Modulation-frequency-specific adaptation in awake auditory cortex

Forward masking of amplitude modulation: Sensory versus perceptual components

Previous findings suggest that forward masking in the amplitude-modulation (AM) domain includes both sensory and perceptual components. The sensory component reflects masking associated with AM-rate-selective neural channels, whereas the perceptual component reflects masking associated with perceived target-masker similarity. In this article, it is shown that AM forward masking can be substantially reduced or even eliminated by reducing perceived target-masker similarity. It is suggested, therefore, that, under certain conditions, AM forward masking includes, at most, a weak sensory component along with a stronger perceptual component related to perceived target-masker similarity. This complicates interpretations of AM forward masking that rely on AM-rate-selective neural channels.

Hierarchical emergence of opponent coding in auditory belt cortex

We recorded from neurons in primary auditory cortex (A1) and middle-lateral belt area (ML) while rhesus macaques either discriminated amplitude-modulated noise (AM) from unmodulated noise or passively heard the same stimuli. We used several post hoc pooling models to investigate the ability of auditory cortex to leverage population coding for AM detection. We find that pooled-response AM detection is better in the active condition than the passive condition, and better using rate-based coding than synchrony-based coding. Neurons can be segregated into two classes based on whether they increase (INC) or decrease (DEC) their firing rate in response to increasing modulation depth. In these samples, A1 had relatively fewer DEC neurons (26%) than ML (45%). When responses were pooled without segregating these classes, AM detection using rate-based coding was much better in A1 than in ML, but when pooling only INC neurons, AM detection in ML approached that found in A1. Pooling only DEC neurons resulted in impaired AM detection in both areas. To investigate the role of DEC neurons, we devised two pooling methods that opposed DEC and INC neurons-a direct subtractive method and a two-pool push-pull opponent method. Only the push-pull opponent method resulted in superior AM detection relative to indiscriminate pooling. In the active condition, the opponent method was superior to pooling only INC neurons during the late portion of the response in ML. These results suggest that the increasing prevalence of the DEC response type in ML can be leveraged by appropriate methods to improve AM detection.NEW & NOTEWORTHY We used several post hoc pooling models to investigate the ability of primate auditory cortex to leverage population coding in the detection of amplitude-modulated sounds. When cells are indiscriminately pooled, primary auditory cortex (A1) detects amplitude-modulated sounds better than middle-lateral belt (ML). When cells that decrease firing rate with increasing modulation depth are excluded, or used in a push-pull opponent fashion, detection is similar in the two areas, and macaque behavior can be approximated using reasonably sized pools.

Receptive-field nonlinearities in primary auditory cortex: a comparative perspective

Cortical processing of auditory information can be affected by interspecies differences as well as brain states. Here we compare multifeature spectro-temporal receptive fields (STRFs) and associated input/output functions or nonlinearities (NLs) of neurons in primary auditory cortex (AC) of four mammalian species. Single-unit recordings were performed in awake animals (female squirrel monkeys, female, and male mice) and anesthetized animals (female squirrel monkeys, rats, and cats). Neuronal responses were modeled as consisting of two STRFs and their associated NLs. The NLs for the STRF with the highest information content show a broad distribution between linear and quadratic forms. In awake animals, we find a higher percentage of quadratic-like NLs as opposed to more linear NLs in anesthetized animals. Moderate sex differences of the shape of NLs were observed between male and female unanesthetized mice. This indicates that the core AC possesses a rich variety of potential computations, particularly in awake animals, suggesting that multiple computational algorithms are at play to enable the auditory system's robust recognition of auditory events.

Adaptation in auditory processing

Adaptation is an essential feature of auditory neurons, which reduces their responses to unchanging and recurring sounds and allows their response properties to be matched to the constantly changing statistics of sounds that reach the ears. As a consequence, processing in the auditory system highlights novel or unpredictable sounds and produces an efficient representation of the vast range of sounds that animals can perceive by continually adjusting the sensitivity and, to a lesser extent, the tuning properties of neurons to the most commonly encountered stimulus values. Together with attentional modulation, adaptation to sound statistics also helps to generate neural representations of sound that are tolerant to background noise and therefore plays a vital role in auditory scene analysis. In this review, we consider the diverse forms of adaptation that are found in the auditory system in terms of the processing levels at which they arise, the underlying neural mechanisms, and their impact on neural coding and perception. We also ask what the dynamics of adaptation, which can occur over multiple timescales, reveal about the statistical properties of the environment. Finally, we examine how adaptation to sound statistics is influenced by learning and experience and changes as a result of aging and hearing loss.

