Population responses to multifrequency sounds in the cat auditory cortex: four-tone complexes

Input-Specific Gain Modulation by Local Sensory Context Shapes Cortical and Thalamic Responses to Complex Sounds

Sensory neurons are customarily characterized by one or more linearly weighted receptive fields describing sensitivity in sensory space and time. We show that in auditory cortical and thalamic neurons, the weight of each receptive field element depends on the pattern of sound falling within a local neighborhood surrounding it in time and frequency. Accounting for this change in effective receptive field with spectrotemporal context improves predictions of both cortical and thalamic responses to stationary complex sounds. Although context dependence varies among neurons and across brain areas, there are strong shared qualitative characteristics. In a spectrotemporally rich soundscape, sound elements modulate neuronal responsiveness more effectively when they coincide with sounds at other frequencies, and less effectively when they are preceded by sounds at similar frequencies. This local-context-driven lability in the representation of complex sounds—a modulation of “input-specific gain” rather than “output gain”—may be a widespread motif in sensory processing.

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Gain of neuronal responses to sound components varies with immediate acoustic context

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“Contextual gain fields” can be estimated from neuronal responses to complex sounds

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Coincident sound at different frequencies boosts gain in cortex and thalamus

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Preceding sound at similar frequency reduces gain for longer in cortex than thalamus

Perinatal asphyxia affects rat auditory processing: implications for auditory perceptual impairments in neurodevelopmental disorders

Perinatal asphyxia, a naturally and commonly occurring risk factor in birthing, represents one of the major causes of neonatal encephalopathy with long term consequences for infants. Here, degraded spectral and temporal responses to sounds were recorded from neurons in the primary auditory cortex (A1) of adult rats exposed to asphyxia at birth. Response onset latencies and durations were increased. Response amplitudes were reduced. Tuning curves were broader. Degraded successive-stimulus masking inhibitory mechanisms were associated with a reduced capability of neurons to follow higher-rate repetitive stimuli. The architecture of peripheral inner ear sensory epithelium was preserved, suggesting that recorded abnormalities can be of central origin. Some implications of these findings for the genesis of language perception deficits or for impaired language expression recorded in developmental disorders, such as autism spectrum disorders, contributed to by perinatal asphyxia, are discussed.

Complex spectral interactions encoded by auditory cortical neurons: relationship between bandwidth and pattern

The focus of most research on auditory cortical neurons has concerned the effects of rather simple stimuli, such as pure tones or broad-band noise, or the modulation of a single acoustic parameter. Extending these findings to feature coding in more complex stimuli such as natural sounds may be difficult, however. Generalizing results from the simple to more complex case may be complicated by non-linear interactions occurring between multiple, simultaneously varying acoustic parameters in complex sounds. To examine this issue in the frequency domain, we performed a parametric study of the effects of two global features, spectral pattern (here ripple frequency) and bandwidth, on primary auditory (A1) neurons in awake macaques. Most neurons were tuned for one or both variables and most also displayed an interaction between bandwidth and pattern implying that their effects were conditional or interdependent. A spectral linear filter model was able to qualitatively reproduce the basic effects and interactions, indicating that a simple neural mechanism may be able to account for these interdependencies. Our results suggest that the behavior of most A1 neurons is likely to depend on multiple parameters, and so most are unlikely to respond independently or invariantly to specific acoustic features.

Nonlinear spectrotemporal interactions underlying selectivity for complex sounds in auditory cortex

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 how temporally and spectrally specific nonlinear integration of putative tone-tuned inputs might underlie a diverse range of high selectivity of A1 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.

Receptive field for dorsal cochlear nucleus neurons at multiple sound levels

Neurons in the dorsal cochlear nucleus (DCN) exhibit nonlinearities in spectral processing, which make it difficult to predict the neurons' responses to stimuli. Here, we consider two possible sources of nonlinearity: nonmonotonic responses as sound level increases due to inhibition and interactions between frequency components. A spectral weighting function model of rate responses is used; the model approximates the neuron's rate response as a weighted sum of the frequency components of the stimulus plus a second-order sum that captures interactions between frequencies. Such models approximate DCN neurons well at low spectral contrast, i.e., when the SD (contrast) of the stimulus spectrum is limited to 3 dB. This model is compared with a first-order sum with weights that are explicit functions of sound level, so that the low-contrast model is extended to spectral contrasts of 12 dB, the range of natural stimuli. The sound-level-dependent weights improve prediction performance at large spectral contrast. However, the interactions between frequencies, represented as second-order terms, are more important at low spectral contrast. The level-dependent model is shown to predict previously described patterns of responses to spectral edges, showing that small changes in the inhibitory components of the receptive field can produce large changes in the responses of the neuron to features of natural stimuli. These results provide an effective way of characterizing nonlinear auditory neurons incorporating stimulus-dependent sensitivity changes. Such models could be used for neurons in other sensory systems that show similar effects.

