Because we can perceive the pitch, timbre, and spatial location of a sound source independently, it seems natural to suppose that cortical processing of sounds might separate out spatial from nonspatial attributes. Indeed, recent studies support the existence of anatomically segregated "what" and "where" cortical processing streams. However, few attempts have been made to measure the responses of individual neurons in different cortical fields to sounds that vary simultaneously across spatial and nonspatial dimensions. We recorded responses to artificial vowels presented in virtual acoustic space to investigate the representations of pitch, timbre, and sound source azimuth in both core and belt areas of ferret auditory cortex. A variance decomposition technique was used to quantify the way in which altering each parameter changed neural responses. Most units were sensitive to two or more of these stimulus attributes. Although indicating that neural encoding of pitch, location, and timbre cues is distributed across auditory cortex, significant differences in average neuronal sensitivity were observed across cortical areas and depths, which could form the basis for the segregation of spatial and nonspatial cues at higher cortical levels. Some units exhibited significant nonlinear interactions between particular combinations of pitch, timbre, and azimuth. These interactions were most pronounced for pitch and timbre and were less commonly observed between spatial and nonspatial attributes. Such nonlinearities were most prevalent in primary auditory cortex, although they tended to be small compared with stimulus main effects.

We can recognize the melody of a familiar song when it is played on different musical instruments. Similarly, an animal must be able to recognize a warning call whether the caller has a high-pitched female or a lower-pitched male voice, and whether they are sitting in a tree to the left or right. This type of perceptual invariance to "nuisance" parameters comes easily to listeners, but it is unknown whether or how such robust representations of sounds are formed at the level of sensory cortex. In this study, we investigate whether neurons in both core and belt areas of ferret auditory cortex can robustly represent the pitch, formant frequencies, or azimuthal location of artificial vowel sounds while the other two attributes vary. We found that the spike rates of the majority of cortical neurons that are driven by artificial vowels carry robust representations of these features, but the most informative temporal response windows differ from neuron to neuron and across five auditory cortical fields. Furthermore, individual neurons can represent multiple features of sounds unambiguously by independently modulating their spike rates within distinct time windows. Such multiplexing may be critical to identifying sounds that vary along more than one perceptual dimension. Finally, we observed that formant information is encoded in cortex earlier than pitch information, and we show that this time course matches ferrets' behavioral reaction time differences on a change detection task.

SummaryThe neural processing of sensory stimuli involves a transformation of physical stimulus parameters into perceptual features, and elucidating where and how this transformation occurs is one of the ultimate aims of sensory neurophysiology. Recent studies have shown that the firing of neurons in early sensory cortex can be modulated by multisensory interactions [1–5], motor behavior [1, 3, 6, 7], and reward feedback [1, 8, 9], but it remains unclear whether neural activity is more closely tied to perception, as indicated by behavioral choice, or to the physical properties of the stimulus. We investigated which of these properties are predominantly represented in auditory cortex by recording local field potentials (LFPs) and multiunit spiking activity in ferrets while they discriminated the pitch of artificial vowels. We found that auditory cortical activity is informative both about the fundamental frequency (F0) of a target sound and also about the pitch that the animals appear to perceive given their behavioral responses. Surprisingly, although the stimulus F0 was well represented at the onset of the target sound, neural activity throughout auditory cortex frequently predicted the reported pitch better than the target F0.

