How synaptic strength, short-term plasticity, and temporal factors contribute to neuronal spike output

Abstract

AbstractTo compute spiking responses, neurons integrate inputs from thousands of synapses whose strengths span an order of magnitude. Intriguingly, in mouse neocortex, the small minority of ‘strong’ synapses is found predominantly between similarly tuned cells, suggesting they are the synapses that determine a neuron’s spike output. This raises the question of how other computational primitives, such as ‘background’ activity from the majority of synapses, which are ‘weak’, short-term plasticity, and temporal synchrony contribute to spiking. First, we combined extracellular stimulation and whole-cell recordings in mouse barrel cortex to map the distribution of excitatory postsynaptic potential (EPSP) amplitudes and paired-pulse ratios of excitatory synaptic connections converging onto individual layer 2/3 (L2/3) neurons. While generally net short-term plasticity was weak, connections with EPSPs > 2 mV displayed pronounced paired-pulse depression. EPSP amplitudes and paired-pulse ratios of connections converging onto the same neurons spanned the full range observed across L2/3 and there was no indication that strong synapses nor those with particular short-term plasticity properties were associated with particular cells, which critically constrains theoretical models of cortical filtering. To investigate how different computational primitives of synaptic information processing interact to shape spiking, we developed a computational model of a pyramidal neuron in the rodent L2/3 circuitry: firing rates and pairwise correlations of presynaptic inputs were constrained by in vivo observations, while synaptic strength and short-term plasticity were set based on our experimental data. Importantly, we found that the ability of strong inputs to evoke spiking critically depended on their high temporal synchrony and high firing rates observed in vivo and on synaptic background activity – and not primarily on synaptic strength, which in turn further enhanced information transfer. Depression of strong synapses was critical for maintaining a neuron’s responsivity and prevented runaway excitation. Our results provide a holistic framework of how cortical neurons exploit complex synergies between temporal coding, synaptic properties, and noise in order to transform synaptic inputs into output firing.