Development of spectral and temporal response selectivity in the auditory cortex

The mechanisms by which hearing selectivity is elaborated and refined in early development are very incompletely determined. In this study, we documented contributions of progressively maturing inhibitory influences on the refinement of spectral and temporal response properties in the primary auditory cortex. Inhibitory receptive fields (IRFs) of infant rat auditory cortical neurons were spectrally far broader and had extended over far longer duration than did those of adults. The selective refinement of IRFs was delayed relative to that of excitatory receptive fields by an approximately 2-week period that corresponded to the critical period for plasticity. Local application of a GABA(A) receptor antagonist revealed that intracortical inhibition contributes to this progressive receptive field maturation for response selectivity in frequency. Conversely, it had no effect on the duration of IRFs or successive-signal cortical response recovery times. The importance of exposure to patterned acoustic inputs was suggested when both spectral and temporal IRF maturation were disrupted in rat pups reared in continuous, moderate-intensity noise. They were subsequently renormalized when animals were returned to standard housing conditions as adults.

Adaptive stimulus optimization for auditory cortical neurons

Despite the extensive physiological work performed on auditory cortex, our understanding of the basic functional properties of auditory cortical neurons is incomplete. For example, it remains unclear what stimulus features are most important for these cells. Determining these features is challenging given the considerable size of the relevant stimulus parameter space as well as the unpredictable nature of many neurons' responses to complex stimuli due to nonlinear integration across frequency. Here we used an adaptive stimulus optimization technique to obtain the preferred spectral input for neurons in macaque primary auditory cortex (AI). This method uses a neuron's response to progressively modify the frequency composition of a stimulus to determine the preferred spectrum. This technique has the advantage of being able to incorporate nonlinear stimulus interactions into a "best estimate" of a neuron's preferred spectrum. The resulting spectra displayed a consistent, relatively simple circumscribed form that was similar across scale and frequency in which excitation and inhibition appeared about equally prominent. In most cases, this structure could be described using two simple models, the Gabor and difference of Gaussians functions. The findings indicate that AI neurons are well suited for extracting important scale-invariant features in sound spectra and suggest that they are designed to efficiently represent natural sounds.

Interaction of Excitatory and Inhibitory Frequency-receptive Fields in Determining Fundamental Frequency Sensitivity of Primary Auditory Cortex Neurons in Awake Cats

Harmonic complex tones produce pitch-height perception corresponding to the fundamental frequency (F0). This study investigates how the spectral cue of F0 is processed in neurons of the primary auditory cortex (A1) with sustained-response properties. We found F0-sensitive and -insensitive cells: the former discriminated between harmonics and noise, while the latter did not. F0-sensitive cells preferred F0s corresponding to the best frequency (BF) and 0.5 x BF. The F0-sensitivity to F0=0.5 x BF was preserved for missing F0, but abolished by eliminating both F0 and the second harmonic. The inhibitory subfield of the frequency-receptive field was restricted to the spectral region between the preferred harmonics in F0-sensitive cells, while it was frequency unspecific in F0-insensitive cells. We conclude that (i) A1 is well organized for discrimination between harmonics and noise; (ii) pitch-height is represented along with the tonotopic axis; (iii) all aspects of the sustained neural responses to harmonic and noise stimuli are consequences of spectral filtering; and (iv) although the observed cell behavior explains some psychophysical pitch perception behaviors, such as pitch-chroma (helical pitch perception with frequency elevation), pitch-level tolerance and adaptive behavior, F0-encoding in A1 remains at the incomplete perceptual level (dominance of the third to fifth harmonics for pitch strength is unexplainable by the cell behavior).

