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Systematic Input–Output Mapping Reveals Structural Plasticity of VTA Dopamine Neurons-Zona Incerta Loop Underlying the Social Buffering Effects in Learned Helplessness
A common phenomenon called social buffering (SB), communication within conspecific animals is a benefit for a stressed individual to better recover from aversive events, is crucial to all mammals. Although the dopamine reward system has been implicated in SB, it is not clear which neuronal populatio...
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Published in: | Molecular neurobiology 2022-02, Vol.59 (2), p.856-871 |
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Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | A common phenomenon called social buffering (SB), communication within conspecific animals is a benefit for a stressed individual to better recover from aversive events, is crucial to all mammals. Although the dopamine reward system has been implicated in SB, it is not clear which neuronal populations are relevant and how they contribute. Here, we adopted a learned helplessness (LH) animal model of depression and found that LH subjects housed with a conspecific partner show better performance in the shuttle box test, showing that SB improves the stress-coping abilities to deal with stress. Bidirectional manipulation of ventral tegmental area (VTA) dopamine neurons by chemogenetic tools can mimic or block the SB effect in LH mice. To screen for SB-induced structure plasticity of VTA dopamine neurons, we employed viral genetic tools for mapping input and output architecture and found LH- and SB-triggered circuit-level changes in neuronal ensembles. Zona incerta (ZI), an overlapping brain region, was significantly changed in both anterograde and retrograde tracing during LH and SB. These results reveal a neural loop with structural plasticity between VTA dopamine neurons and ZI underlies the SB effects in LH and lays a foundation for studying how VTA dopamine neurons regulate SB-related neural circuits. |
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ISSN: | 0893-7648 1559-1182 |
DOI: | 10.1007/s12035-021-02614-4 |