Neuropsychiatric research searches to understand mental disorders in terms of underlying brain activity (e.g., Greicius 2008; Poldrack et al. 2012). Investigations into the underlying neurological substrate(s) of mental disorders are crucially dependent on the possibility to observe brain activity in vivo. Without the presence of brain imaging technologies allowing for the visualization of functional brain activity, such as Electroencephalography (EEG) or functional Magnetic Resonance Imaging (fMRI), this cannot be done.
In postphenomenology, technologies in scientific practice are understood as mediating intentional relations between scientists and the world (e.g., Ihde 1991, 2009; Verbeek 2005). Technologies help to shape the objects that scientists investigate, instead of being mere instruments that allow the observation of objects ‘out there’; they mediate how scientists can perceive what they study, and in doing so they also shape the interpretative frameworks to make sense of these perceptions. That is, in the developing relationship between scientists and the technologies they use, simultaneously a specific relationship between scientist and reality is being constituted. Within such a relation, specific interpretative categories and options for action and manipulation come into being that allow scientists to understand the object under study in a variety of ways (Ihde 1991, p. 137). Technological mediations are always accompanied by human appropriations of those, such that they are integrated into particular schemes of interpretation and action (Verbeek 2016). The way in which technologies mediate how scientists understand their objects of study does not only depend on the characteristics of these technologies but also on the ways in which scientists make sense of the technologies and give them a place in their relations to the object of study.
The perspective of technological mediation allows us to study how the objects that neuroscientists investigate (e.g., cognitive functions, mental disorders) are shaped by how brain imaging technologies help to disclose them (De Boer et al. 2020). Accordingly, also how neuropsychiatrists relate to (symptoms of) mental disorders is contingent on how they relate to the technologies they use to investigate those disorders. In this paper, we use this perspective to study how these technologies mediate the way(s) in which neuropsychiatrists understand mental disorders by making brain activity perceptually available in vivo. Specifically, we focus on how this technological mediation constitutes the human brain as complex, and on how researchers appropriate this complexity.
As was indicated before, the promise of integrating brain imaging technologies into neuropsychiatry is that these allow to measure brain activity, which will lead to more fine-grained diagnostics and treatment in the long run. In the laboratory in which the data of this study was obtained, brain imaging technologies such as fMRI are primarily used to investigate how mental disorders such as ASD, Obsessive Compulsive Disorder (OCD) or ADHD correlate with specific patterns of brain activity.
Diagnosing someone with ADHD, OCD, or ASD is not to point to a singular entity, but to categorize a multiplicity of different symptoms under a single header. For example, the DSM-V lists the following symptoms as diagnostic criteria for ASD: (i) Persistent deficits in social communication and social interaction, (ii) restricted, repetitive patterns of behavior, interest, or activities, (iii) symptoms must be present in early developmental period, (iv) symptoms cause clinically significant impairment, (v) disturbances are not better explained by intellectual disability (APA 2013, pp. 49–50). As will become clear throughout this paper, the neuropsychiatrists under study tend to follow this symptom-based understanding of mental disorders. They are specifically interested in developing causal explanations of symptoms of mental disorders, rather than targeting mental disorders as a whole.
The promise of neuropsychiatry is (i) to offer an objective foundation grounding diagnostic processes, and (ii) to prescribe forms of clinical (pharmacological) treatment that specifically target the symptoms of a mental disorder. Accordingly, neurological activity is theoretically posited as an explanatory cause of symptoms of specific mental disorders, such that the observation of brain activity is treated as potentially simplifying the process of psychiatric diagnosis and treatment by revealing clear causal pathways that are constitutive of mental disorders (Insel and Cuthbert 2015).
Such expectations show that the technologically mediated way in which the complexity of the brain and the way it helps realizing specific forms of cognitive (dis)functioning does not occur in a vacuum, but is relative to existing knowledge of mental disorders, and neurobiological knowledge of brain functioning. It is against this background that the mediated complexity of the brain is integrated into the existing goals and aims of neuropsychiatrists. Accordingly, when brain imaging technologies present the brain as a complex organ, neuropsychiatrists are not simply confronted with a fait accompli. Rather, they need to develop new interpretative strategies and plans of action against the background from which they understand mental disorders. In the appropriation of the complexity of the brain, new ways open up to hypothesize how (symptoms of) mental disorders are realized and to develop experimental circumstances in which such hypotheses can be tested.
However, as Pickersgill (2011) has argued, there is no clear consensus in mental health research and practice about what mental disorders are and what is the best way to investigate them (cf. Rüppel and Voigt 2019). However, there is a clear consensus on another issue (hence the prefix “neuro-”): research into mental disorders should involve research into their neurological substrates, and experiments should be developed to make the link between cognitive functions and brain functions empirically testable (Cohn 2008; Fitzgerald 2014), even in the absence of direct clinical merit (Brosnan and Michael 2014). Building on these earlier studies, we intend to show in this paper that both in the ways in which neuropsychiatrists understand mental disorders and in their experimental designs, there seems to be a strong demand to ‘brain’ neuropsychiatric experiments. This practice of ‘braining’ requires the brain’s perceived complexity to be managed in light of the aim of neuropsychiatry, which is to reveal causal pathways that are constitutive of mental disorders. Thus, even though that the complexity of the brain as mediated through brain imaging technologies must be accounted for, it must be done in such a way that experimental set-ups allow for the development of causal explanations.
The management of complexity is of course not unique to the neurosciences. In the context of molecular biology, Rheinberger (1997) has argued that in the history of biology, crucial experiments typically developed parameters for simplification in order to be explanatory successful, while at the same time retaining the complexity of the research object (e.g., genes). Similarly, based on a critical reading of how pioneering synthetic biologists describe their work, Dan-Cohen (2016) points to the fact that many synthetic biologists were originally trained as computer scientists and electrical engineers, and largely ignored the biological complexity of life when developing models for designing and constructing novel organisms. These researchers proclaimed that a certain degree of ignorance of complexity was necessary for synthetic biology to develop as a field. Recently, in the context of neurocriminology, it has been shown that researchers orient to the neurological origins of allegedly criminal behavior at the expense of focusing on the complex social factors influencing it (Fallin et al. 2019). Based on an analysis of historical case studies or of written documents (scientific articles or autobiographical accounts of scientific work), these studies show that (neuro-)scientists need to manage complexity to make it a workable element within their research.
Our study aims to add to the body of literature that focuses on how complexity is managed in two ways. On the one hand, drawing from the perspective of technological mediation, we intend to augment existing social studies of neuroscience by focusing on how brain imaging technologies shape the objects that neuropsychiatrists study to become present as complex. This requires, on the other hand, to provide a detailed analysis of how scientists manage complexity in practice. To this purpose, we use a combination of ethnomethodology (EM) and conversation analysis (CA). We thereby study how technological mediations are appropriated and made fit into the interpretative frameworks that neuropsychiatrists use to understand mental disorders. Through these two additions we want to turn attention not only to the fact that managing complexity is an integral part of science, but also to how scientists do so in their research practices and the implications thereof.