Spectral integration in A1 of awake primates: neurons with single- and multipeaked tuning characteristics

We investigated modulations by stimulus components placed outside of the classical receptive field in the primary auditory cortex (A1) of awake marmosets. Two classes of neurons were identified using single tone stimuli: neurons with single-peaked frequency tuning characteristics (147/185, 80%) and neurons with multipeaked frequency tuning characteristics (38/185, 20%), referred to as single- and multipeaked units, respectively. Each class of neurons was further studied using two-tone paradigms in which the frequency, intensity, and timing of the second tone were systematically varied while a unit was driven by the first tone placed at a unit's characteristic frequency (CF) if it was single-peaked or at one of multiple spectral peaks if it was multipeaked. The main findings were: 1) excitatory spectral peaks in the frequency tuning of the multipeaked units were often harmonically related. 2) Multipeaked units showed facilitation in their responses to combinations of two harmonically related tones placed at the spectral peaks of their frequency tuning. The two-tone facilitation was strongest for the simultaneously presented tones. 3) In 76 of 113 single-peaked units studied using the two-tone paradigm, facilitatory and/or inhibitory modulations by distant off-CF tones were observed. This distant inhibition differed from flanking (or side-band) inhibitions near CF. 4) In single-peaked units, the distant off-CF inhibitions were dominated by tones at frequencies that were harmonically related to the CF of a unit, whereas the facilitation by off-CF tones was observed for a wide range of frequencies. And 5) in both single- and multipeaked units, sound levels of two interacting tones determined whether the two tones produced excitation or inhibition. The largest facilitation was achieved by using two tones at their corresponding preferred sound levels. Together, these findings suggest that extracting or rejecting harmonically related components embedded in complex sounds may represent fundamental signal processing properties in different classes of A1 neurons.

Changes of AI receptive fields with sound density

Primates engage in auditory behaviors under a broad range of signal-to-noise conditions. In this study, optimal linear receptive fields were measured in alert primate primary auditory cortex (A1) in response to stimuli that vary in spectrotemporal density. As density increased, A1 excitatory receptive fields systematically changed. Receptive field sensitivity, expressed as the expected change in firing rate after a tone pip onset, decreased by an order of magnitude. Spectral selectivity more than doubled. Inhibitory subfields, which were rarely recorded at low sound densities, emerged at higher sound densities. The ratio of excitatory to inhibitory population strength changed from 14.4:1 to 1.4:1. At low sound densities, the sound associated with the evocation of an action potential from an A1 neuron was broad in spectrum and time. At high sound densities, a spike-evoking sound was more likely to be a spectral or temporal edge and was narrower in time and frequency range. Receptive fields were used to predict responses to a novel high-noise-density stimulus. The predictions were highly correlated with the actual responses to the 2-s complex sound excerpt. The structure of prediction failures revealed that neurons with prominent inhibitory fields had relatively poor linear predictions. Further, the finding that stochastic variance is limiting in prediction even after averaging 150 repetitions means that high-fidelity representations of simple sounds in A1 must be distributed over at least hundreds of neurons. Auditory context alters A1 responses across multiple parameter spaces; this presents a challenge for reconstructing neural codes.

Temporal coherence sensitivity in auditory cortex

Natural sounds often contain energy over a broad spectral range and consequently overlap in frequency when they occur simultaneously; however, such sounds under normal circumstances can be distinguished perceptually (e.g., the cocktail party effect). Sound components arising from different sources have distinct (i.e., incoherent) modulations, and incoherence appears to be one important cue used by the auditory system to segregate sounds into separately perceived acoustic objects. Here we show that, in the primary auditory cortex of awake marmoset monkeys, many neurons responsive to amplitude- or frequency-modulated tones at a particular carrier frequency [the characteristic frequency (CF)] also demonstrate sensitivity to the relative modulation phase between two otherwise identically modulated tones: one at CF and one at a different carrier frequency. Changes in relative modulation phase reflect alterations in temporal coherence between the two tones, and the most common neuronal response was found to be a maximum of suppression for the coherent condition. Coherence sensitivity was generally found in a narrow frequency range in the inhibitory portions of the frequency response areas (FRA), indicating that only some off-CF neuronal inputs into these cortical neurons interact with on-CF inputs on the same time scales. Over the population of neurons studied, carrier frequencies showing coherence sensitivity were found to coincide with the carrier frequencies of inhibition, implying that inhibitory inputs create the effect. The lack of strong coherence-induced facilitation also supports this interpretation. Coherence sensitivity was found to be greatest for modulation frequencies of 16-128 Hz, which is higher than the phase-locking capability of most cortical neurons, implying that subcortical neurons could play a role in the phenomenon. Collectively, these results reveal that auditory cortical neurons receive some off-CF inputs temporally matched and some temporally unmatched to the on-CF input(s) and respond in a fashion that could be utilized by the auditory system to segregate natural sounds containing similar spectral components (such as vocalizations from multiple conspecifics) based on stimulus coherence.

