Heterogeneous appetite patterns in depression: computational modeling of nutritional interoception, reward processing, and decision-making
Accurate interoceptive processing in decision-making is essential to maintain homeostasis and overall health. Disruptions in this process have been associated with various psychiatric conditions, including depression. Recent studies have focused on nutrient homeostatic dysregulation in depression fo...
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Frontiers Media S.A.
2024-12-01
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| Series: | Frontiers in Human Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnhum.2024.1502508/full |
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| author | Yuuki Uchida Yuuki Uchida Takatoshi Hikida Manabu Honda Yuichi Yamashita |
| author_facet | Yuuki Uchida Yuuki Uchida Takatoshi Hikida Manabu Honda Yuichi Yamashita |
| author_sort | Yuuki Uchida |
| collection | DOAJ |
| description | Accurate interoceptive processing in decision-making is essential to maintain homeostasis and overall health. Disruptions in this process have been associated with various psychiatric conditions, including depression. Recent studies have focused on nutrient homeostatic dysregulation in depression for effective subtype classification and treatment. Neurophysiological studies have associated changes in appetite in depression with altered activation of the mesolimbic dopamine system and interoceptive regions, such as the insular cortex, suggesting that disruptions in reward processing and interoception drive changes in nutrient homeostasis and appetite. This study aimed to explore the potential of computational psychiatry in addressing these issues. Using a homeostatic reinforcement learning model formalizing the link between internal states and behavioral control, we investigated the mechanisms by which altered interoception affects homeostatic behavior and reward system activity via simulation experiments. Simulations of altered interoception demonstrated behaviors similar to those of depression subtypes, such as appetite dysregulation. Specifically, reduced interoception led to decreased reward system activity and increased punishment, mirroring the neuroimaging study findings of decreased appetite in depression. Conversely, increased interoception was associated with heightened reward activity and impaired goal-directed behavior, reflecting an increased appetite. Furthermore, effects of interoception manipulation were compared with traditional reinforcement learning parameters (e.g., inverse temperature β and delay discount γ), which represent cognitive-behavioral features of depression. The results suggest that disruptions in these parameters contribute to depressive symptoms by affecting the underlying homeostatic regulation. Overall, this study findings emphasize the importance of integrating interoception and homeostasis into decision-making frameworks to enhance subtype classification and facilitate the development of effective therapeutic strategies. |
| format | Article |
| id | doaj-art-e0c7aa5d6f504c14854eea0047ad5a28 |
| institution | OA Journals |
| issn | 1662-5161 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Human Neuroscience |
| spelling | doaj-art-e0c7aa5d6f504c14854eea0047ad5a282025-08-20T02:38:06ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612024-12-011810.3389/fnhum.2024.15025081502508Heterogeneous appetite patterns in depression: computational modeling of nutritional interoception, reward processing, and decision-makingYuuki Uchida0Yuuki Uchida1Takatoshi Hikida2Manabu Honda3Yuichi Yamashita4Department of Information Medicine, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, JapanGraduate School of Medical and Dental Sciences, Institute of Science Tokyo, Tokyo, JapanLaboratory for Advanced Brain Functions, Institute for Protein Research, Osaka University, Osaka, JapanDepartment of Information Medicine, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, JapanDepartment of Information Medicine, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, JapanAccurate interoceptive processing in decision-making is essential to maintain homeostasis and overall health. Disruptions in this process have been associated with various psychiatric conditions, including depression. Recent studies have focused on nutrient homeostatic dysregulation in depression for effective subtype classification and treatment. Neurophysiological studies have associated changes in appetite in depression with altered activation of the mesolimbic dopamine system and interoceptive regions, such as the insular cortex, suggesting that disruptions in reward processing and interoception drive changes in nutrient homeostasis and appetite. This study aimed to explore the potential of computational psychiatry in addressing these issues. Using a homeostatic reinforcement learning model formalizing the link between internal states and behavioral control, we investigated the mechanisms by which altered interoception affects homeostatic behavior and reward system activity via simulation experiments. Simulations of altered interoception demonstrated behaviors similar to those of depression subtypes, such as appetite dysregulation. Specifically, reduced interoception led to decreased reward system activity and increased punishment, mirroring the neuroimaging study findings of decreased appetite in depression. Conversely, increased interoception was associated with heightened reward activity and impaired goal-directed behavior, reflecting an increased appetite. Furthermore, effects of interoception manipulation were compared with traditional reinforcement learning parameters (e.g., inverse temperature β and delay discount γ), which represent cognitive-behavioral features of depression. The results suggest that disruptions in these parameters contribute to depressive symptoms by affecting the underlying homeostatic regulation. Overall, this study findings emphasize the importance of integrating interoception and homeostasis into decision-making frameworks to enhance subtype classification and facilitate the development of effective therapeutic strategies.https://www.frontiersin.org/articles/10.3389/fnhum.2024.1502508/fullappetitecomputational neurosciencecomputational psychiatrydecision-makingdopaminehomeostasis |
| spellingShingle | Yuuki Uchida Yuuki Uchida Takatoshi Hikida Manabu Honda Yuichi Yamashita Heterogeneous appetite patterns in depression: computational modeling of nutritional interoception, reward processing, and decision-making Frontiers in Human Neuroscience appetite computational neuroscience computational psychiatry decision-making dopamine homeostasis |
| title | Heterogeneous appetite patterns in depression: computational modeling of nutritional interoception, reward processing, and decision-making |
| title_full | Heterogeneous appetite patterns in depression: computational modeling of nutritional interoception, reward processing, and decision-making |
| title_fullStr | Heterogeneous appetite patterns in depression: computational modeling of nutritional interoception, reward processing, and decision-making |
| title_full_unstemmed | Heterogeneous appetite patterns in depression: computational modeling of nutritional interoception, reward processing, and decision-making |
| title_short | Heterogeneous appetite patterns in depression: computational modeling of nutritional interoception, reward processing, and decision-making |
| title_sort | heterogeneous appetite patterns in depression computational modeling of nutritional interoception reward processing and decision making |
| topic | appetite computational neuroscience computational psychiatry decision-making dopamine homeostasis |
| url | https://www.frontiersin.org/articles/10.3389/fnhum.2024.1502508/full |
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