N°87
-
2027/2
Computational psychiatry
Beaumont Sami, Vinckier Fabien
Call for papers
Special Issue of Intellectica journal on Computational Psychiatry
Since its emergence in the 2000s, stemming from a drive to renew theoretical perspectives on mental disorders, computational psychiatry has expanded rapidly, to the extent that the diversity of work it encompasses now makes it difficult to provide a single, unambiguous definition of the discipline. In the absence of an exhaustive review, it is worth examining certain distinctive features of computational approaches in psychiatry and illustrating their conceptual frameworks for mental disorders, their methods and their limitations. This is the focus of this special issue of the journal Intellectica.
Ever since it adopted, with the DSM-III in the early 1980s, a descriptive and agnostic nosography with regard to aetiology, psychiatry has remained in search of an explanatory framework capable of uncovering the mechanisms linking clinical manifestations to the underlying biological processes. Major advances in genetics and imaging have profoundly transformed our understanding of the pathophysiology of mental disorders, without, however, bringing about the hoped-for clinical revolution: in the absence of sufficiently robust and informative biomarkers at the individual level, diagnosis and the personalization of treatments continue to rely primarily on clinical and psychometric assessment.
This observation may have contributed to further widening the gap between clinical practice and basic scientific research, and, sometimes to a questioning of the project of biological psychiatry. Computational psychiatry has emerged within this paradigm, defined neither by a preferred level of analysis—genetic, neural, or behavioural—nor by a specific investigative method—imaging, experimental tasks, or questionnaires— but rather by the use of formal models to study psychiatric phenomena, with the goal of translating findings from neuroscience and experimental psychology into clinical practice.
This issue aims to explore the diversity of computational approaches in psychiatry, their contribution to our fundamental understanding of mental disorders, and the obstacles that still prevent the application of these findings in clinical practice. Contributions may fall into one or more of the following categories (non-exhaustive list):
1. Theoretical proposals concerning psychiatric syndromes and their neurobiological underpinnings
2. Contributions of computational phenotyping from a trans-nosographic perspective
3. Methodological issues specific to computational tools in psychiatry
4. Historical and epistemological perspectives on computational methods in psychiatry
Submission guidelines
Issue coordinated by Sami Beaumont (sami.beaumont@ghu-paris.fr) and Fabien Vinckier (f.vinckier@ghu-paris.fr)
- Articles in french or english
- Expected length : between 12 and 20 pages
- Complete instructions to authors: https://intellectica.org/fr/auteurs
- Deadline for submission: 31/03/2027
- Planned publication date: 31/12/2027
Special Issue of Intellectica journal on Computational Psychiatry
Since its emergence in the 2000s, stemming from a drive to renew theoretical perspectives on mental disorders, computational psychiatry has expanded rapidly, to the extent that the diversity of work it encompasses now makes it difficult to provide a single, unambiguous definition of the discipline. In the absence of an exhaustive review, it is worth examining certain distinctive features of computational approaches in psychiatry and illustrating their conceptual frameworks for mental disorders, their methods and their limitations. This is the focus of this special issue of the journal Intellectica.
Ever since it adopted, with the DSM-III in the early 1980s, a descriptive and agnostic nosography with regard to aetiology, psychiatry has remained in search of an explanatory framework capable of uncovering the mechanisms linking clinical manifestations to the underlying biological processes. Major advances in genetics and imaging have profoundly transformed our understanding of the pathophysiology of mental disorders, without, however, bringing about the hoped-for clinical revolution: in the absence of sufficiently robust and informative biomarkers at the individual level, diagnosis and the personalization of treatments continue to rely primarily on clinical and psychometric assessment.
This observation may have contributed to further widening the gap between clinical practice and basic scientific research, and, sometimes to a questioning of the project of biological psychiatry. Computational psychiatry has emerged within this paradigm, defined neither by a preferred level of analysis—genetic, neural, or behavioural—nor by a specific investigative method—imaging, experimental tasks, or questionnaires— but rather by the use of formal models to study psychiatric phenomena, with the goal of translating findings from neuroscience and experimental psychology into clinical practice.
This issue aims to explore the diversity of computational approaches in psychiatry, their contribution to our fundamental understanding of mental disorders, and the obstacles that still prevent the application of these findings in clinical practice. Contributions may fall into one or more of the following categories (non-exhaustive list):
1. Theoretical proposals concerning psychiatric syndromes and their neurobiological underpinnings
2. Contributions of computational phenotyping from a trans-nosographic perspective
3. Methodological issues specific to computational tools in psychiatry
4. Historical and epistemological perspectives on computational methods in psychiatry
Submission guidelines
Issue coordinated by Sami Beaumont (sami.beaumont@ghu-paris.fr) and Fabien Vinckier (f.vinckier@ghu-paris.fr)
- Articles in french or english
- Expected length : between 12 and 20 pages
- Complete instructions to authors: https://intellectica.org/fr/auteurs
- Deadline for submission: 31/03/2027
- Planned publication date: 31/12/2027