A fast-conducting, stochastic integrative mode for neocortical neurons in vivo

During activated states, neocortical neurons receive intense synaptic background activity that induces large-amplitude membrane potential fluctuations and a strong conductance in the membrane. However, little is known about the integrative properties of neurons during such high-conductance states. Here we investigated the integrative properties of neocortical pyramidal neurons under in vivo conditions simulated by computational models. We show that the presence of high-conductance fluctuations induces a stochastic state in which active dendrites are fast conducting and have a different dynamics of initiation and forward-propagation of Na+-dependent spikes. Synaptic efficacy, quantified as the probability that a synaptic input specifically evokes a somatic spike, was approximately independent of the dendritic location of the synapse. Synaptic inputs evoked precisely timed responses (milliseconds), which also showed a reduced location dependence. This scheme was found to apply to a broad range of kinetics and density distributions of voltage-dependent conductances, as well as to different dendritic morphologies. Synaptic efficacies were, however, modulable by the balance of excitation and inhibition in background activity, for all synapses at once. Thus, models predict that the intense synaptic activity in vivo can confer advantageous computational properties to neocortical neurons: they can be set to an integrative mode that is stochastic, fast conducting, and optimized to process synaptic inputs at high temporal resolution independently of their position in the dendrites. Some of these predictions can be tested experimentally.