Cortical neuron response selectivity derives from strength in numbers of synapses

Single neocortical neurons are driven by populations of excitatory inputs, forming the basis of neural selectivity to features of sensory input. Excitatory connections are thought to mature during development through activity-dependent Hebbian plasticity1, whereby similarity between presynaptic and postsynaptic activity selectively strengthens some synapses and weakens others2. Evidence in support of this process ranges from measurements of synaptic ultrastructure to slice and in vivo physiology and imaging studies3,4,5,6,7,8. These corroborating lines of evidence lead to the prediction that a small number of strong synaptic inputs drive neural selectivity, while weak synaptic inputs are less correlated with the functional properties of somatic output and act to modulate activity overall6,7. Supporting evidence from cortical circuits, however, has been limited to measurements of neighboring, connected cell pairs, raising the question of whether this prediction holds for the full profile of synapses converging onto cortical neurons. Here we measure the strengths of functionally characterized excitatory inputs contacting single pyramidal neurons in ferret primary visual cortex (V1) by combining in vivo two-photon synaptic imaging and post hoc electron microscopy (EM). Using EM reconstruction of individual synapses as a metric of strength, we find no evidence that strong synapses play a predominant role in the selectivity of cortical neuron responses to visual stimuli. Instead, selectivity appears to arise from the total number of synapses activated by different stimuli. Moreover, spatial clustering of co-active inputs, thought to amplify synaptic drive, appears reserved for weaker synapses, further enhancing the contribution of the large number of weak synapses to somatic response. Our results challenge the role of Hebbian mechanisms in shaping neuronal selectivity in cortical circuits, and suggest that selectivity reflects the co-activation of large populations of presynaptic neurons with similar properties and a mixture of strengths.