Frequency and space representation in the primary auditory cortex of the frequency modulating batEptesicus fuscus

1. Frequency and space representation in the auditory cortex of the big brown bat, Eptesicus fuscus, were studied by recording responses of 223 neurons to acoustic stimuli presented in the bat's frontal auditory space. 2. The majority of the auditory cortical neurons were recorded at a depth of less than 500 microns with a response latency between 8 and 20 ms. They generally discharged phasically and had nonmonotonic intensity-rate functions. The minimum threshold, (MT) of these neurons was between 8 and 82 dB sound pressure level (SPL). Half of the cortical neurons showed spontaneous activity. All 55 threshold curves are V-shaped and can be described as broad, intermediate, or narrow. 3. Auditory cortical neurons are tonotopically organized along the anteroposterior axis of the auditory cortex. High-frequency-sensitive neurons are located anteriorly and low-frequency-sensitive neurons posteriorly. An overwhelming majority of neurons were sensitive to a frequency range between 30 and 75 kHz. 4. When a sound was delivered from the response center of a neuron on the bat's frontal auditory space, the neuron had its lowest MT. When the stimulus amplitude was increased above the MT, the neuron responded to sound delivered within a defined spatial area. The response center was not always at the geometric center of the spatial response area. The latter also expanded with stimulus amplitude. High-frequency-sensitive neurons tended to have smaller spatial response areas than low-frequency-sensitive neurons. 5. Response centers of all 223 neurons were located between 0 degrees and 50 degrees in azimuth, 2 degrees up and 25 degrees down in elevation of the contralateral frontal auditory space. Response centers of auditory cortical neurons tended to move toward the midline and slightly downward with increasing best frequency. 6. Auditory space representation appears to be systematically arranged according to the tonotopic axis of the auditory cortex. Thus, the lateral space is represented posteriorly and the middle space anteriorly. Space representation, however, is less systematic in the vertical direction. 7. Auditory cortical neurons are columnarly organized. Thus, the BFs, MTs, threshold curves, azimuthal location of response centers, and auditory spatial response areas of neurons sequentially isolated from an orthogonal electrode penetration are similar.     

Selective and Efficient Neural Coding of Communication Signals Depends on Early Acoustic and Social Environment

Previous research has shown that postnatal exposure to simple, synthetic sounds can affect the sound representation in the auditory cortex as reflected by changes in the tonotopic map or other relatively simple tuning properties, such as AM tuning. However, their functional implications for neural processing in the generation of ethologically-based perception remain unexplored. Here we examined the effects of noise-rearing and social isolation on the neural processing of communication sounds such as species-specific song, in the primary auditory cortex analog of adult zebra finches. Our electrophysiological recordings reveal that neural tuning to simple frequency-based synthetic sounds is initially established in all the laminae independent of patterned acoustic experience; however, we provide the first evidence that early exposure to patterned sound statistics, such as those found in native sounds, is required for the subsequent emergence of neural selectivity for complex vocalizations and for shaping neural spiking precision in superficial and deep cortical laminae, and for creating efficient neural representations of song and a less redundant ensemble code in all the laminae. Our study also provides the first causal evidence for ‘sparse coding’, such that when the statistics of the stimuli were changed during rearing, as in noise-rearing, that the sparse or optimal representation for species-specific vocalizations disappeared. Taken together, these results imply that a layer-specific differential development of the auditory cortex requires patterned acoustic input, and a specialized and robust sensory representation of complex communication sounds in the auditory cortex requires a rich acoustic and social environment.     

Neural Resolution of Formant Frequencies in the Primary Auditory Cortex of Rats

Pulse-resonance sounds play an important role in animal communication and auditory object recognition, yet very little is known about the cortical representation of this class of sounds. In this study we shine light on one simple aspect: how well does the firing rate of cortical neurons resolve resonant (“formant”) frequencies of vowel-like pulse-resonance sounds. We recorded neural responses in the primary auditory cortex (A1) of anesthetized rats to two-formant pulse-resonance sounds, and estimated their formant resolving power using a statistical kernel smoothing method which takes into account the natural variability of cortical responses. While formant-tuning functions were diverse in structure across different penetrations, most were sensitive to changes in formant frequency, with a frequency resolution comparable to that reported for rat cochlear filters.     

