A fundamental feature of auditory perception is the constancy of sound recognition over a large range of intensities. Although this invariance has been described in behavioral studies, the underlying neural mechanism is essentially unknown. Here we show a putative level-invariant representation of sounds by populations of neurons in primary auditory cortex (A1) that may provide a neural basis for the behavioral observations. Previous studies reported that pure-tone frequency tuning of most A1 neurons widens with increasing sound level. In sharp contrast, we found that a large proportion of neurons in A1 of awake marmosets were narrowly and separably tuned to both frequency and sound level. Tuning characteristics and firing rates of the neural population were preserved across all tested sound levels. These response properties lead to a level-invariant representation of sounds over the population of A1 neurons. Such a representation is an important step for robust feature recognition in natural environments.

In the auditory cortex of awake animals, a substantial number of neurons do not respond to pure tones. These neurons have historically been classified as "unresponsive" and even been speculated as being nonauditory. We discovered, however, that many of these neurons in the primary auditory cortex (A1) of awake marmoset monkeys were in fact highly selective for complex sound features. We then investigated how such selectivity might arise from the tone-tuned inputs that these neurons likely receive. We found that these non-tone responsive neurons exhibited nonlinear combination-sensitive responses that require precise spectral and temporal combinations of two tone pips. The nonlinear spectrotemporal maps derived from these neurons were correlated with their selectivity for complex acoustic features. These non-tone responsive and nonlinear neurons were commonly encountered at superficial cortical depths in A1. Our findings demonstrate howtemporallyandspectrallyspecificnonlinearintegrationofputativetone-tunedinputsmightunderlieadiverserangeofhighselectivityofA1 neurons in awake animals. We propose that describing A1 neurons with complex response properties in terms of tone-tuned input channels can conceptually unify a wide variety of observed neural selectivity to complex sounds into a lower dimensional description.

SUMMARY Contrast invariant orientation tuning in simple cells of the visual cortex depends critically on contrast dependent trial-to-trial variability in their membrane potential responses. This observation raises the question of whether this variability originates from within the cortical circuit or the feedforward inputs from the lateral geniculate nucleus (LGN). To distinguish between these two sources of variability, we first measured membrane potential responses while inactivating the surrounding cortex, and found that response variability was nearly unaffected. We then studied variability in the LGN, including contrast dependence, and the trial-to-trial correlation in responses between nearby neurons. Variability decreased significantly with contrast, whereas correlation changed little. When these experimentally measured parameters of variability were applied to a feedforward model of simple cells that included realistic mechanisms of synaptic integration, contrast-dependent, orientation independent variability emerged in the membrane potential responses. Analogous mechanisms might contribute to the stimulus dependence and propagation of variability throughout the neocortex.