The Algorithmic Agent Perspective and Computational Neuropsychiatry: From Etiology to Advanced Therapy in Major Depressive Disorder
Giulio Ruffini, Francesca Castaldo, Edmundo Lopez-Sola, Roser Sanchez-Todo, Jakub Vohryzek
Entropy November 6, 2024 DOI: 10.3390/e26110953 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Topics | Depression |
| Keywords | Neuropsychiatry Perspective graphical Etiology Psychotherapist Artificial intelligence Cognition |
| Citations | 10 |
| Key points | Proposes that depression can be modeled as a state of persistently low affective valence arising from factors such as inaccurate world models, dysfunctional objective functions, deficient planning, or unfavorable environments. |
Abstract
Major Depressive Disorder (MDD) is a complex, heterogeneous condition affecting millions worldwide. Computational neuropsychiatry offers potential breakthroughs through the mechanistic modeling of this disorder. Using the Kolmogorov theory (KT) of consciousness, we developed a foundational model where algorithmic agents interact with the world to maximize an Objective Function evaluating affective valence. Depression, defined in this context by a state of persistently low valence, may arise from various factors-including inaccurate world models (cognitive biases), a dysfunctional Objective Function (anhedonia, anxiety), deficient planning (executive deficits), or unfavorable environments. Integrating algorithmic, dynamical systems, and neurobiological concepts, we map the agent model to brain circuits and functional networks, framing potential etiological routes and linking with depression biotypes. Finally, we explore how brain stimulation, psychotherapy, and plasticity-enhancing compounds such as psychedelics can synergistically repair neural circuits and optimize therapies using personalized computational models.
Comparable studies
Other theoretical and historical papers on depression, most cited first.
| Study | Year | Design | Participants |
|---|---|---|---|
| Mindfulness-based cognitive therapy for depression | 2006 | Theoretical or philosophical paper | |
| Psilocybin-assisted therapy of major depressive disorder using Acceptance and Commitment Therapy as a therapeutic frame | 2020 | Theoretical or philosophical paper | |
| The Yale Manual for Psilocybin-Assisted Therapy of Depression (using Acceptance and Commitment Therapy as a Therapeutic Frame) | 2020 | Theoretical or philosophical paper | |
| Neuroinflammation and neuroprogression in depression: Effects of alternative drug treatments | 2022 | Theoretical or philosophical paper | |
| Improving cognitive functioning in major depressive disorder with psychedelics: A dimensional approach | 2021 | Theoretical or philosophical paper |
Citations in the library
Cited by 2
- Perturbing whole‐brain models of brain hierarchy: An application for depression following pharmacological treatment Annals of the New York Academy of Sciences July 21, 2025
- Novel and emerging anesthetic drugs for the treatments of major depression: a comprehensive review of efficacy, mechanism, and outlook. Frontiers in Psychiatry 2025
Cites 43
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- Neural correlates of the psychedelic state as determined by fMRI studies with psilocybin Proceedings of the National Academy of Sciences January 23, 2012
- REBUS and the Anarchic Brain: Toward a Unified Model of the Brain Action of Psychedelics Pharmacological Reviews June 20, 2019
- The salience network is responsible for switching between the default mode network and the central executive network: Replication from DCM Neuroimage May 24, 2014
- Are the Neural Correlates of Consciousness in the Front or in the Back of the Cerebral Cortex? Clinical and Neuroimaging Evidence Journal of Neuroscience October 4, 2017
and 38 more in the library