Location coding by opponent neural populations in the auditory cortex

Although the auditory cortex plays a necessary role in sound localization, physiological investigations in the cortex reveal inhomogeneous sampling of auditory space that is difficult to reconcile with localization behavior under the assumption of local spatial coding. Most neurons respond maximally to sounds located far to the left or right side, with few neurons tuned to the frontal midline. Paradoxically, psychophysical studies show optimal spatial acuity across the frontal midline. In this paper, we revisit the problem of inhomogeneous spatial sampling in three fields of cat auditory cortex. In each field, we confirm that neural responses tend to be greatest for lateral positions, but show the greatest modulation for near-midline source locations. Moreover, identification of source locations based on cortical responses shows sharp discrimination of left from right but relatively inaccurate discrimination of locations within each half of space. Motivated by these findings, we explore an opponent-process theory in which sound-source locations are represented by differences in the activity of two broadly tuned channels formed by contra- and ipsilaterally preferring neurons. Finally, we demonstrate a simple model, based on spike-count differences across cortical populations, that provides bias-free, level-invariant localization—and thus also a solution to the “binding problem” of associating spatial information with other nonspatial attributes of sounds.     

弱背景噪声对大鼠听皮层神经元频率调谐的影响

在自然环境中,人和动物常在一定的背景噪声下感知信号声刺激,然而,关于低强度的弱背景噪声如何影响听皮层神经元对声刺激频率的编码尚不清楚.本研究以大鼠听皮层神经元的频率反应域为研究对象,测定了阈下背景噪声对79个神经元频率反应域的影响.结果表明,弱背景噪声对大鼠初级听皮层神经元的听反应既有抑制性影响、又有易化性影响.一般来说,抑制性影响使神经元的频率调谐范围和最佳频率反应域缩小,易化性影响使神经元的频率调谐范围和最佳频率反应域增大.对于少数神经元,弱背景噪声并未显著改变其频率调谐范围,但却改变了其最佳频率反应域范围.弱背景噪声对63.64%神经元的特征频率和55.84%神经元的最低阈值无显著影响.神经元频率调谐曲线的尖部比中部更容易受到弱背景噪声的影响.该研究结果有助于我们进一步理解复杂声环境下大脑听皮层对听觉信息的编码机制.     

Neural representation of spectral and temporal information in speech

Speech is the most interesting and one of the most complex sounds dealt with by the auditory system. The neural representation of speech needs to capture those features of the signal on which the brain depends in language communication. Here we describe the representation of speech in the auditory nerve and in a few sites in the central nervous system from the perspective of the neural coding of important aspects of the signal. The representation is tonotopic, meaning that the speech signal is decomposed by frequency and different frequency components are represented in different populations of neurons. Essential to the representation are the properties of frequency tuning and nonlinear suppression. Tuning creates the decomposition of the signal by frequency, and nonlinear suppression is essential for maintaining the representation across sound levels. The representation changes in central auditory neurons by becoming more robust against changes in stimulus intensity and more transient. However, it is probable that the form of the representation at the auditory cortex is fundamentally different from that at lower levels, in that stimulus features other than the distribution of energy across frequency are analysed.     

Encoding of Natural Sounds at Multiple Spectral and Temporal Resolutions in the Human Auditory Cortex

Functional neuroimaging research provides detailed observations of the response patterns that natural sounds (e.g. human voices and speech, animal cries, environmental sounds) evoke in the human brain. The computational and representational mechanisms underlying these observations, however, remain largely unknown. Here we combine high spatial resolution (3 and 7 Tesla) functional magnetic resonance imaging (fMRI) with computational modeling to reveal how natural sounds are represented in the human brain. We compare competing models of sound representations and select the model that most accurately predicts fMRI response patterns to natural sounds. Our results show that the cortical encoding of natural sounds entails the formation of multiple representations of sound spectrograms with different degrees of spectral and temporal resolution. The cortex derives these multi-resolution representations through frequency-specific neural processing channels and through the combined analysis of the spectral and temporal modulations in the spectrogram. Furthermore, our findings suggest that a spectral-temporal resolution trade-off may govern the modulation tuning of neuronal populations throughout the auditory cortex. Specifically, our fMRI results suggest that neuronal populations in posterior/dorsal auditory regions preferably encode coarse spectral information with high temporal precision. Vice-versa, neuronal populations in anterior/ventral auditory regions preferably encode fine-grained spectral information with low temporal precision. We propose that such a multi-resolution analysis may be crucially relevant for flexible and behaviorally-relevant sound processing and may constitute one of the computational underpinnings of functional specialization in auditory cortex.     

