Excellent genetically-encoded sensors for calcium, glutamate and voltage have been developed 1, 2, 3, which when combined with two-photon laser-scanning microscopy can monitor the activity of neurons even down to the synaptic level in highly light-scattering brain tissue 4. On the network level, neuroscience faces an extreme ‘needle in the haystack’ problem: it is thought to be impossible, in practice, to create a map of all synapses that are active during a specific sensory input or behavior. The physical changes underlying learning and memory likely involve alterations in the strength and/or number of synaptic connections. Together, these tools provide an efficient method for repeatedly mapping active neurons and synapses in cell culture, slice preparations, and in vivo during behavior. To analyze large datasets, we show how to identify and track the fluorescence of thousands of individual synapses in an automated fashion. Targeted to excitatory postsynapses, postSynTagMA creates a snapshot of synapses active just before photoconversion. Targeted to presynaptic terminals, preSynTagMA allows discrimination between active and silent axons. Upon 395–405 nm illumination, this genetically encoded marker of activity converts from green to red fluorescence if, and only if, it is bound to calcium. Here we introduce SynTagMA to tag active synapses in a user-defined time window. At any given moment, only a small subset of neurons and synapses are active, but finding the active synapses in brain tissue has been a technical challenge. Information within the brain travels from neuron to neuron across billions of synapses.
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