Spectrotemporal receptive fields in the lemniscal auditory thalamus and cortex

Receptive fields have been characterized independently in the lemniscal auditory thalamus and cortex, usually with spectrotemporally simple sounds tailored to a specific task. No studies have employed naturalistic stimuli to investigate the thalamocortical transformation in temporal, spectral, and aural domains simultaneously and under identical conditions. We recorded simultaneously in the ventral division of the medial geniculate body (MGBv) and in primary auditory cortex (AI) of the ketamine-anesthetized cat. Spectrotemporal receptive fields (STRFs) of single units (n = 387) were derived by reverse-correlation with a broadband and dynamically varying stimulus, the dynamic ripple. Spectral integration, as measured by excitatory bandwidth and spectral modulation preference, was similar across both stations (mean Q(1/e) thalamus = 5.8, cortex = 5.4; upper cutoff of spectral modulation transfer function, thalamus = 1.30 cycles/octave, cortex = 1.37 cycles/octave). Temporal modulation rates slowed by a factor of two from thalamus to cortex (mean preferred rate, thalamus = 32.4 Hz, cortex = 16.6 Hz; upper cutoff of temporal modulation transfer function, thalamus = 62.9 Hz, cortex = 37.4 Hz). We found no correlation between spectral and temporal integration properties, suggesting that the excitatory-inhibitory interactions underlying preference in each domain are largely independent. A small number of neurons in each station had highly asymmetric STRFs, evidence of frequency sweep selectivity, but the population showed no directional bias. Binaural preferences differed in their relative proportions, most notably an increased prevalence of excitatory contralateral-only cells in cortex (40%) versus thalamus (23%), indicating a reorganization of this parameter. By comparing simultaneously along multiple stimulus dimensions in both stations, these observations establish the global characteristics of the thalamocortical receptive field transformation.

The auditory ‘C-process’: analyzing the spectral envelope of complex sounds

OBJECTIVE

To examine the hypothesis that auditory evoked potentials (AEPs) to pitch and timbre change of complex harmonic tones reflect a process of spectral envelope analysis.

METHODS

AEPs were recorded to: (1) continuous tones of 'clarinet' timbre whose pitch abruptly rose or fell by 1 or 7 semitones every 0.5 or 1.5 s; (2) a cycle of 6 pitches changing every 0.5 s; (3) tones of constant pitch whose timbre (spectral envelope shape) changed periodically; (4) pitch change of high- and low-pass filtered 'clarinet' tones.

RESULTS

The amplitudes of the 'change-N1' (CN1) potential peaking at ca. 90 ms and the following CP2 were influenced to a far greater degree by the time interval between changes, than by the magnitude of the change or by the time interval between occurrences of the same pitch. Amplitudes were also strongly dependent on the number of partials present, irrespective of whether they were increasing or decreasing in energy. The algebraic sum of the responses to pitch change of high- and low-pass filtered tones closely approximated the response to the unfiltered tone.

CONCLUSION

The rate-sensitivity of the responses cannot be explained by the refractoriness of frequency-specific 'feature detector' neurones, but rather of a process (termed 'C-process') which analyzes amplitude modulations across the spectral envelope, the contribution of different frequency bands combining linearly in the scalp-recorded activity. On-going computation of the spectral envelope shape may be an important factor in maintaining the perceptual constancy of timbre.

Relating cluster and population responses to natural sounds and tonal stimuli in cat primary auditory cortex

Most information about neuronal properties in primary auditory cortex (AI) has been gathered using simple artificial sounds such as pure tones and broad-band noise. These sounds are very different from the natural sounds that are processed by the auditory system in real world situations. In an attempt to bridge this gap, simple tonal stimuli and a standard set of six natural sounds were used to create models relating the responses of neuronal clusters in AI of barbiturate-anesthetized cats to the two classes of stimuli. A significant correlation was often found between the response to the separate frequency components of the natural sounds and the response to the natural sound itself. At the population level, this correlation resulted in a rate profile that represented robustly the spectral profiles of the natural sounds. There was however a significant scatter in the responses to the natural sound around the predictions based on the responses to tonal stimuli. Going the other way, in order to understand better the non-linearities in the responses to natural sounds, responses of neuronal clusters were characterized using second order Volterra kernel analysis of their responses to natural sounds. This characterization predicted reasonably well the amplitude of the response to other natural sounds, but could not reproduce the responses to tonal stimuli. Thus, second order non-linear characterizations, at least those using the Volterra kernel model, do not interpolate well between responses to tones and to natural sounds in auditory cortex.