Plasticity and corticofugal modulation for hearing in adult animals

The descending (corticofugal) auditory system adjusts and improves auditory signal processing in the subcortical auditory nuclei. The auditory cortex and corticofugal system evoke small, short-term changes of the subcortical auditory nuclei in response to a sound repetitively delivered to an animal. These changes are specific to the parameters characterizing the sound. When the sound becomes significant to the animal through conditioning (associative learning), the changes are augmented and the cortical changes become long-term. There are two types of reorganizations: expanded reorganization resulting from centripetal shifts in tuning curves of neurons toward the values of the parameters characterizing a sound and compressed reorganization resulting from centrifugal shifts in tuning curves of neurons away from these values. The two types of reorganizations are based on a single mechanism consisting of two components: facilitation and inhibition.     

Eye position influences auditory responses in primate inferior colliculus

We examined the frame of reference of auditory responses in the inferior colliculus in monkeys fixating visual stimuli at different locations. Eye position modulated the level of auditory responses in 33% of the neurons we encountered, but it did not appear to shift their spatial tuning. The effect of eye position on auditory responses was substantial-comparable in magnitude to that of sound location. The eye position signal appeared to interact with the auditory responses in at least a partly multiplicative fashion. We conclude that the representation of sound location in primate IC is distributed and that the frame of reference is intermediate between head- and eye-centered coordinates. The information contained in these neurons appears to be sufficient for later neural stages to calculate the positions of sounds with respect to the eyes.     

A Neural Model of Auditory Space Compatible with Human Perception under Simulated Echoic Conditions

In a typical auditory scene, sounds from different sources and reflective surfaces summate in the ears, causing spatial cues to fluctuate. Prevailing hypotheses of how spatial locations may be encoded and represented across auditory neurons generally disregard these fluctuations and must therefore invoke additional mechanisms for detecting and representing them. Here, we consider a different hypothesis in which spatial perception corresponds to an intermediate or sub-maximal firing probability across spatially selective neurons within each hemisphere. The precedence or Haas effect presents an ideal opportunity for examining this hypothesis, since the temporal superposition of an acoustical reflection with sounds arriving directly from a source can cause otherwise stable cues to fluctuate. Our findings suggest that subjects’ experiences may simply reflect the spatial cues that momentarily arise under various acoustical conditions and how these cues are represented. We further suggest that auditory objects may acquire “edges” under conditions when interaural time differences are broadly distributed.     

The function of the medial superior olive in small mammals: temporal receptive fields in auditory analysis

Traditionally, the medial superior olive, a mammalian auditory brainstem structure, is considered to encode interaural time differences, the main cue for localizing low-frequency sounds. Detection of binaural excitatory and inhibitory inputs are considered as an underlying mechanism. Most small mammals, however, hear high frequencies well beyond 50 kHz and have small interaural distances. Therefore, they can not use interaural time differences for sound localization and yet possess a medial superior olive. Physiological studies in bats revealed that medial superior olive cells show similar interaural time difference coding as in larger mammals tuned to low-frequency hearing. Their interaural time difference sensitivity, however, is far too coarse to serve in sound localization. Thus, interaural time difference sensitivity in medial superior olive of small mammals is an epiphenomenon. We propose that the original function of the medial superior olive is a binaural cooperation causing facilitation due to binaural excitation. Lagging inhibitory inputs, however, suppress reverberations and echoes from the acoustic background. Thereby, generation of antagonistically organized temporal fields is the basic and original function of the mammalian medial superior olive. Only later in evolution with the advent of larger mammals did interaural distances, and hence interaural time differences, became large enough to be used as cues for sound localization of low-frequency stimuli. Accepted: 28 February 2000     

Sparse codes for speech predict spectrotemporal receptive fields in the inferior colliculus

We have developed a sparse mathematical representation of speech that minimizes the number of active model neurons needed to represent typical speech sounds. The model learns several well-known acoustic features of speech such as harmonic stacks, formants, onsets and terminations, but we also find more exotic structures in the spectrogram representation of sound such as localized checkerboard patterns and frequency-modulated excitatory subregions flanked by suppressive sidebands. Moreover, several of these novel features resemble neuronal receptive fields reported in the Inferior Colliculus (IC), as well as auditory thalamus and cortex, and our model neurons exhibit the same tradeoff in spectrotemporal resolution as has been observed in IC. To our knowledge, this is the first demonstration that receptive fields of neurons in the ascending mammalian auditory pathway beyond the auditory nerve can be predicted based on coding principles and the statistical properties of recorded sounds.     

