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Connectional architecture of a mouse hypothalamic circuit node controlling social behavior

Type 1 estrogen receptor-expressing neurons in the ventrolateral subdivision of the ventromedial hypothalamus (VMHvl(Esr1)) play a causal role in the control of social behaviors, including aggression. Here we use six different viral-genetic tracing methods to systematically map the connectional arch...

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Detalles Bibliográficos
Autores principales: Lo, Liching, Yao, Shenqin, Kim, Dong-Wook, Cetin, Ali, Harris, Julie, Zeng, Hongkui, Anderson, David J., Weissbourd, Brandon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6462064/
https://www.ncbi.nlm.nih.gov/pubmed/30898882
http://dx.doi.org/10.1073/pnas.1817503116
Descripción
Sumario:Type 1 estrogen receptor-expressing neurons in the ventrolateral subdivision of the ventromedial hypothalamus (VMHvl(Esr1)) play a causal role in the control of social behaviors, including aggression. Here we use six different viral-genetic tracing methods to systematically map the connectional architecture of VMHvl(Esr1) neurons. These data reveal a high level of input convergence and output divergence (“fan-in/fan-out”) from and to over 30 distinct brain regions, with a high degree (∼90%) of bidirectionality, including both direct as well as indirect feedback. Unbiased collateralization mapping experiments indicate that VMHvl(Esr1) neurons project to multiple targets. However, we identify two anatomically distinct subpopulations with anterior vs. posterior biases in their collateralization targets. Nevertheless, these two subpopulations receive indistinguishable inputs. These studies suggest an overall system architecture in which an anatomically feed-forward sensory-to-motor processing stream is integrated with a dense, highly recurrent central processing circuit. This architecture differs from the “brain-inspired,” hierarchical feed-forward circuits used in certain types of artificial intelligence networks.