Yamamori, Yumeya;
Robinson, Oliver J;
(2024)
Thinking computationally in translational psychiatry. A commentary on Neville et al. (2024).
Cognitive, Affective, & Behavioral Neuroscience
10.3758/s13415-024-01172-1.
(In press).
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Abstract
There is a growing focus on the computational aspects of psychiatric disorders in humans. This idea also is gaining traction in nonhuman animal studies. Commenting on a new comprehensive overview of the benefits of applying this approach in translational research by Neville et al. (Cognitive Affective & Behavioral Neuroscience 1-14, 2024), we discuss the implications for translational model validity within this framework. We argue that thinking computationally in translational psychiatry calls for a change in the way that we evaluate animal models of human psychiatric processes, with a shift in focus towards symptom-producing computations rather than the symptoms themselves. Further, in line with Neville et al.'s adoption of the reinforcement learning framework to model animal behaviour, we illustrate how this approach can be applied beyond simple decision-making paradigms to model more naturalistic behaviours.
| Type: | Article |
|---|---|
| Title: | Thinking computationally in translational psychiatry. A commentary on Neville et al. (2024) |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3758/s13415-024-01172-1 |
| Publisher version: | http://dx.doi.org/10.3758/s13415-024-01172-1 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | Computational, Psychiatry, Reinforcement learning, Translational, Validity |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Institute of Cognitive Neuroscience |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10188888 |
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