Computational brain models use machine learning algorithms and statistical models to harness big data for delivering disease-specific diagnosis or prognosis for individuals. They are intended to support clinical decision making and are widely available. However, their translation into clinical practice remains weak despite efforts to improve implementation such as through training clinicians and clinical staff in their use and benefits. In this paper, we argue that it is necessary to go beyond existing implementation efforts to understand and meaningfully integrate the clinician's perspective and tacit knowledge for This is an Accepted Manuscript of an article published by Taylor & Francis in Interdisciplinary Science Reviews 2 translating computational brain models in neurological practice. The empirical research draws on our collective seven-year engagement with the Human Brain Project as researchers of its 'Ethics and Society' subproject and includes analysis of published and grey literature, participant observation at workshops and conferences, and interviews with data scientists, neuroscientists, and neurologists in the UK and Europe developing computational tools for neurology.Our findings show that building trust in the relationships between clinicians and researchers (modelers, data scientists) through meaningful upstream collaboration, greater model transparency and integration of tacit knowledge play a salient role in translation processes with meaningful benefit for patients.

The Human Brain Project (HBP) was launched in October 2013 by the European Commission to build an information and communication technology infrastructure that would support large-scale brain modelling and simulation. Less than a year after its launch, more than 800 neuroscientists signed a letter that claimed the HBP ‘would fail to meet its goals’. Based on multi-sited ethnographic fieldwork conducted between February 2014 and January 2017 in France, Germany, the United Kingdom and the HBP headquarters in Switzerland, and over 40 interviews with scientists, engineers and project administrators, this article traces how competing visions over how brain models should be built became tied into debates over how scientific communities should be governed. Articulations of these different kinds of models and communities appealed to competing imaginaries of Europe itself – of Europe and European science as unified or pluralistic. This article argues that scientific models are sites of contestation over social and political futures. The tensions between visions of scientific unification and pluralism in the HBP mirrored the tensions between imaginaries of European political unification and pluralism.

This paper reviews ethnographies of neuroscience laboratories in the United States and Europe, organizing them into three main sections: (1) descriptions of the capabilities and limitations of technologies used in neuroimaging laboratories to map “activity” or “function” onto structural models of the brain; (2) discussions of the “distributed” or “extended” mind in neuroscience practice; and (3) the implications of neuroscience research and the power of brain images outside the laboratory. I will try to show the importance of ethnographic work in such settings, and place this body of ethnographic work within its historical framework—such ethnographies largely emerged within the Decade of the Brain, as announced by former President of the United States George H. W. Bush in 1990. The main argument is that neuroscience research and the context within which it is taking place has changed since the 1990’s—specifically with the launch of “big science” projects such as the Human Brain Project (HBP) in the European Union and the BRAIN initiative in the United States. There is an opportunity for more research into the institutional and politico-economic context within which neuroscience research is taking place, and for continued engagement between the social and biological sciences.

This article draws on long-term engagement with the Human Brain Project (HBP), one of the Future and Emerging Technology Flagship Initiatives funded by the European Commission to address EU “grand challenges” of understanding the human brain and applying these insights to brain-inspired technology development. Based on participant observation and interviews with researchers and project administrators, our findings suggest that the formal infrastructure built to facilitate and structure collaboration within large-scale interdisciplinary research projects can be in tension with the ways researchers collaborate. While much of the literature on infrastructure focuses on top-down, formal infrastructural design, we also pay attention to the informal, bottom-up infrastructural assemblage involved in large-scale interdisciplinary collaborations. This brings into question how scientists and science funders navigate the tensions and interactions between formal and informal infrastructure, rendering certain kinds of collaboration and knowledge (in)visible.

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