Modular organization of frequency integration in primary auditory cortex

Two fundamental aspects of frequency analysis shape the functional organization of primary auditory cortex. For one, the decomposition of complex sounds into different frequency components is reflected in the tonotopic organization of auditory cortical fields. Second, recent findings suggest that this decomposition is carried out in parallel for a wide range of frequency resolutions by neurons with frequency receptive fields of different sizes (bandwidths). A systematic representation of the range of frequency resolution and, equivalently, spectral integration shapes the functional organization of the iso-frequency domain. Distinct subregions, or "modules," along the iso-frequency domain can be demonstrated with various measures of spectral integration, including pure-tone tuning curves, noise masking, and electrical cochlear stimulation. This modularity in the representation of spectral integration is expressed by intrinsic cortical connections. This organization has implications for our understanding of psychophysical spectral integration measures such as the critical band and general cortical coding strategies.

Organization of inhibitory frequency receptive fields in cat primary auditory cortex

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.

Spectral envelope coding in cat primary auditory cortex: linear and non-linear effects of stimulus characteristics

Electrophysiological studies in mammal primary auditory cortex have demonstrated neuronal tuning and cortical spatial organization based upon spectral and temporal qualities of the stimulus including: its frequency, intensity, amplitude modulation and frequency modulation. Although communication and other behaviourally relevant sounds are usually complex, most response characterizations have used tonal stimuli. To better understand the mechanisms necessary to process complex sounds, we investigated neuronal responses to a specific class of broadband stimuli, auditory gratings or ripple stimuli, and compared the responses with single tone responses. Ripple stimuli consisted of 150-200 frequency components with the intensity of each component adjusted such that the envelope of the frequency spectrum is sinusoidal. It has been demonstrated that neurons are tuned to specific characteristics of those ripple stimulus including the intensity, the spacing of the peaks, and the location of the peaks and valleys (C. E. Schreiner and B. M. Calhoun, Auditory Neurosci., 1994; 1: 39-61). Although previous results showed that neuronal response strength varied with the intensity and the fundamental frequency of the stimulus, it is shown here that the relative response to different ripple spacings remains essentially constant with changes in the intensity and the fundamental frequency. These findings support a close relationship between pure-tone receptive fields and ripple transfer functions. However, variations of other stimulus characteristics, such as spectral modulation depth, result in non-linear alterations in the ripple transformation. The processing between the basilar membrane and the primary auditory cortex of broadband stimuli appears generally to be non-linear, although specific stimulus qualities, including the phase of the spectral envelope, are processed in a nearly linear manner.

Orderly cortical representation of vowels based on formant interaction

Psychophysical experiments have shown that the discrimination of human vowels chiefly relies on the frequency relationship of the first two peaks F1 and F2 of the vowel's spectral envelope. It has not been possible, however, to relate the two-dimensional (F1, F2)-relationship to the known organization of frequency representation in auditory cortex. We demonstrate that certain spectral integration properties of neurons are topographically organized in primary auditory cortex in such a way that a transformed (F1,F2) relationship sufficient for vowel discrimination is realized.

Linear and nonlinear spectral integration in type IV neurons of the dorsal cochlear nucleus. II. Predicting responses with the use of nonlinear models

Two nonlinear modeling methods were used to characterize the input/output relationships of type IV units, which are one principal cell type in the dorsal cochlear nucleus (DCN). In both cases, the goal was to derive predictive models, i.e., models that could predict the responses to other stimuli. In one method, frequency integration was estimated from response maps derived from single tones and simultaneous pairs of tones presented over a range of frequencies. This model combined linear integration of energy across frequency and nonlinear interactions of energy at different frequencies. The model was used to predict responses to noisebands with varying width and center frequency. In almost all cases, predictions using two-tone interactions were better than linear predictions based on single-tone responses only. In about half the cases, reasonable quantitative fits were achieved. The fits were best for noisebands with narrow bandwidth and low sound levels. In the second nonlinear method, the spectrotemporal receptive field (STRF) was derived from responses to broadband stimuli. The STRF could account for some qualitative features of the responses to broad noisebands and spectral notches embedded in broad noisebands. Quantitatively, however, the STRFs failed to predict the responses of type IV units even to simple broadband noise stimuli. For narrowband stimuli, the STRF failed to predict even qualitative features (such as excitatory and inhibitory frequency bands). The responses of DCN type IV units presumably result from interactions of two inhibitory sources, a strong one that is preferentially activated by narrowband stimuli and a weaker one that is preferentially activated by broadband stimuli. The results presented here suggest that the STRF measures effects related to the broadband inhibition, whereas two-tone interactions measure mostly effects related to narrowband inhibition. This explains why models based on two-tone interactions predict the responses to narrow noisebands much better then models based on STRFs. It is concluded that a minimal stimulus set for characterizing type IV units must contain both broadband and narrowband stimuli, because each stimulus class by itself activates only partially the integration mechanisms that shape the responses of type IV units. Similar conclusions are expected to hold in other parts of the auditory system: when characterizing a complex auditory unit, it is necessary to use a range of stimuli to ensure that all integration mechanisms are activated.

