Dynamic Influences on Coincidence Detection in Neocortical Pyramidal Neurons

Abstract

The firing rate of neocortical pyramidal neurons is believed to represent primarily the average arrival rate of synaptic inputs; however, it has also been found to vary somewhat depending on the degree of synchrony among synaptic inputs. We investigated the ability of pyramidal neurons to perform coincidence detection, that is, to represent input timing in their firing rate, and explored some factors that influence that representation. We injected computer-generated simulated synaptic inputs into pyramidal neurons during whole-cell recordings, systematically altering the phase delay between two groups of periodic simulated input events. We explored how input intensity, the synaptic time course, inhibitory synaptic conductance, and input jitter influenced the firing rate representation of input timing. In agreement with computer modeling studies, we found that input synchronization increases firing rate when intensity is low but reduces firing rate when intensity is high. At high intensity, the effect of synchrony on firing rate could be switched from reducing to increasing firing rate by shortening the simulated excitatory synaptic time course, adding inhibition (using the dynamic clamp technique), or introducing a small input jitter. These opposite effects of synchrony may serve different computational functions: as a means of increasing firing rate it may be useful for efficient recruitment or for computing a continuous parameter, whereas as a means of decreasing firing rate it may provide gain control, which would allow redundant or excessive input to be ignored. Modulation of dynamic input properties may allow neurons to perform different operations depending on the task at hand.

Gamma Oscillations and Stimulus Selection

“…Coherent (i.e., nearly simultaneous) excitatory input pulses targeting a leaky neuron are more likely to trigger a spike response than incoherent ones (Murthy & Fetz, 1994;Singer, 1999). The advantage of coherent input can be amplified by synaptic inhibition, which can significantly raise the leakiness of the target neuron (Häusser & Clark, 1997;Funabiki, Koyano, & Ohmori, 1998;Pouille & Scanziani, 2001;Grande, Kinney, Miracle, & Spain, 2004). Here we present numerical and analytic results for theta and integrate-and-fire neurons confirming that this is an important effect.…”

Short-Term Synaptic Depression Causes a Non-Monotonic Response to Correlated Stimuli

“…Unless M Ն 5, the increase I produced by the autocorrelations is too little to overcome the decrease in I and, including autocorrelation, leads to an decrease in the response even in the case N 0 Ͼ 1 (data not shown). 2000) (but see also Grande et al, 2004), which happens just because a coordinated population of neurons can produce larger depolarizations than a population of independent neurons. Let us then consider a simple configuration in which each presynaptic neuron fires, locked to a periodic signal of frequency f, one spike per cycle.…”

Diversity of Gain Modulation by Noise in Neocortical Neurons: Regulation by the Slow Afterhyperpolarization Conductance

“…In layer 5 pyramidal cells, synchronizing two groups of simulated EPSCs arriving at gamma frequency (40 Hz) increased the firing rate when each group was subthreshold but reduced the firing rate at higher input amplitude (Grande et al, 2004). Generally, a transition from coincidence detection to temporal integration may occur when the mean current exceeds threshold (Gerstner and Kistler, 2002).…”