Data-driven synapse classification reveals a logic of glutamate receptor composition

The rich diversity of synapses facilitates the capacity of neural circuits to transmit, process and store information. Here, we used multiplex super-resolution proteometric imaging through array tomography to define features of single synapses in the adult mouse neocortex. We find that glutamatergic synapses cluster into subclasses that parallel the distinct biochemical and functional categories of receptor subunits: GluA1/4, GluA2/3 and GluN1/GluN2B. Two of these subclasses align with physiological expectations based on synaptic plasticity: large AMPAR-rich synapses may represent potentiated synapses, whereas small NMDAR-rich synapses suggest "silent" synapses. The NMDA receptor content of large synapses correlates with spine neck diameter, and thus the potential for coupling to the parent dendrite. Conjugate array tomography's rigorous registration of immunofluorescence with electron microscopy provides validation for future super-resolution imaging studies in other systems. No barriers prevent generalization of this approach to other species, laying a foundation for future studies of human disorders and therapeutics.