Neural Correlates of Gap Detection in Three Auditory Cortical Fields in the Cat

Abstract

Neural correlates of gap detection in three auditory cortical fields in the cat. Mimimum detectable gaps in noise in humans are independent of the position of the gap, whereas in cat primary auditory cortex (AI) they are position dependent. The position dependence in other cortical areas is not known and may resolve this contrast. This study presents minimum detectable gap-in-noise values for which single-unit (SU), multiunit (MU) recordings and local field potentials (LFPs) show an onset response to the noise after the gap. The gap, which varied in duration between 5 and 70 ms, was preceded by a noise burst of either 5 ms (early gap) or 500 ms (late gap) duration. In 10 cats, simultaneous recordings were made with one electrode each in AI, anterior auditory field (AAF), and secondary auditory cortex (AII). In nine additional cats, two electrodes were inserted in AI and one in AAF. Minimum detectable gaps based on SU, MU, or LFP data in each cortical area were the same. In addition, very similar minimum early-gap values were found in all three areas (means, 36.1–41.7 ms). The minimum late-gap values were also similar in AI and AII (means, 11.1 and 11.7 ms), whereas AAF showed significantly larger minimum late-gap durations (mean 21.5 ms). For intensities >35 dB SPL, distributions of minimum early-gap durations in AAF and AII had modal values at ∼45 ms. In AI, the distribution was more uniform. Distributions for minimum late-gap duration were skewed toward low values (mode at 5 ms), but high values (≤60 ms) were found infrequently as well. A small fraction of units showed a response after the gap only for early-gap durations <20 ms. In AI and AII, the mean minimum early- and late-gap durations decreased significantly with increase in the neuron’s characteristic frequency (CF), whereas the lower boundary for the minimum early gap was CF independent. The findings suggest that human within-perceptual-channel gap detection, showing no dependence of the minimum detectable gap on the duration of the leading noise burst, likely is based on the lower envelope of the distribution of neural minimum gap values of units in AI and AAF. In contrast, across-perceptual-channel gap detection, which shows a decreasing minimum detectable gap with increasing duration of the leading noise burst, likely is based on the comparison ofon responses from populations of neurons that converge on units in AII.