A Redundant Cortical Code for Speech Envelope

Animal communication sounds exhibit complex temporal structure because of the amplitude fluctuations that comprise the sound envelope. In human speech, envelope modulations drive synchronized activity in auditory cortex (AC), which correlates strongly with comprehension (Giraud and Poeppel, 2012; Peelle and Davis, 2012; Haegens and Zion Golumbic, 2018). Studies of envelope coding in single neurons, performed in nonhuman animals, have focused on periodic amplitude modulation (AM) stimuli and use response metrics that are not easy to juxtapose with data from humans. In this study, we sought to bridge these fields. Specifically, we looked directly at the temporal relationship between stimulus envelope and spiking, and we assessed whether the apparent diversity across neurons' AM responses contributes to the population representation of speech-like sound envelopes. We gathered responses from single neurons to vocoded speech stimuli and compared them to sinusoidal AM responses in auditory cortex (AC) of alert, freely moving Mongolian gerbils of both sexes. While AC neurons displayed heterogeneous tuning to AM rate, their temporal dynamics were stereotyped. Preferred response phases accumulated near the onsets of sinusoidal AM periods for slower rates (<8 Hz), and an over-representation of amplitude edges was apparent in population responses to both sinusoidal AM and vocoded speech envelopes. Crucially, this encoding bias imparted a decoding benefit: a classifier could discriminate vocoded speech stimuli using summed population activity, while higher frequency modulations required a more sophisticated decoder that tracked spiking responses from individual cells. Together, our results imply that the envelope structure relevant to parsing an acoustic stream could be read-out from a distributed, redundant population code.SIGNIFICANCE STATEMENT Animal communication sounds have rich temporal structure and are often produced in extended sequences, including the syllabic structure of human speech. Although the auditory cortex (AC) is known to play a crucial role in representing speech syllables, the contribution of individual neurons remains uncertain. Here, we characterized the representations of both simple, amplitude-modulated sounds and complex, speech-like stimuli within a broad population of cortical neurons, and we found an overrepresentation of amplitude edges. Thus, a phasic, redundant code in auditory cortex can provide a mechanistic explanation for segmenting acoustic streams like human speech.

Forward masking of spectrotemporal modulation detection

Recent work has suggested that there may be specialized mechanisms in the auditory system for coding spectrotemporal modulations (STMs), tuned to different combinations of spectral modulation frequency, temporal modulation frequency, and STM sweep direction. The current study sought evidence of such mechanisms using a psychophysical forward masking paradigm. The detectability of a target comprising upward sweeping STMs was measured following the presentation of modulated maskers applied to the same carrier. Four maskers were tested, which had either (1) the same spectral modulation frequency as the target but a flat temporal envelope, (2) the same temporal modulation frequency as the target but a flat spectral envelope, (3) the same spectral and temporal modulation frequencies as the target but the opposite sweep direction (downward sweeping STMs), or (4) the same spectral and temporal modulation frequencies as the target and the same sweep direction (upward sweeping STMs). Forward masking was greatest for the masker fully matched to the target (4), intermediate for the masker with the opposite sweep direction (3), and negligible for the other two (1, 2). These findings are consistent with the suggestion that the detectability of the target was mediated by an STM-specific coding mechanism with sweep-direction selectivity.

