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Title: Integrating Model-Based Approaches Into a Neuroscience Curriculum—An Interdisciplinary Neuroscience Course in Engineering
Award ID(s):
1659831
NSF-PAR ID:
10176934
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
IEEE Transactions on Education
Volume:
62
Issue:
1
ISSN:
0018-9359
Page Range / eLocation ID:
48 to 56
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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  1. 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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