Degeneracy and stability in neural circuits of dopamine and serotonin neuromodulators: A theoretical consideration
Degenerate neural circuits perform the same function despite being structurally different. However, it is unclear whether neural circuits with interacting neuromodulator sources can themselves degenerate while maintaining the same neuromodulatory function. Here, we address this by computationally mo...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-01-01
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| Series: | Frontiers in Computational Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fncom.2022.950489/full |
| _version_ | 1828054596046553088 |
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| author | Chandan K. Behera Alok Joshi Da-Hui Wang Da-Hui Wang Trevor Sharp KongFatt Wong-Lin |
| author_facet | Chandan K. Behera Alok Joshi Da-Hui Wang Da-Hui Wang Trevor Sharp KongFatt Wong-Lin |
| author_sort | Chandan K. Behera |
| collection | DOAJ |
| description | Degenerate neural circuits perform the same function despite being structurally different. However, it is unclear whether neural circuits with interacting neuromodulator sources can themselves degenerate while maintaining the same neuromodulatory function. Here, we address this by computationally modeling the neural circuits of neuromodulators serotonin and dopamine, local glutamatergic and GABAergic interneurons, and their possible interactions, under reward/punishment-based conditioning tasks. The neural modeling is constrained by relevant experimental studies of the VTA or DRN system using, e.g., electrophysiology, optogenetics, and voltammetry. We first show that a single parsimonious, sparsely connected neural circuit model can recapitulate several separate experimental findings that indicated diverse, heterogeneous, distributed, and mixed DRNVTA neuronal signaling in reward and punishment tasks. The inability of this model to recapitulate all observed neuronal signaling suggests potentially multiple circuits acting in parallel. Then using computational simulations and dynamical systems analysis, we demonstrate that several different stable circuit architectures can produce the same observed network activity profile, hence demonstrating degeneracy. Due to the extensive D2-mediated connections in the investigated circuits, we simulate the D2 receptor agonist by increasing the connection strengths emanating from the VTA DA neurons. We found that the simulated D2 agonist can distinguish among sub-groups of the degenerate neural circuits based on substantial deviations in specific neural populations’ activities in reward and punishment conditions. This forms a testable model prediction using pharmacological means. Overall, this theoretical work suggests the plausibility of degeneracy within neuromodulator circuitry and has important implications for the stable and robust maintenance of neuromodulatory functions. |
| first_indexed | 2024-04-10T20:26:13Z |
| format | Article |
| id | doaj.art-3b552f5ca36c435c8a04adf1a30c2239 |
| institution | Directory Open Access Journal |
| issn | 1662-5188 |
| language | English |
| last_indexed | 2024-04-10T20:26:13Z |
| publishDate | 2023-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Computational Neuroscience |
| spelling | doaj.art-3b552f5ca36c435c8a04adf1a30c22392023-01-25T10:16:56ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882023-01-011610.3389/fncom.2022.950489950489Degeneracy and stability in neural circuits of dopamine and serotonin neuromodulators: A theoretical considerationChandan K. Behera0Alok Joshi1Da-Hui Wang2Da-Hui Wang3Trevor Sharp4KongFatt Wong-Lin5Intelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Derry∼Londonderry, United KingdomIntelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Derry∼Londonderry, United KingdomState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, ChinaSchool of Systems Science, Beijing Normal University, Beijing, ChinaDepartment of Pharmacology, University of Oxford, Oxford, United KingdomIntelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Derry∼Londonderry, United KingdomDegenerate neural circuits perform the same function despite being structurally different. However, it is unclear whether neural circuits with interacting neuromodulator sources can themselves degenerate while maintaining the same neuromodulatory function. Here, we address this by computationally modeling the neural circuits of neuromodulators serotonin and dopamine, local glutamatergic and GABAergic interneurons, and their possible interactions, under reward/punishment-based conditioning tasks. The neural modeling is constrained by relevant experimental studies of the VTA or DRN system using, e.g., electrophysiology, optogenetics, and voltammetry. We first show that a single parsimonious, sparsely connected neural circuit model can recapitulate several separate experimental findings that indicated diverse, heterogeneous, distributed, and mixed DRNVTA neuronal signaling in reward and punishment tasks. The inability of this model to recapitulate all observed neuronal signaling suggests potentially multiple circuits acting in parallel. Then using computational simulations and dynamical systems analysis, we demonstrate that several different stable circuit architectures can produce the same observed network activity profile, hence demonstrating degeneracy. Due to the extensive D2-mediated connections in the investigated circuits, we simulate the D2 receptor agonist by increasing the connection strengths emanating from the VTA DA neurons. We found that the simulated D2 agonist can distinguish among sub-groups of the degenerate neural circuits based on substantial deviations in specific neural populations’ activities in reward and punishment conditions. This forms a testable model prediction using pharmacological means. Overall, this theoretical work suggests the plausibility of degeneracy within neuromodulator circuitry and has important implications for the stable and robust maintenance of neuromodulatory functions.https://www.frontiersin.org/articles/10.3389/fncom.2022.950489/fulldegeneracycomputational modelingserotonindopaminereward and punishment |
| spellingShingle | Chandan K. Behera Alok Joshi Da-Hui Wang Da-Hui Wang Trevor Sharp KongFatt Wong-Lin Degeneracy and stability in neural circuits of dopamine and serotonin neuromodulators: A theoretical consideration Frontiers in Computational Neuroscience degeneracy computational modeling serotonin dopamine reward and punishment |
| title | Degeneracy and stability in neural circuits of dopamine and serotonin neuromodulators: A theoretical consideration |
| title_full | Degeneracy and stability in neural circuits of dopamine and serotonin neuromodulators: A theoretical consideration |
| title_fullStr | Degeneracy and stability in neural circuits of dopamine and serotonin neuromodulators: A theoretical consideration |
| title_full_unstemmed | Degeneracy and stability in neural circuits of dopamine and serotonin neuromodulators: A theoretical consideration |
| title_short | Degeneracy and stability in neural circuits of dopamine and serotonin neuromodulators: A theoretical consideration |
| title_sort | degeneracy and stability in neural circuits of dopamine and serotonin neuromodulators a theoretical consideration |
| topic | degeneracy computational modeling serotonin dopamine reward and punishment |
| url | https://www.frontiersin.org/articles/10.3389/fncom.2022.950489/full |
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