Complexity theory of psychopathology

There is a renewed interest for complex adaptive system approaches that can account for the inherently complex and dynamic nature of psychopathology. Yet a theory of psychopathology grounded in the principles of complex adaptive systems is lacking. Here, we present such a theory based on the notion of dynamic patterns: patterns that are formed over time. We propose that psychopathology can be understood as a dynamic pattern that emerges from self-organized interactions between interdependent biopsychosocial processes in a complex adaptive system comprising a person in their environment. Psychopathology is emergent in the sense that it refers to the person-environment system as a whole and cannot be reduced to specific system parts. Psychopathology as a dynamic pattern is also self-organized, meaning that it arises solely from the interdependencies in the system: the interactions between countless biopsychosocial variables. All possible manifestations of psychopathology will correspond to a wide variety of dynamic patterns. Yet we propose that the development of these patterns over time can be described by general principles of pattern formation in complex adaptive systems. A discussion of implications for classification, intervention, and public health concludes the article. (PsycInfo Database Record (c) 2023 APA, all rights reserved).</p

Corrigendum:Studying Brains. What could neurometaphysics be to NeurotechEU?

Frontiers in Neuroscience, (2023), 17, (1155547), 10.3389/fnins.2023.1155547In the published article, there was an error in the article title. Instead of “Studying brains what could neurometaphysics be to NeurotechEU?” it should be “Studying Brains. What could neurometaphysics be to NeurotechEU?” The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.</p

Corrigendum:Studying Brains. What could neurometaphysics be to NeurotechEU?

Frontiers in Neuroscience, (2023), 17, (1155547), 10.3389/fnins.2023.1155547In the published article, there was an error in the article title. Instead of “Studying brains what could neurometaphysics be to NeurotechEU?” it should be “Studying Brains. What could neurometaphysics be to NeurotechEU?” The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.</p

Studying Brains. What could neurometaphysics be to NeurotechEU?

NeurotechEU has introduced a new conceptual hierarchy for neuroscientific research and its applications along 8 different core research areas, including the so-called ‘neurometaphysics’. This paper explores this concept of neurometaphysics, its topics and its potential approach. It warns against an endemic Cartesianism in (neuro)science that somehow seems to survive explicit refutations by implicitly persisting in our conceptual scheme. Two consequences of this persisting Cartesian legacy are discussed; the isolated brain assumption and the idea that activity requires identifiable neural ‘decisions’. Neuropragmatism is introduced as offering the promise of progress in neurometaphysics, by emphasizing that (1) studying brains interact organically with their environment and (2) studying brains requires an attitude of continuous learning

Studying brains what could neurometaphysics be to NeurotechEU?

NeurotechEU has introduced a new conceptual hierarchy for neuroscientific research and its applications along 8 different core research areas, including the so-called ‘neurometaphysics’. This paper explores this concept of neurometaphysics, its topics and its potential approach. It warns against an endemic Cartesianism in (neuro)science that somehow seems to survive explicit refutations by implicitly persisting in our conceptual scheme. Two consequences of this persisting Cartesian legacy are discussed; the isolated brain assumption and the idea that activity requires identifiable neural ‘decisions’. Neuropragmatism is introduced as offering the promise of progress in neurometaphysics, by emphasizing that (1) studying brains interact organically with their environment and (2) studying brains requires an attitude of continuous learning.</p

Psychology's Theory Crisis, and Why Formal Modelling Cannot Solve It

In light of psychology’s ‘theory crisis’, multiple authors have argued that adopting formalization and/or formal modelling would constitute a useful or even necessary step towards stronger psychological theory. In this article, I instead argue that formal modelling cannot solve the core problem the psychological ‘theory crisis’ refers to, which are the currently high degrees of contrastive and holistic underdetermination of our theories by our data. I do so by first introducing underdetermination as an explanatory framework for determining the evidential import of research findings for theories, and showing how both broader theoretical considerations and informal assumptions are key to this process. Then, I derive the aforementioned core problem from the current ‘theory crisis’ literature and tentatively explore its possible solutions. Lastly, I show that formal modelling is neither a necessary nor sufficient solution for either contrastive or holistic underdetermination, and that its uncritical adoption might instead worsen the crisis

Measuring social constructions? On the meaningful difference between indexing and measurement

Many psychological constructs of interest are fuzzy, and are ultimately social constructions. However, how social constructions relate to measurement models - how they should be meas-ured, and if they’re measurable in the first place - is a big open question in the philosophy of psychometrics. In this article, we propose a meaningful distinction between measurement and indexing by discussing the role of causality versus constitutive relations. We also discuss how social constructions can be handled, and tackle other issues in ontology and causality

Idiographic personality networks:Stability, variability and when they become problematic

Idiographic personality networks are gaining popularity for modeling individual differences, but their validity requires stability, which seems contradicted by theory and empirics. This study employs conventional idiographic network analysis to evaluate inter- and intra-individual variation in youngsters with a mild intellectual disability (N = 26; Mage = 23) who completed 60 daily self-reports. Results show high between-person heterogeneity in network structures, even within subgroups with a similar personality profile. Repeatedly estimating idiographic networks in a sliding 30-day window revealed within-person network variability throughout the 60 days. Both theory and our study suggest non-stationarity, which invalidates aggregated network estimates. This is problematic because capturing individuals’ stable personality networks is required to subsequently assess individual differences. We discuss implications for modeling and theory building.</p

Idiographic personality networks: stability, variability and when they become problematic

Idiographic personality networks are gaining popularity for modeling individual differences. Their validity requires stability, which seems contradicted by theory and empirics. This study employs conventional idiographic personality network analysis to evaluate inter- and intra-individual variation in youngsters with a mild intellectual disability (N = 26; Mage=23) who completed 60 daily self-reports. Results show high between-person heterogeneity in network structures, even within subgroups with a similar personality profile. Repeatedly estimating idiographic networks in a sliding 30-day window revealed within-person network variability throughout the 60 days. Both theory and our study suggest non-stationarity, which invalidates aggregated network estimates. This is problematic because capturing individuals’ stable personality networks is required to subsequently assess individual differences. We discuss implications for modeling and theory building

Idiographic Personality Network Modeling

R codes related to analyses for https://doi.org/10.31234/osf.io/xf65q can be found here on the OSF. The data are available on request from https://doi.org/10.17026/dans-z92-yv4x - If you want to replicate main analyses of the findings on between- and within-persons heterogeneity in idiographic networks, you can use pre-processed dataset 'df_networks_imputed.csv'. The 'Script_Revised_Idiographic_network_analyses.html' or 'R_Script_Revision_network_analyses.R' should enable replication of these main findings. - Replicating the imputation or attribution of SURPS profiles is possible with corresponding datafiles on DANS and with 'Data_preparation.html'