Conflicting results have led to different views about how temporal modulation is encoded in primary auditory cortex (A1). Some studies find a substantial population of neurons that change firing rate without synchronizing to temporal modulation, whereas other studies fail to see these nonsynchronized neurons. As a result, the role and scope of synchronized temporal and nonsynchronized rate codes in AM processing in A1 remains unresolved. We recorded A1 neurons' responses in awake macaques to sinusoidal AM noise. We find most (37-78%) neurons synchronize to at least one modulation frequency (MF) without exhibiting nonsynchronized responses. However, we find both exclusively nonsynchronized neurons (7-29%) and "mixed-mode" neurons (13-40%) that synchronize to at least one MF and fire nonsynchronously to at least one other. We introduce new measures for modulation encoding and temporal synchrony that can improve the analysis of how neurons encode temporal modulation. These include comparing AM responses to the responses to unmodulated sounds, and a vector strength measure that is suitable for single-trial analysis. Our data support a transformation from a temporally based population code of AM to a rate-based code as information ascends the auditory pathway. The number of mixed-mode neurons found in A1 indicates this transformation is not yet complete, and A1 neurons may carry multiplexed temporal and rate codes.

In Experiment 1 (n = 8), the rat's ability to detect brief gaps in white noise was measured by gap-produced inhibition of an acoustic startle reflex, elicited 100 ms after the gap. After bilateral application of KCl to the cortex, gaps as long as 15 ms provided no reflex inhibition; in contrast, the inhibitory threshold was between 2 and 4 ms in the saline control condition. In Experiment 2 (n = 13), noise pulses of 40, 50, or 70 dB were presented 20-500 ms before the startle stimulus, and in Experiment 3 (n = 5) noise offsets occurred so that the startle stimulus was presented at the end of a 2-30-ms gap. Noise pulses and offsets both inhibited reflex expression equally in saline- and KCl-treated animals. Differences between the normal (saline) functions of noise offsets and gaps suggest additional sensory processing with the longer lead time. The loss of gap sensitivity after KCl application indicates that gap processing, unlike pulses and offsets, depends on cortical mechanisms.

. Organization of inhibitory frequency receptive fields in cat primary auditory cortex. J. Neurophysiol. 82: 2358Neurophysiol. 82: -2371Neurophysiol. 82: , 1999. Based on properties of excitatory frequency (spectral) receptive fields (esRFs), previous studies have indicated that cat primary auditory cortex (A1) is composed of functionally distinct dorsal and ventral subdivisions. Dorsal A1 (A1d) has been suggested to be involved in analyzing complex spectral patterns, whereas ventral A1 (A1v) appears better suited for analyzing narrowband sounds. However, these studies were based on single-tone stimuli and did not consider how neuronal responses to tones are modulated when the tones are part of a more complex acoustic environment. In the visual and peripheral auditory systems, stimulus components outside of the esRF can exert strong modulatory effects on responses. We investigated the organization of inhibitory frequency regions outside of the pure-tone esRF in single neurons in cat A1. We found a high incidence of inhibitory response areas (in 95% of sampled neurons) and a wide variety in the structure of inhibitory bands ranging from a single band to more than four distinct inhibitory regions. Unlike the auditory nerve where most fibers possess two surrounding "lateral" suppression bands, only 38% of A1 cells had this simple structure. The word lateral is defined in this sense to be inhibition or suppression that extends beyond the low-and high-frequency borders of the esRF. Regional differences in the distribution of inhibitory RF structure across A1 were evident. In A1d, only 16% of the cells had simple two-banded lateral RF organization, whereas 50% of A1v cells had this organization. This nonhomogeneous topographic distribution of inhibitory properties is consistent with the hypothesis that A1 is composed of at least two functionally distinct subdivisions that may be part of different auditory cortical processing streams.

When interfering objects occlude a scene, the visual system restores the occluded information. Similarly, when a sound of interest (a "foreground" sound) is interrupted (occluded) by loud noise, the auditory system restores the occluded information. This process, called auditory induction, can be exploited to create a continuity illusion. When a segment of a foreground sound is deleted and loud noise fills the missing portion, listeners incorrectly report hearing the foreground continuing through the noise. Here we reveal the neurophysiological underpinnings of illusory continuity in single-neuron responses from awake macaque monkeys' primary auditory cortex (A1). A1 neurons represented the missing segment of occluded tonal foregrounds by responding to discontinuous foregrounds interrupted by intense noise as if they were responding to the complete foregrounds. By comparison, simulated peripheral responses represented only the noise and not the occluded foreground. The results reveal that many A1 single-neuron responses closely follow the illusory percept.

The effect of attention on single neuron responses in the auditory system is unresolved. We found that when monkeys discriminated temporally amplitude modulated (AM) from unmodulated sounds, primary auditory cortical (A1) neurons better discriminated those sounds than when the monkeys were not discriminating them. This was observed for both average firing rate and vector strength (VS), a measure of how well neurons temporally follow the stimulus’ temporal modulation. When data were separated by non-synchronized and synchronized responses, the firing rate of non-synchronized responses best distinguished AM-noise from unmodulated noise followed by VS for synchronized responses, with firing rate for synchronized neurons providing the poorest AM discrimination. Firing rate-based AM discrimination for synchronized neurons, however, improved most with task engagement, showing that the least sensitive code in the passive condition improves the most with task-engagement. Rate coding improved due to larger increases in absolute firing-rate at higher modulation depths than for lower depths and unmodulated sounds. Relative to spontaneous activity (which increased with engagement), the response to unmodulated sounds decreased substantially. The temporal coding improvement -- responses more precisely temporally following a stimulus when animals were required to attend to it -- expands the framework of possible mechanisms of attention to include increasing temporal precision of stimulus following. These findings provide a crucial step to understanding the coding of temporal modulation, and support a model where rate and temporal coding work in parallel, permitting a multiplexed code for temporal modulation, and for a complementary representation of rate and temporal coding.