Roles for Coincidence Detection in Coding Amplitude-Modulated Sounds
Fig 2
LSO coincidence counting model.
A: Modeled AM-frequency dependence of the excitatory input rates. B: Modeled AM-frequency dependence of phase-locking of excitatory inputs. C: Modeled operation of coincidence detection. Each vertical bar corresponds to a spike. An input coincidence is counted when the number of inputs in the coincidence window W (vertical gray rectangle) reaches or exceeds the threshold θ. In this example, threshold θ is 3. The small arrow indicates an output spike rejected by the refractory period T. Effects of inhibitory inputs were modeled as threshold increase δ in the inhibition window Δ (dotted rectangle). D: Monaural AM-tuning curve with the default parameter set (θ = 8 inputs, W = 0.8 ms, T = 1.6 ms). Peak rate = 138.3 spikes/sec. Peak frequency = 265 Hz. Baseline = 9.7 spikes/sec. Half-peak frequency = 549 Hz. E: Binaural AM-phase coding with the default parameter set (fm = 300 Hz, δ = 2 inputs and Δ = 1.6 ms). Peak rate = 130.7 spikes/sec. Peak phase = −137 deg. Trough rate = 18.7 spikes/sec. Trough phase = +46 deg. Half-peak width = 191 deg. F: Modeled level-dependence of input spike rates. G: Modeled level-dependence of phase-locking. Both excitatory and inhibitory inputs were assumed to share the rate-level and VS-level functions. H: Effects of modulation frequency fm on coincidence detection. Depending on frequency, the length of one modulation cycle could be larger (at low fm) or smaller (at high fm) than width W of the coincidence window. Thick curves show the spike rates of the phase-locked inputs. Broken lines show the time-averaged (non-phase-locked) spike rates.