Tuned inhibitory firing rate and connection weights as emergent network properties

Abstract

Excitatory cortical neurons show clear tuning to stimulus features, but the tuning properties of inhibitory neurons are ambiguous and have been the subject of a long debate. While inhibitory neurons have been considered to be largely untuned [1-4], recent studies show that some parvalbumin expressing (PV) neurons do show feature selectivity and participate in co-tuned subnetworks with pyramidal cells in which PV cells show high response similarity to the excitatory (E) neurons [5, 6]. Given shared input from layer 4 that drives feature tuning in excitatory subnetworks, we demonstrate that homeostatic regulation of postsynaptic firing rate governing the synaptic dynamics of the connections from PV to E cells, in combination with heterogeneity in the excitatory postsynaptic potentials (EPSP) that impinge on PV cells, results in the self-organization of PV subnetworks. We reconcile different experimental findings by showing that feature tuning of PV cells is an emerging network property that may be driven by synaptic heterogeneity, and can be inferred using population-level measures, while pairwise individual-level measures may fail to reveal inhibitory tuning. We show that such co-tuning can enhance network stability at the cost of response salience.