Social behaviour shapes hypothalamic neural ensemble representations of conspecific sex

Abstract

SummaryAll animals possess a repertoire of innate (or instinctive1,2) behaviors, which can be performed without training. Whether such behaviors are mediated by anatomically distinct and/or genetically specified neural pathways remains a matter of debate3-5. Here we report that hypothalamic neural ensemble representations underlying innate social behaviors are shaped by social experience. Estrogen receptor 1-expressing (Esr1+) neurons in the ventrolateral subdivision of the ventromedial hypothalamus (VMHvl) control mating and fighting in rodents6-8. We used microendoscopy9 to image VMHvl Esr1+ neuronal activity in male mice engaged in these social behaviours. In sexually and socially experienced adult males, divergent and characteristic neural ensembles represented male vs. female conspecifics. But surprisingly, in inexperienced adult males, male and female intruders activated overlapping neuronal populations. Sex-specific ensembles gradually separated as the mice acquired social and sexual experience. In mice permitted to investigate but not mount or attack conspecifics, ensemble divergence did not occur. However, 30 min of sexual experience with a female was sufficient to promote both male vs. female ensemble separation and attack, measured 24 hr later. These observations uncover an unexpected social experience-dependent component to the formation of hypothalamic neural assemblies controlling innate social behaviors. More generally, they reveal plasticity and dynamic coding in an evolutionarily ancient deep subcortical structure that is traditionally viewed as a “hard-wired” system.

NINscope: a versatile miniscope for multi-region circuit investigations

“…Thus, imaging approaches can reveal how individual cells embedded in a larger network display coordinated activity during different stages of behavior or training (Wagner et al 2017;Heffley et al 2018;Galiñanes, Bonardi, and Huber 2018;Giovannucci et al 2017) . Moreover, because of their ability to record in freely moving animals, miniscopes have been instrumental in uncovering neural activity patterns occurring during natural behaviors and related brain-states including social interactions (Murugan et al 2017;Remedios et al 2017;Liang et al 2018;Kingsbury et al 2019) or sleep Cox, Pinto, and Dan 2016) with fully intact vestibular input.…”

A neuronal signature for monogamous reunion

“…For instance, grid cells display functional micro-organization and clustering within the medial entorhinal cortex (Gu et al, 2018;Heys et al, 2014). However, in mouse brain areas projecting to the NAc, including the medial prefrontal cortex, amygdala, and hypothalamus (Walum and Young, 2018), ensembles encoding social information seem to lack meaningful spatial organization (Kingsbury et al, 2019;Li et al, 2017;Remedios et al, 2017). Thus, we asked whether approach and departure ensembles displayed spatial organization within NAc.…”

Emergent buffering balances evolvability and robustness in the evolution of phenotypic flexibility

“…; Remedios et al. ) and optimal phenotypic adjustment in relation to current costs and benefits (Kokko ; Cichoñ ; Frankenhuis and Panchanathan ; Fischer et al. ; English et al.…”

“…The study of phenotypic flexibility-environmentally influenced phenotypic adjustment ("updating") that occurs repeatedly during the lifetime of an individual (Piersma and Drent 2003;West-Eberhard 2003)-provides such an opportunity, because it allows direct insight into integration of an existing phenotype, new environmental inputs, and inherited components in modification of adaptive features (Bateson et al 2014;Stamps and Krishnan 2014;Nettle and Bateson 2015;Beaman et al 2016;Panchanathan and Frankenhuis 2016;Stamps and Frankenhuis 2016). Indeed, recent studies of age-dependent phenotypic adjustments that integrated life-history, developmental, genetic, and informational perspectives have provided some of the most illuminating insights into both the mechanistic basis of withingeneration modifications (e.g., Fagiolini et al 2009;Remedios et al 2017) and optimal phenotypic adjustment in relation to current costs and benefits (Kokko 1997;Cichoñ 2001;Frankenhuis and Panchanathan 2011;Fischer et al 2014;English et al 2016;Stamps and Krishnan 2017).…”