research practices and standards of evidence if they are to promote knowledge generation. My approach to this work is both traditionally philosophical, insofar as it involves reading and analyzing the work of philosophers and neuroscientists, and embedded insofar as most of the research was conducted while engaged in attending lab meetings and participating in the work of those scientists whose work is the object of my research. (shrink)

Advances in emotion and affective science have yet to translate routinely into psychiatric research and practice. This is unfortunate since emotion and affect are fundamental components of many psychiatric conditions. Rectifying this lack of interdisciplinary integration could thus be a potential avenue for improving psychiatric diagnosis and treatment. In this contribution, we propose and discuss an ontological framework for explicitly capturing the complex interrelations between affective entities and psychiatric disorders, in order to facilitate mapping and integration between affective science and (...) psychiatric diagnostics. We build on and enhance the categorisation of emotion, affect and mood within the previously developed Emotion Ontology, and that of psychiatric disorders in the Mental Disease Ontology. This effort further draws on developments in formal ontology regarding the distinction between normal and abnormal in order to formalize the interconnections. This operational semantic framework is relevant for applications including clarifying psychiatric diagnostic categories, clinical information systems, and the integration and translation of research results across disciplines. (shrink)