On the Role of Theory and Modeling in Neuroscience

Medientyp: E-Artikel

Titel: On the Role of Theory and Modeling in Neuroscience

Beteiligte: Levenstein, Daniel; Alvarez, Veronica A.; Amarasingham, Asohan; Azab, Habiba; Chen, Zhe S.; Gerkin, Richard C.; Hasenstaub, Andrea; Iyer, Ramakrishnan; Jolivet, Renaud B.; Marzen, Sarah; Monaco, Joseph D.; Prinz, Astrid A.; Quraishi, Salma; Santamaria, Fidel; Shivkumar, Sabyasachi; Singh, Matthew F.; Traub, Roger; Nadim, Farzan; Rotstein, Horacio G.; Redish, A. David

Erschienen: Society for Neuroscience, 2023

Sprache: Englisch

DOI: 10.1523/jneurosci.1179-22.2022

ISSN: 0270-6474; 1529-2401

Schlagwörter: General Neuroscience

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Beschreibung: 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.

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