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Whole-Brain Neural Connectivity to Lateral Pontine Tegmentum
RG-deleted RV strategy was used to identify monosynaptic inputs to LPT GABAergic neurons. ChR2-mCherry was used to label the axonal projections. (All viruses were packaged by BrainVTA)
The viruses used in this article from BrainVTA are in the table below
RV  R01002 RV-EnvA-△RG-DsRed
Optogenetic  PT-0002 AAV-EF1a-DIO-ChR2-mCherry
Tracing Helper  PT-0165 AAV-EF1a-DIO-TVA-GFP
 PT-0023 AAV-EF1a-DIO-RV-G
Pan Luo, Anan Li, Yanxiao Zheng, Yutong Han, Jiaojiao Tian, Zhengchao Xu, Hui Gong and Xiangning Li
Pub Date: 2019-04-17,  DOI: 10.3389/fnana.2019.00044, Email:
Long-range neuronal circuits play an important role in motor and sensory information processing. Determining direct synaptic inputs of excited and inhibited neurons is important for understanding the circuit mechanisms involved in regulating movement. Here, we used the monosynaptic rabies tracing technique, combined with fluorescent micro-optical sectional tomography, to characterize the brain-wide input to the motor cortex (MC). The whole brain dataset showed that the main excited and inhibited neurons in the MC received inputs from similar brain regions with a quantitative difference. With 3D reconstruction we found that the distribution of input neurons, that target the primary and secondary MC, had different patterns. In the cortex, the neurons projecting to the primary MC mainly distributed in the lateral and anterior portion, while those to the secondary MC distributed in the medial and posterior portion. The input neurons in the subcortical areas also showed the topographic shift model, as in the thalamus, the neurons distributed as outer and inner shells while the neurons in the claustrum and amygdala were in the ventral and dorsal part, respectively. These results lay the anatomical foundation to understanding the organized pattern of motor circuits and the functional differences between the primary and secondary MC.
Figure. 1 Schematic presenting the typical regions with monosynaptic inputs to LPT GABAergic neurons.
The authors employed a modified RV and AAV in combination with the Cre/LoxP system to map presynaptic inputs and output projections of LPT GABAergic neurons. They identified several monosynaptic inputs of LPT GABAergic neurons by double labeling with antibodies for molecular markers related to sleep-wake regulation. The results revealed the wide-ranging connectivity of LPT GABAergic neurons and provided a structural framework to understand the underlying neural circuits of important physiological functions.
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