Mapping Synaptic Input Fields of Neurons with Super-Resolution Imaging

• Published in: Cell 2015-10, Vol.163 (2), p.493-505
• Main Authors: Sigal, Yaron M., Speer, Colenso M., Babcock, Hazen P., Zhuang, Xiaowei
• Format: Article
• Language: English
• Subjects: Animals; Brain - cytology; Carrier Proteins; Immunohistochemistry; Membrane Proteins; Mice; Nerve Net; Neural Pathways; Neurons - cytology; Optical Imaging - methods; Receptors, GABA - metabolism; Receptors, Glycine - metabolism; Retinal Ganglion Cells - metabolism; Retinal Neurons - metabolism; Synapses - metabolism
• ISSN: 0092-8674; 1097-4172
• DOI: 10.1016/j.cell.2015.08.033

As a basic functional unit in neural circuits, each neuron integrates input signals from hundreds to thousands of synapses. Knowledge of the synaptic input fields of individual neurons, including the identity, strength, and location of each synapse, is essential for understanding how neurons compute. Here, we developed a volumetric super-resolution reconstruction platform for large-volume imaging and automated segmentation of neurons and synapses with molecular identity information. We used this platform to map inhibitory synaptic input fields of On-Off direction-selective ganglion cells (On-Off DSGCs), which are important for computing visual motion direction in the mouse retina. The reconstructions of On-Off DSGCs showed a GABAergic, receptor subtype-specific input field for generating direction selective responses without significant glycinergic inputs for mediating monosynaptic crossover inhibition. These results demonstrate unique capabilities of this super-resolution platform for interrogating neural circuitry. [Display omitted] •A super-resolution platform for volumetric tissue imaging and analysis is developed•The platform allows synapses on neurons to be identified with molecular specificity•On-Off DSGCs receive receptor subunit-specific GABAergic inputs•On-Off DSGCs do not receive substantial monosynaptic glycinergic inputs A super-resolution fluorescence-imaging platform for multi-color volumetric reconstruction of synapses and neurons in brain tissue is developed, enabling interrogation of neural circuitry at the nanoscale.