Correlated spiking is often observed in cortical circuits, but its functional role is controversial. It is believed that correlations are a consequence of shared inputs between nearby neurons and could severely constrain information decoding. Here we show theoretically that recurrent neural networks can generate an asynchronous state characterized by arbitrarily low mean spiking correlations despite substantial amounts of shared input. In this state, spontaneous fluctuations in the activity of excitatory and inhibitory populations accurately track each other, generating negative correlations in synaptic currents which cancel the effect of shared input. Near-zero mean correlations were seen experimentally in recordings from rodent neocortex in vivo. Our results suggest a re-examination of the sources underlying observed correlations and their functional consequences for information processing.

Gain modulation is a prominent feature of neuronal activity recorded in behaving animals, but the mechanism by which it occurs is unknown. By introducing a barrage of excitatory and inhibitory synaptic conductances that mimics conditions encountered in vivo into pyramidal neurons in slices of rat somatosensory cortex, we show that the gain of a neuronal response to excitatory drive can be modulated by varying the level of "background" synaptic input. Simultaneously increasing both excitatory and inhibitory background firing rates in a balanced manner results in a divisive gain modulation of the neuronal response without appreciable signal-independent increases in firing rate or spike-train variability. These results suggest that, within active cortical circuits, the overall level of synaptic input to a neuron acts as a gain control signal that modulates responsiveness to excitatory drive.

Populations of neurons in the retina, olfactory system, visual and somatosensory thalamus, and several cortical regions show temporal correlation between the discharge times of their action potentials (spike trains). Correlated firing has been linked to stimulus encoding, attention, stimulus discrimination, and motor behaviour. Nevertheless, the mechanisms underlying correlated spiking are poorly understood, and its coding implications are still debated. It is not clear, for instance, whether correlations between the discharges of two neurons are determined solely by the correlation between their afferent currents, or whether they also depend on the mean and variance of the input. We addressed this question by computing the spike train correlation coefficient of unconnected pairs of in vitro cortical neurons receiving correlated inputs. Notably, even when the input correlation remained fixed, the spike train output correlation increased with the firing rate, but was largely independent of spike train variability. With a combination of analytical techniques and numerical simulations using 'integrate-and-fire' neuron models we show that this relationship between output correlation and firing rate is robust to input heterogeneities. Finally, this overlooked relationship is replicated by a standard threshold-linear model, demonstrating the universality of the result. This connection between the rate and correlation of spiking activity links two fundamental features of the neural code.

In neocortical circuits, repetitively active neurons evoke unitary postsynaptic potentials (PSPs) whose peak amplitudes either increase (facilitate) or decrease (depress) progressively. To examine the basis for these different synaptic responses, we made simultaneous recordings from three classes of neurons in cortical layer 2/3. We induced repetitive action potentials in pyramidal cells and recorded the evoked unitary excitatory (E)PSPs in two classes of GABAergic neurons. We observed facilitation of EPSPs in bitufted GABAergic interneurons, many of which expressed somatostatin immunoreactivity. EPSPs recorded from multipolar interneurons, however, showed depression. Some of these neurons were immunopositive for parvalbumin. Unitary inhibitory (I)PSPs evoked by repetitive stimulation of a bitufted neuron also showed a less pronounced but significant difference between the two target neurons. Facilitation and depression involve presynaptic mechanisms, and because a single neuron can express both behaviors simultaneously, we infer that local differences in the molecular structure of presynaptic nerve terminals are induced by retrograde signals from different classes of target neurons. Because bitufted and multipolar neurons both formed reciprocal inhibitory connections with pyramidal cells, the results imply that the balance of activation between two recurrent inhibitory pathways in the neocortex depends on the frequency of action potentials in pyramidal cells.