Recent work on epistemic integration in the life sciences has emphasized the importance of integration in thinking about explanatory practice in science, particularly for articulating a robust alternative to reductionism and anti-reductionism. This paper analyzes the role of models in balancing the relative contributions of lower- and higher-level epistemic resources involved in this process. Integration between multiple disciplines proceeds by constructing a problem agenda (Love, Philos Sci 75(5): 874–886, 2008), a set of interrelated problems that structures the problem space of a complex phenomenon that is investigated by many disciplines. The usage of models, it is argued, mark changes in a phenomenon’s problem agenda depending on the task that is expected of it. Particularly, it emphasizes the sensitivity of a problem agenda to changing attitudes in the solutions to the conceptual and empirical items constituting that agenda. The analysis will proceed by means of a case study, the Reichardt motion detector, a model that has been vital to the methodological and conceptual development of research on motion detection, especially in invertebrates. As will be seen, the history of the Reichardt model will exemplify the dynamic changes that occur in the interdisciplinary negotiations that comprise the active efforts of various sciences working to integrate their resources.
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Other epistemic products also serve as the basis for discussion on integration, including interfield theories (Darden and Maull 1977), and even entire disciplines like cell biology (Bechtel 1986). The variety of different epistemic products that may be emphasized in the analysis of integration underscores the broadness of the issue at stake here, and the need to clarify the scope of the particular enterprise that the respective philosophers take to be integrative.
Carl Craver and Lindley Darden's recent (2013) book In Search of Mechanisms is a welcome step in the direction of accommodating an element of open-endedness into the philosophy of explanation in the life sciences.
In particular, similar figures have been compiled from human psychophysical experiments (Clifford and Langley 1996). These experiments incorporate drastically different variables and methods, however, than those represented in Fig. 2. The objects of study in Clifford and Langley’s investigation are human individuals, who verbally reported changes in their perception of motion, rather than electrode-mediated measurements of single neurons in the brain.
Constituent to this computationalist vision was a commitment to “abstraction”, rather than integration. That is, in order for the computationalist attitude to be implemented, a conscious move towards ignoring the details of other disciplinary contributions to describing and explaining the phenomenon is required. The tension between these concurrent commitments to, respectively, abstraction and integration is an interesting issue that must be held for a later time. For now, it is sufficient to see this computationalist phase constituting both (a) the “computationalist attitude”, whereby abstraction is methodological tool, and (b) the “computationalist vision” meant to hold for all of (cognitive) neuroscience. Thanks to the editor for bringing this point to my attention.
There is a growing interest among researchers to control for how exactly they apply the term “realistic” to their work. Experiments that use artificial settings can make experiments using, i.a., flight simulators, problematic due to their emphasis on “user-defined” parameters used to investigate the phenomenon of interest. (Martin Egelhaaf, personal communication) For this reason, contemporary experiments on visual motion phenomena (including adaptation) work to emphasize more “natural” conditions using whole, unrestrained organisms, which seek to avoid introducing experimental artifacts into the study of the phenomenon.
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I would like to thank Rebecca Mertens, Staffan Müller-Wille, and two anonymous reviewers for their very helpful feedback and suggestions.
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Brooks, D.S. The role of models in the process of epistemic integration: the case of the Reichardt motion detector. HPLS 36, 90–113 (2014). https://doi.org/10.1007/s40656-014-0006-1
- Werner Reichardt
- Correlator model
- Motion detection