We measured the responses of neurons in auditory cortex of male and female ferrets to artificial vowels of varying fundamental frequency ( f 0 ), or periodicity, and compared these with the performance of animals trained to discriminate the periodicity of these sounds. Sensitivity to f 0 was found in all five auditory cortical fields examined, with most of those neurons exhibiting either low-pass or high-pass response functions. Only rarely was the stimulus dependence of individual neuron discharges sufficient to account for the discrimination performance of the ferrets. In contrast, when analyzed with a simple classifier, responses of small ensembles, comprising 3-61 simultaneously recorded neurons, often discriminated periodicity changes as well as the animals did. We examined four potential strategies for decoding ensemble responses: spike counts, relative first-spike latencies, a binary "spike or no-spike" code, and a spike-order code. All four codes represented stimulus periodicity effectively, and, surprisingly, the spike count and relative latency codes enabled an equally rapid readout, within 75 ms of stimulus onset. Thus, relative latency codes do not necessarily facilitate faster discrimination judgments. A joint spike count plus relative latency code was more informative than either code alone, indicating that the information captured by each measure was not wholly redundant. The responses of neural ensembles, but not of single neurons, reliably encoded f 0 changes even when stimulus intensity was varied randomly over a 20 dB range. Because trained animals can discriminate stimulus periodicity across different sound levels, this implies that ensemble codes are better suited to account for behavioral performance.

Although many studies have examined the performance of animals in detecting a frequency change in a sequence of tones, few have measured animals' discrimination of the fundamental frequency (F0) of complex, naturalistic stimuli. Additionally, it is not yet clear if animals perceive the pitch of complex sounds along a continuous, low-to-high scale. Here, four ferrets (Mustela putorius) were trained on a two-alternative forced choice task to discriminate sounds that were higher or lower in F0 than a reference sound, using pure tones and artificial vowels as stimuli. Average Weber fractions for ferrets on this task varied from ~20 -80% across references (200 -1200 Hz), and these fractions were similar for pure tones and vowels. These thresholds are approximately 10 times higher than those typically reported for other mammals on frequency change detection tasks that use go/no-go designs. Naive human listeners outperformed ferrets on the present task, but they showed similar effects of stimulus type and reference F0. These results suggest that while non-human animals can be trained to label complex sounds as high or low in pitch, this task may be much more difficult for animals than simply detecting a frequency change.

No abstract

Despite decades of microelectrode recordings, fundamental questions remain about how auditory cortex represents sound-source location. Here, we used in vivo 2-photon calcium imaging to measure the sensitivity of layer II/III neurons in mouse primary auditory cortex (A1) to interaural level differences (ILDs), the principal spatial cue in this species. Although most ILD-sensitive neurons preferred ILDs favoring the contralateral ear, neurons with either midline or ipsilateral preferences were also present. An opponent-channel decoder accurately classified ILDs using the difference in responses between populations of neurons that preferred contralateral-ear-greater and ipsilateral-ear-greater stimuli. We also examined the spatial organization of binaural tuning properties across the imaged neurons with unprecedented resolution. Neurons driven exclusively by contralateral ear stimuli or by binaural stimulation occasionally formed local clusters, but their binaural categories and ILD preferences were not spatially organized on a more global scale. In contrast, the sound frequency preferences of most neurons within local cortical regions fell within a restricted frequency range, and a tonotopic gradient was observed across the cortical surface of individual mice. These results indicate that the representation of ILDs in mouse A1 is comparable to that of most other mammalian species, and appears to lack systematic or consistent spatial order.

It is widely appreciated that the key predictor of the pitch of a sound is its periodicity. Neural structures which support pitch perception must therefore be able to reflect the repetition rate of a sound, but this alone is not sufficient. Since pitch is a psychoacoustic property, a putative cortical code for pitch must also be able to account for the relationship between the amount to which a sound is periodic (i.e. its temporal regularity) and the perceived pitch salience, as well as limits in our ability to detect pitch changes or to discriminate rising from falling pitch. Pitch codes must also be robust in the presence of nuisance variables such as loudness or timbre. Here, we review a large body of work on the cortical basis of pitch perception, which illustrates that the distribution of cortical processes that give rise to pitch perception is likely to depend on both the acoustical features and functional relevance of a sound. While previous studies have greatly advanced our understanding, we highlight several open questions regarding the neural basis of pitch perception. These questions can begin to be addressed through a cooperation of investigative efforts across species and experimental techniques, and, critically, by examining the responses of single neurons in behaving animals.