小鼠初级听皮质神经元的强度调谐特性与机制分析

强度是声音的基本参数之一,听神经元的强度调谐在听觉信息处理方面具有重要意义．以往研究发现γ-氨基丁酸(γ-aminobutyric acid, GABA)能抑制性输入在强度调谐的形成过程中起重要作用,但对抑制性输入与局部神经回路之间的关系并不清楚．本实验通过在体细胞外电生理记录和神经药理学方法,分析了小鼠初级听皮质神经元的强度调谐特性,结果显示：单调型神经元在声刺激强度自中等强度增高时潜伏期缩短(P < 0.05)且发放持续时间延长(P < 0.05),非单调型神经元在声刺激强度自最佳强度增高时潜伏期不变且发放持续时间缩短(P < 0.01)．注射GABA能阻断剂荷包牡丹碱(bicuculline, Bic)后,39.3%的神经元强度调谐类型不变,42.9%的神经元非单调性减弱,17.9%的神经元非单调性增强．表明GABA能抑制并非是形成非单调性的唯一因素,兴奋性输入本身的非单调性和高阈值非GABA能抑制的激活也可能在其中发挥作用．推测由兴奋性和抑制性输入所构成的局部神经功能回路及其整合决定了听皮质神经元的强度调谐特性．     

Distributed coding of sound locations in the auditory cortex

Although the auditory cortex plays an important role in sound localization, that role is not well understood. In this paper, we examine the nature of spatial representation within the auditory cortex, focusing on three questions. First, are sound-source locations encoded by individual sharply tuned neurons or by activity distributed across larger neuronal populations? Second, do temporal features of neural responses carry information about sound-source location? Third, are any fields of the auditory cortex specialized for spatial processing? We present a brief review of recent work relevant to these questions along with the results of our investigations of spatial sensitivity in cat auditory cortex. Together, they strongly suggest that space is represented in a distributed manner, that response timing (notably first-spike latency) is a critical information-bearing feature of cortical responses, and that neurons in various cortical fields differ in both their degree of spatial sensitivity and their manner of spatial coding. The posterior auditory field (PAF), in particular, is well suited for the distributed coding of space and encodes sound-source locations partly by modulations of response latency. Studies of neurons recorded simultaneously from PAF and/or A1 reveal that spatial information can be decoded from the relative spike times of pairs of neurons - particularly when responses are compared between the two fields - thus partially compensating for the absence of an absolute reference to stimulus onset.     

Coding of communication calls in the subcortical and cortical structures of the auditory system

The processing of species-specific communication signals in the auditory system represents an important aspect of animal behavior and is crucial for its social interactions, reproduction, and survival. In this article the neuronal mechanisms underlying the processing of communication signals in the higher centers of the auditory system--inferior colliculus (IC), medial geniculate body (MGB) and auditory cortex (AC)--are reviewed, with particular attention to the guinea pig. The selectivity of neuronal responses for individual calls in these auditory centers in the guinea pig is usually low--most neurons respond to calls as well as to artificial sounds; the coding of complex sounds in the central auditory nuclei is apparently based on the representation of temporal and spectral features of acoustical stimuli in neural networks. Neuronal response patterns in the IC reliably match the sound envelope for calls characterized by one or more short impulses, but do not exactly fit the envelope for long calls. Also, the main spectral peaks are represented by neuronal firing rates in the IC. In comparison to the IC, response patterns in the MGB and AC demonstrate a less precise representation of the sound envelope, especially in the case of longer calls. The spectral representation is worse in the case of low-frequency calls, but not in the case of broad-band calls. The emotional content of the call may influence neuronal responses in the auditory pathway, which can be demonstrated by stimulation with time-reversed calls or by measurements performed under different levels of anesthesia. The investigation of the principles of the neural coding of species-specific vocalizations offers some keys for understanding the neural mechanisms underlying human speech perception.     

