Detectability depends on input amplitude and output firing rate, and excitatory inputs are detected more readily than inhibitory.

As with the experimental data, we find that, in both the current-based and conductance-based models, higher amplitude synapses are easier to detect and there is an asymmetry between excitatory and inhibitory inputs with inhibitory inputs being more difficult to detect than excitatory inputs of the same magnitude.

3) Excitatory inputs are more readily detected than inhibitory.

Importantly, inhibitory inputs are more difficult to detect than excitatory inputs of the same amplitude, and inhibition required ~ 30% more data for detection with pairwise tests.

They have less impact on the postsynaptic firing, and thus are less accurate in predicting output spikes compared to excitatory inputs of the same magnitude (the log likelihood ratios comparing Model 2 with coupling to Model 1 with spike-history alone are 58i2% smaller for inhibitory inputs).

With these data we find c = 111, 32, and 18s for detection of excitatory inputs at 1Hz, 5Hz, and 10Hz output rates and c = 182, 46, and 29s for detection of inhibitory inputs at these rates.

On average, inhibitory inputs required 32:3% more data for detection than excitatory inputs .

In this way, high frequency bursts indicate the coincident input of excitatory input onto two distinct areas of the neuron.

Here, concurrent excitatory input into the superficial and deeper layers produces high-frequency bursting, signaling coincident basal and apical input to downstream neurons.

In addition to excitatory inputs , inhibitory inputs across cortical layers are diverse.

We create three abstract models to describe the input-output relationship from tuft and basal excitatory input to firing rate output.