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Families of network structures – we need both phenomenal and explanatory models

Published online by Cambridge University Press:  06 March 2019

Tony Ward  and
Ronald Fischer
Tony Ward
Affiliation:
School of Psychology, Victoria University of Wellington, PO Box 600, Wellington, New Zealand. [email protected]@vuw.ac.nzhttps://mindcultureevolution.com/
Ronald Fischer
Affiliation:
School of Psychology, Victoria University of Wellington, PO Box 600, Wellington, New Zealand. [email protected]@vuw.ac.nzhttps://mindcultureevolution.com/
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Abstract

Symptom network models (SNWMs) play an important role in identifying but not explaining patterns of symptoms. We discuss underlying assumptions of SNWMs and argue that they represent phenomenal models, best suited to detecting patterns among symptoms. SNWMs need to be supplemented with mechanistic models that provide constitutive and etiological explanations of each symptom (network nodes) once relevant patterns have been identified.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 42 , 2019 , e31
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Copyright
Copyright © Cambridge University Press 2019 

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References

Beck, A. T. & Bredemeier, K. (2016) A unified model of depression: Integrating clinical, cognitive, biological, and evolutionary perspectives. Clinical Psychological Science 4(4):596–619. Available at: https://doi.org/10.1177/2167702616628523.Google Scholar
Craver, C. & Kaplan, D. M. (in press) Are more details better? On the norms of completeness for mechanistic explanations. Philosophy of Science. Available at: https://doi.org/10.1093/bjps/axy015.Google Scholar
Eliasmith, C. (2013) How to build a brain: A neural architecture for biological cognition. Oxford University Press.Google Scholar
Hochstein, E. (2016) One mechanism, many models: A distributed theory of mechanistic explanation. Synthese 193:1387–407. Available at: https://doi.org/10.1007/s11229-015-08.Google Scholar