Dynamical Models and Explanation in Neuroscience

Abstract

Kaplan and Craver claim that all explanations in neuroscience appeal to mechanisms. They extend this view to the use of mathematical models in neuroscience and propose a constraint such models must meet in order to be explanatory. I analyze a mathematical model used to provide explanations in dynamical systems neuroscience and indicate how this explanation cannot be accommodated by the mechanist framework. I argue that this explanation is well characterized by Batterman's account of minimal model explanations and that it demonstrates how relationships between explanatory models in neuroscience and the systems they represent is more complex than has been appreciated.

One mechanism, many models: a distributed theory of mechanistic explanation

“…Despite its many advocates however, no clear consensus exists regarding what sorts of scientific models provide mechanistic explanations, or even what exactly a model must do in order to provide such explanations. This lack of consensus has resulted in disagreements regarding whether or not we should interpret certain kinds of scientific models, such as computational models, dynamical models, and topological models, as providing mechanistic explanations (see, for example : Piccinini 2006: Piccinini , 2015Rusanen & Lappi 2007;Eliasmith 2010;Huneman 2010;Milkowski 2011Milkowski , 2013Zednik 2011;Kaplan & Craver 2011;Jones 2014;Chirimuuta 2014;Ross 2015).…”

“…These models frequently attempt to characterize the dynamics of complex systems without consideration as to their underlying physical implementation (see : Thelen & Smith 1994;Van Gelder & Port 1995;Chemero & Silberstein 2008;Walmsley 2008). This has resulted in some claiming that such models fail to provide mechanistic explanations (Eliasmith 2010;Stepp, Chemero & Turvey 2011;Ross 2015). Despite this fact, such models can often play an important role in helping to discover the underlying mechanisms of a system, and are often the first step in fleshing out more detailed mechanistic accounts.…”

Why one model is never enough: a defense of explanatory holism

“…In doing so, our model would be able to satisfy both goals (4) and (5), but by adding additional parameters to our model we complicate it further and in doing so sacrifice our ability to effectively understand the phenomenon. In fact, the very reason that the Fitzhugh-Nagumo model simplifies away many of the details of the Hodgkin-Huxley model (which was itself already an abstract description of the action potential that did not identify its underlying causal mechanisms) was because such simplifications were essential to provide an understanding of the relevant behavioural regularities and patterns (Fitzhugh 1960;Ross 2015). Fitzhugh himself justified the simplifying assumptions of the model on the grounds that such simplifications lead "to a better understanding of the complete system than can be obtained by considering all the variables at once" (Fitzhugh 1960, p.873).…”

“…In other words, it satisfies explanatory goal (3). Yet, the main reason why this goal is considered explanatory in the study of the action potential is because, by identifying the dynamic principles that guide the system, we are able to gain a better understanding of its overall behaviour than can be gained from models which include additional mechanistic details (Fitzhugh 1960;Ross 2015). Thus, the explanatory justification for satisfying goal (3) is that it is the most effective way to help us satisfy goal (1).…”

Beyond bioethics: the 5th International Philosophy of Medicine Roundtable

“…We believe, however, that the papers published in this issue well represent both the quality and range of the papers that were presented. Other papers from the roundtable have been published or are forthcoming in the Journal of Medicine and Philosophy [11], Philosophy of Science, [12] and Journal of Evaluation in Clinical Practice [13].…”