URN zum Zitieren der Version auf EPub Bayreuth: urn:nbn:de:bvb:703-epub-6981-5
Titelangaben
Kästner, Lena:
Modeling psychopathology : 4D multiplexes to the rescue.
In: Synthese.
Bd. 201
(2022)
Heft 1
.
- No. 9.
ISSN 1573-0964
DOI der Verlagsversion: https://doi.org/10.1007/s11229-022-04008-y
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Deutsche Forschungsgemeinschaft VolkswagenStiftung |
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Abstract
Accounts of mental disorders focusing either on the brain as neurophysiological substrate or on systematic connections between symptoms are insufficient to account for the multifactorial nature of mental illnesses. Recently, multiplexes have been suggested to provide a holistic view of psychopathology that integrates data from different factors, at different scales, or across time. Intuitively, these multi-layered network structures present quite appealing models of mental disorders that can be constructed by powerful computational machinery based on increasing amounts of real-world data. In this paper, I systematically examine what challenges psychopathology models face and to what extent different species of psychopathology models can address them. My analysis highlights that while multiplexes, as they are usually conceived, appear promising, they suffer from the same problems as other approaches. To remedy this, I suggest, we must go a step further and combine different kinds of multiplexes into 4D models. Once we embrace 4D multiplexes and identify appropriate ways to constrain them, we might unlock the true potential of multiplexes for making headway in psychopathology research.
Weitere Angaben
Publikationsform: | Artikel in einer Zeitschrift |
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Keywords: | Mental illness; Mental disorder; Multiplex; Symptom network model; Connectivity; Temporal dynamics; Multifactorial model |
Themengebiete aus DDC: | 100 Philosophie und Psychologie |
Institutionen der Universität: | Fakultäten > Kulturwissenschaftliche Fakultät Fakultäten |
Sprache: | Englisch |
Titel an der UBT entstanden: | Ja |
URN: | urn:nbn:de:bvb:703-epub-6981-5 |
Eingestellt am: | 09 Mai 2023 08:52 |
Letzte Änderung: | 09 Mai 2023 08:53 |
URI: | https://epub.uni-bayreuth.de/id/eprint/6981 |