Short-term plasticity of EI balance at single neurons can detect pattern transitions

Sensory input and internal context converge onto the hippocampus as spatio-temporal patterns of activity. Transitions in these input patterns are frequently salient, yet the CA1 pyramidal neurons operate under conditions of divisive normalisation of summed patterned input by excitatory-inhibitory (EI) balance which suppresses most responses. We characterized the role of short-term potentiation (STP) in mediating change detection in the mouse hippocampus CA3-CA1 network using optogenetic patterned stimuli in CA3 while recording from CA1 pyramidal neurons. We parameterized STP and its effect on summation, and developed a multiscale model of network projections onto hundreds of E and I boutons each including stochastic signaling to mediate STP on the postsynaptic neuron. We show that STP modulates EI summation across patterns, and predicted and confirmed that single neurons can detect transitions in input patterns responses. Using the model we show that in feedforward networks, STP coupled with moderate sparsity of input due to input pattern sparsity and connections, strengthens rapid pattern change detection by single neurons.