Noise correlations (r(noise)) between neurons can affect a neural population's discrimination capacity, even without changes in mean firing rates of neurons. r(noise), the degree to which the response variability of a pair of neurons is correlated, has been shown to change with attention with most reports showing a reduction in r(noise). However, the effect of reducing r(noise) on sensory discrimination depends on many factors, including the tuning similarity, or tuning correlation (r(tuning)), between the pair. Theoretically, reducing r(noise) should enhance sensory discrimination when the pair exhibits similar tuning, but should impair discrimination when tuning is dissimilar. We recorded from pairs of neurons in primary auditory cortex (A1) under two conditions: while rhesus macaque monkeys (Macaca mulatta) actively performed a threshold amplitude modulation (AM) detection task and while they sat passively awake. We report that, for pairs with similar AM tuning, average r(noise) in A1 decreases when the animal performs the AM detection task compared with when sitting passively. For pairs with dissimilar tuning, the average r(noise) did not significantly change between conditions. This suggests that attention-related modulation can target selective subcircuits to decorrelate noise. These results demonstrate that engagement in an auditory task enhances population coding in primary auditory cortex by selectively reducing deleterious r(noise) and leaving beneficial r(noise) intact.

We recorded from middle-lateral (ML) and primary (A1) auditory cortex while macaques discriminated amplitude-modulated (AM) noise from unmodulated noise. Compared with A1, ML had a higher proportion of neurons that encoded increasing AM depth by decreasing their firing rates ("decreasing" neurons), particularly with responses that were not synchronized to the modulation. Choice probability (CP) analysis revealed that A1 and ML activity were different during the first half of the test stimulus. In A1, significant CP began before the test stimulus, remained relatively constant (or increased slightly) during the stimulus, and increased greatly within 200 ms of lever release. Neurons in ML behaved similarly, except that significant CP disappeared during the first half of the stimulus and reappeared during the second half and prerelease periods. CP differences between A1 and ML depend on neural response type. In ML (but not A1), when activity was lower during the first half of the stimulus in nonsynchronized, decreasing neurons, the monkey was more likely to report AM. Neurons that both increased firing rate with increasing modulation depth ("increasing" neurons) and synchronized their responses to AM had similar choice-related activity dynamics in ML and A1. These results suggest that, when ascending the auditory system, there is a transformation in coding AM from primarily synchronized increasing responses in A1 to nonsynchronized and dual (increasing/decreasing) coding in ML. This sensory transformation is accompanied by changes in the timing of activity related to choice, suggesting functional differences between A1 and ML related to attention and/or behavior.

Previous observations show that humans outperform non-human primates on some temporally-based auditory discrimination tasks, suggesting there are species differences in the proficiency of auditory temporal processing among primates. To further resolve these differences we compared the abilities of rhesus macaques and humans to detect sine-amplitude modulation (AM) of a broad-band noise carrier as a function of both AM frequency (2.5 Hz-2 kHz) and signal duration (50-800 ms), under similar testing conditions. Using a go/no-go AM detection task, we found that macaques were less sensitive than humans at the lower frequencies and shorter durations tested but were as, or slightly more, sensitive at higher frequencies and longer durations. Humans had broader AM tuning functions, with lower frequency regions of peak sensitivity (10-60 Hz) than macaques (30-120 Hz). These results support the notion that there are species differences in temporal processing among primates, and underscore the importance of stimulus duration when making cross-species comparisons for temporally-based tasks.