Order and disorder in auditory cortical maps

Recent physiological experiments suggest that several basic receptive field properties of neurons show non-uniform spatial distributions in the primary auditory cortex of cats and primates. The spatial distribution patterns of some of these receptive field parameters are suggestive of a parallel coding scheme for processing sound information onto several superimposed cortical 'maps'. The representations of these parameters in the auditory cortex are compatible with general features of self-organizing mapping algorithms, as the spatial representations exhibit global parameter gradients with overlaid functional patchiness. Recent studies have also revealed that within a 'representational' map, the degree of local coherence varies over a wide range and that the map can contain a substantial degree of disorder in its parametric representation of sounds. Although the causes and consequences of this representational disorder are not known, it may reflect yet unresolved organizational principles in the auditory cortex.

Population responses to multifrequency sounds in the cat auditory cortex: one- and two-parameter families of sounds

Population responses to multi-frequency sounds were recorded in primary auditory cortex of anesthetized cats. The sounds consisted of single-tone stimuli; two-tone stimuli; and nine-tone stimuli, with the tones evenly spaced on a linear frequency scale. The stimuli were presented through a sealed, calibrated sound delivery system. Single units, cluster activity (CA) and the short-time mean absolute value of the envelope of the neural signal (MABS) were recorded extracellularly from six microelectrodes simultaneously. The CA and MABS were interpreted as measures of the activity of large populations of neurons, in contrast with the single unit activity which is presumably recorded from single neurons. The responses of the MABS signal to simple stimuli were generally similar to those of the CA, but were more stable statistically. Thus, the MABS is better suited for studying the activity of populations of neurons. The responses to tones near the best frequency were strongly influenced by a second tone, even when the second tone was outside the single-tone response area. These influences could be both facilitatory and suppressory. They could not be predicted from the responses to single tones. The responses to the nine-tone stimuli could be explained qualitatively by the responses to the two-tone stimuli. It is concluded that the population responses in primary auditory cortex are shaped by the contributions of the individual frequencies appearing in the stimulus and by the interactions between pairs of frequencies. Interactions between stimulus components are therefore a necessary component of any attempt to explain the processing of complex sounds in the auditory cortex. They may play a role in a global representation of the stimulus spectrum in the primary auditory cortex. The presence of higher-order interactions cannot be excluded by the results presented here.

In search of the best stimulus: an optimization procedure for finding efficient stimuli in the cat auditory cortex

Units in the auditory cortex of cats respond to a large variety of stimuli: pure tones, AM- and FM-modulated signals, clicks, wideband noise, natural sounds, and more. However, no single family of sounds was found to be optimal (in the sense that oriented lines are optimal in the visual cortex). The search for optimal complex sounds is hard because of the high dimensionality of the space of interesting sounds. In an effort to overcome this problem, an automatic search procedure for finding efficient stimuli in high-dimensional sound spaces was developed. This procedure chooses the stimuli to be presented according to the responses to past stimuli, trying to increase the strength of the response. The results of applying this method to recordings of population activity in the primary auditory cortex of cats are described. The search was applied to single tones, two-tone stimuli, four-tone stimuli and to a two-dimensional subset of nine-tone stimuli, parametrized by the center frequency and the fixed difference between adjacent frequencies. The method was able to find efficient stimuli, and its performance improved with the dimension of the sound spaces. Efficient stimuli, found in different optimization runs using population activity recorded from the same electrode, often shared similar frequencies and pairs of frequencies, and tended to evoke similar levels of activity. This result indicates that a global analysis of the location of spectral peaks is performed at the level of the auditory cortex.