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The posterior dorsomedial striatum (pDMS) is mainly composed of medium spiny neurons (MSNs) expressing either dopamine D1 receptors (D1Rs) or D2Rs. Activation of these two MSN types produces opposing effects on addictive behaviors. However, it remains unclear whether pDMS D1-MSNs or D2-MSNs receive afferent inputs from different brain regions or whether the extrastriatal afferents express distinct dopamine receptors. To assess whether these afferents also contained D1Rs or D2Rs, we generated double transgenic mice, in which D1R-expressing and D2R-expressing neurons were fluorescently labeled. We used rabies virus-mediated retrograde tracing in these mice to perform whole-brain mapping of direct inputs to D1-MSNs or D2-MSNs in the pDMS. We found that D1-MSNs preferentially received inputs from the secondary motor, secondary visual, and cingulate cortices, whereas D2-MSNs received inputs from the primary motor and primary sensory cortices, and the thalamus. We also discovered that the bed nucleus of the stria terminalis (BNST) and the central nucleus of the amygdala (CeA) contained abundant D2R-expressing, but few D1R-expressing, neurons in a triple transgenic mouse model. Remarkably, although limited D1R or D2R expression was observed in extrastriatal neurons that projected to D1-MSNs or D2-MSNs, we found that cortical structures preferentially contained D1R-expressing neurons that projected to D1-MSNs or D2-MSNs, while the thalamus, substantia nigra pars compacta (SNc), and BNST had more D2R-expressing cells that projected to D2-MSNs. Taken together, these findings provide a foundation for future understanding of the pDMS circuit and its role in action selection and reward-based behaviors.

Assigning behavioral functions to neural structures has long been a central goal in neuroscience and is a necessary first step toward a circuit-level understanding of how the brain generates behavior. Here, we map the neural substrates of locomotion and social behaviors for Drosophila melanogaster using automated machine-vision and machine-learning techniques. From videos of 400,000 flies, we quantified the behavioral effects of activating 2,204 genetically targeted populations of neurons. We combined a novel quantification of anatomy with our behavioral analysis to create brain-behavior correlation maps, which are shared as browsable web pages and interactive software. Based on these maps, we generated hypotheses of regions of the brain causally related to sensory processing, locomotor control, courtship, aggression, and sleep. Our maps directly specify genetic tools to target these regions, which we used to identify a small population of neurons with a role in the control of walking.