We recorded from middle lateral belt (ML) and primary (A1) auditory cortical neurons while animals discriminated amplitude-modulated (AM) sounds and also while they sat passively. Engagement in AM discrimination improved ML and A1 neurons' ability to discriminate AM with both firing rate and phase-locking; however, task engagement affected neural AM discrimination differently in the two fields. The results suggest that these two areas utilize different AM coding schemes: a "single mode" in A1 that relies on increased activity for AM relative to unmodulated sounds and a "dual-polar mode" in ML that uses both increases and decreases in neural activity to encode modulation. In the dual-polar ML code, nonsynchronized responses might play a special role. The results are consistent with findings in the primary and secondary somatosensory cortices during discrimination of vibrotactile modulation frequency, implicating a common scheme in the hierarchical processing of temporal information among different modalities. The time course of activity differences between behaving and passive conditions was also distinct in A1 and ML and may have implications for auditory attention. At modulation depths ≥ 16% (approximately behavioral threshold), A1 neurons' improvement in distinguishing AM from unmodulated noise is relatively constant or improves slightly with increasing modulation depth. In ML, improvement during engagement is most pronounced near threshold and disappears at highly suprathreshold depths. This ML effect is evident later in the stimulus, and mainly in nonsynchronized responses. This suggests that attention-related increases in activity are stronger or longer-lasting for more difficult stimuli in ML.

Recent evidence is reshaping the view of primary auditory cortex (A1) from a unisensory area to one more involved in dynamically integrating multisensory- and task-related information. We found A1 single- (SU) and multiple-unit (MU) activity correlated with macaques' choices in an amplitude modulation (AM) discrimination task. Animals were trained to discriminate AM noise from unmodulated noise by releasing a lever for AM noise and holding down the lever for unmodulated noise. Activity for identical stimuli was compared between trials where the animals reported AM and trials where they did not. We found 47.4% of MUs and 22.8% of SUs significantly increased firing shortly before the animal's behavioral response to report AM when compared to the equivalent time period on trials where AM was not reported. Activity was also linked to lever release in a different task context, suggesting A1 modulation by somatosensory, or efference copy, input. When spikes were counted only during the stimulus, 19.6% of MUs and 13.8% of SUs increased firing rate when animals reported AM compared to when they did not, suggesting an attentional effect, or that A1 activity can be used by higher decision areas, or that such areas provide feedback to A1. Activity associated with AM reporting was correlated with a unit's AM sensitivity, suggesting AM sensitive neurons' involvement in task performance. A1 neurons' phase locking to AM correlated more weakly (compared to firing rate) with the animals' report of AM, suggesting a preferential role for rate-codes in A1 for this AM discrimination task.

In macaques, the middle lateral auditory cortex (ML) is a belt region adjacent to the primary auditory cortex (A1) and believed to be at a hierarchically higher level. Although ML single-unit responses have been studied for several auditory stimuli, the ability of ML cells to encode amplitude modulation (AM)-an ability that has been widely studied in A1-has not yet been characterized. Here, we compared the responses of A1 and ML neurons to amplitude-modulated (AM) noise in awake macaques. Although several of the basic properties of A1 and ML responses to AM noise were similar, we found several key differences. ML neurons were less likely to phase lock, did not phase lock as strongly, and were more likely to respond in a nonsynchronized fashion than A1 cells, consistent with a temporal-to-rate transformation as information ascends the auditory hierarchy. ML neurons tended to have lower temporally (phase-locking) based best modulation frequencies than A1 neurons. Neurons that decreased their firing rate in response to AM noise relative to their firing rate in response to unmodulated noise became more common at the level of ML than they were in A1. In both A1 and ML, we found a prevalent class of neurons that usually have enhanced rate responses relative to responses to the unmodulated noise at lower modulation frequencies and suppressed rate responses relative to responses to the unmodulated noise at middle modulation frequencies.NEW & NOTEWORTHY ML neurons synchronized less than A1 neurons, consistent with a hierarchical temporal-to-rate transformation. Both A1 and ML had a class of modulation transfer functions previously unreported in the cortex with a low-modulation-frequency (MF) peak, a middle-MF trough, and responses similar to unmodulated noise responses at high MFs. The results support a hierarchical shift toward a two-pool opponent code, where subtraction of neural activity between two populations of oppositely tuned neurons encodes AM.

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 nonsynchronized and synchronized responses, the firing rate of nonsynchronized 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 in which rate and temporal coding work in parallel, permitting a multiplexed code for temporal modulation, and for a complementary representation of rate and temporal coding.