Constructing Noise-Invariant Representations of Sound in the Auditory Pathway

Identifying behaviorally relevant sounds in the presence of background noise is one of the most important and poorly understood challenges faced by the auditory system. An elegant solution to this problem would be for the auditory system to represent sounds in a noise-invariant fashion. Since a major effect of background noise is to alter the statistics of the sounds reaching the ear, noise-invariant representations could be promoted by neurons adapting to stimulus statistics. Here we investigated the extent of neuronal adaptation to the mean and contrast of auditory stimulation as one ascends the auditory pathway. We measured these forms of adaptation by presenting complex synthetic and natural sounds, recording neuronal responses in the inferior colliculus and primary fields of the auditory cortex of anaesthetized ferrets, and comparing these responses with a sophisticated model of the auditory nerve. We find that the strength of both forms of adaptation increases as one ascends the auditory pathway. To investigate whether this adaptation to stimulus statistics contributes to the construction of noise-invariant sound representations, we also presented complex, natural sounds embedded in stationary noise, and used a decoding approach to assess the noise tolerance of the neuronal population code. We find that the code for complex sounds in the periphery is affected more by the addition of noise than the cortical code. We also find that noise tolerance is correlated with adaptation to stimulus statistics, so that populations that show the strongest adaptation to stimulus statistics are also the most noise-tolerant. This suggests that the increase in adaptation to sound statistics from auditory nerve to midbrain to cortex is an important stage in the construction of noise-invariant sound representations in the higher auditory brain.     

A corticothalamic circuit model for sound identification in complex scenes

The identification of the sound sources present in the environment is essential for the survival of many animals. However, these sounds are not presented in isolation, as natural scenes consist of a superposition of sounds originating from multiple sources. The identification of a source under these circumstances is a complex computational problem that is readily solved by most animals. We present a model of the thalamocortical circuit that performs level-invariant recognition of auditory objects in complex auditory scenes. The circuit identifies the objects present from a large dictionary of possible elements and operates reliably for real sound signals with multiple concurrently active sources. The key model assumption is that the activities of some cortical neurons encode the difference between the observed signal and an internal estimate. Reanalysis of awake auditory cortex recordings revealed neurons with patterns of activity corresponding to such an error signal.     

Direction-dependent corticofugal modulation of frequency-tuning curves of inferior collicular neurons in the big brown bat, Eptesicus fuscus

This study examined if corticofugal modulation of subcortical frequency-tuning curves varied with sound direction. Both excitatory and inhibitory frequency tuning curves of inferior collicular neurons of the big brown bat, Eptesicus fuscus were plotted before and during electrical stimulation in the auditory cortex at two sound directions (contra-40 degrees and ipsi-40 degrees). Most collicular neurons had broader excitatory frequency-tuning curves at contra-40 degrees but had broader inhibitory frequency-tuning curves at ipsi-40 degrees. Cortical electrical stimulation changed the excitatory minimum thresholds of most collicular neurons at a greater degree at ipsi-40 degrees than at contra-40 degrees. However, cortical electrical stimulation produced a greater increase in the sharpness of excitatory frequency-tuning curves of most corticofugally inhibited collicular neurons at contra-40 degrees but produced a greater decrease in the sharpness of excitatory frequency-tuning curves of most corticofugally facilitated collicular neurons at ipsi-40 degrees. Cortical electrical stimulation also produced a greater change in the sharpness of inhibitory frequency-tuning curves of most corticofugally inhibited collicular neurons at contra-40 degrees than at ipsi-40 degrees. Possible mechanisms for this direction-dependent corticofugal modulation of frequency-tuning curves of collicular neurons are discussed.     

Competing sound sources reveal spatial effects in cortical processing

Why is spatial tuning in auditory cortex weak, even though location is important to object recognition in natural settings? This question continues to vex neuroscientists focused on linking physiological results to auditory perception. Here we show that the spatial locations of simultaneous, competing sound sources dramatically influence how well neural spike trains recorded from the zebra finch field L (an analog of mammalian primary auditory cortex) encode source identity. We find that the location of a birdsong played in quiet has little effect on the fidelity of the neural encoding of the song. However, when the song is presented along with a masker, spatial effects are pronounced. For each spatial configuration, a subset of neurons encodes song identity more robustly than others. As a result, competing sources from different locations dominate responses of different neural subpopulations, helping to separate neural responses into independent representations. These results help elucidate how cortical processing exploits spatial information to provide a substrate for selective spatial auditory attention.     

Contrast gain control in auditory cortex

The auditory system must represent sounds with a wide range of statistical properties. One important property is the spectrotemporal contrast in the acoustic environment: the variation in sound pressure in each frequency band, relative to the mean pressure. We show that neurons in ferret auditory cortex rescale their gain to partially compensate for the spectrotemporal contrast of recent stimulation. When contrast is low, neurons increase their gain, becoming more sensitive to small changes in the stimulus, although the effectiveness of contrast gain control is reduced at low mean levels. Gain is primarily determined by contrast near each neuron's preferred frequency, but there is also a contribution from contrast in more distant frequency bands. Neural responses are modulated by contrast over timescales of ～100?ms. By using contrast gain control to expand or compress the representation of its inputs, the auditory system may be seeking an efficient coding of natural sounds.