On the Role of Theory and Modeling in Neuroscience

Abstract

In recent years, the field of neuroscience has gone through rapid experimental advances and a significant increase in the use of quantitative and computational methods. This growth has created a need for clearer analyses of the theory and modeling approaches used in the field. This issue is particularly complex in neuroscience because the field studies phenomena that cross a wide range of scales and often require consideration at varying degrees of abstraction, from precise biophysical interactions to the computations they implement. We argue that a pragmatic perspective of science, in which descriptive, mechanistic, and normative models and theories each play a distinct role in defining and bridging levels of abstraction, will facilitate neuroscientific practice. This analysis leads to methodological suggestions, including selecting a level of abstraction that is appropriate for a given problem, identifying transfer functions to connect models and data, and the use of models themselves as a form of experiment.

Figure 1.

The three explanatory processes that underlie scientific explanations. Descriptive theories address the question of “what is the phenomenon?” and identify the repeatable characteristics of that phenomenon. Mechanistic theories address the question of “how does the phenomenon arise?” and explains the phenomenon in terms of the parts and interactions of other phenomena at lower levels of abstraction. Normative theories address the question of “why do the phenomena exist?” and allow a comparison of the phenomenon to an identified function or goal. Normative theories allow the determination of whether a process is achieving its goal; inadequacies generally imply an incomplete understanding of the limitations engendered by processes at a lower level of abstraction.

Figure 2.

Interactions between three explanatory processes and levels of abstraction. Descriptive explanations define an idealized abstraction of specific aspects of a phenomenon for discussion, measurement, and repeatability. Mechanistic explanations account for properties of a phenomenon by their emergence from less abstract phenomena, while normative explanations account for those properties by appealing to their ability to perform more abstract goals.

Figure 3.

How the various components discussed in this manuscript interact. The domain of a theory is the set of phenomena which it purports to explain. Theories are instantiated in models, which are an abstraction of phenomena in the domain, as specified by a translation function. By constraining the form solutions can take, a conceptual framework defines a way of looking at a problem, within which models and theories can be proposed. A given model can instantiate more than one theory, and a theory can be instantiated by more than one model.