Temporally precise population coding of dynamic sounds by auditory cortex

Fluctuations in the amplitude envelope of complex sounds provide critical cues for hearing, particularly for speech and animal vocalizations. Responses to amplitude modulation (AM) in the ascending auditory pathway have chiefly been described for single neurons. How neural populations might collectively encode and represent information about AM remains poorly characterized, even in primary auditory cortex (A1). We modeled population responses to AM based on data recorded from A1 neurons in awake squirrel monkeys and evaluated how accurately single trial responses to modulation frequencies from 4 to 512 Hz could be decoded as functions of population size, composition, and correlation structure. We found that a population-based decoding model that simulated convergent, equally weighted inputs was highly accurate and remarkably robust to the inclusion of neurons that were individually poor decoders. By contrast, average rate codes based on convergence performed poorly; effective decoding using average rates was only possible when the responses of individual neurons were segregated, as in classical population decoding models using labeled lines. The relative effectiveness of dynamic rate coding in auditory cortex was explained by shared modulation phase preferences among cortical neurons, despite heterogeneity in rate-based modulation frequency tuning. Our results indicate significant population-based synchrony in primary auditory cortex and suggest that robust population coding of the sound envelope information present in animal vocalizations and speech can be reliably achieved even with indiscriminate pooling of cortical responses. These findings highlight the importance of firing rate dynamics in population-based sensory coding.NEW & NOTEWORTHY Fundamental questions remain about population coding in primary auditory cortex (A1). In particular, issues of spike timing in models of neural populations have been largely ignored. We find that spike-timing in response to sound envelope fluctuations is highly similar across neuron populations in A1. This property of shared envelope phase preference allows for a simple population model involving unweighted convergence of neuronal responses to classify amplitude modulation frequencies with high accuracy.

Frequency selectivity in the modulation domain estimated using forward masking: Effects of masker modulation depth and masker-signal delay

The threshold for detecting amplitude modulation (AM) of a sinusoidal or noise carrier is elevated when the signal AM is preceded by masker AM applied to the same carrier. This effect, called AM forward masking, shows selectivity in the AM domain, consistent with the existence of a modulation filter bank (MFB). In this paper we explore the effect of two factors that can influence AM forward masking, using an 8-kHz sinusoidal carrier and a range of masker AM frequencies, f_m, both below and above the signal AM frequency, f_s, of 40 Hz. The first factor was the time delay, t_d, between the end of the masker AM and the start of the signal AM. The second was the AM depth, m, of the masker, which was either 1 or 0.25. The AM forward masking patterns in all conditions showed tuning in the AM domain; signal thresholds were highest when f_m was close to f_s. The amount of AM forward masking decreased with increasing t_d in a similar way for all f_m, so the shapes of the masking patterns did not change markedly with t_d. Remarkably, the amount of AM forward masking decreased by only about 3 dB (a non-significant effect) when the masker m was decreased from 1 to 0.25. This result appears to be inconsistent with an explanation of AM forward masking in terms of adaptation in a MFB or in terms of a sliding temporal integrator.

Auditory Cortical Plasticity Dependent on Environmental Noise Statistics

During critical periods, neural circuits develop to form receptive fields that adapt to the sensory environment and enable optimal performance of relevant tasks. We hypothesized that early exposure to background noise can improve signal-in-noise processing, and the resulting receptive field plasticity in the primary auditory cortex can reveal functional principles guiding that important task. We raised rat pups in different spectro-temporal noise statistics during their auditory critical period. As adults, they showed enhanced behavioral performance in detecting vocalizations in noise. Concomitantly, encoding of vocalizations in noise in the primary auditory cortex improves with noise-rearing. Significantly, spectro-temporal modulation plasticity shifts cortical preferences away from the exposed noise statistics, thus reducing noise interference with the foreground sound representation. Auditory cortical plasticity shapes receptive field preferences to optimally extract foreground information in noisy environments during noise-rearing. Early noise exposure induces cortical circuits to implement efficient coding in the joint spectral and temporal modulation domain.

After rearing rats in moderately loud spectro-temporally modulated background noise, Homma et al. investigated signal-in-noise processing in the primary auditory cortex. Noise-rearing improved vocalization-in-noise performance in both behavioral testing and neural decoding. Cortical plasticity shifted neuronal spectro-temporal modulation preferences away from the exposed noise statistics.

Forward masking of amplitude modulation across ears and its tuning in the modulation domain

Frequency selectivity in the amplitude modulation (AM) domain has been demonstrated using both simultaneous AM masking and forward AM masking. This has been explained using the concept of a modulation filter bank (MFB). Here, we assessed whether the MFB occurs before or after the point of binaural interaction in the auditory pathway by using forward masking in the AM domain in an ipsilateral condition (masker AM and signal AM applied to the left ear with an unmodulated carrier in the right ear) and a contralateral condition (masker AM applied to the right ear and signal AM applied to the left ear). The carrier frequency was 8 kHz, the signal AM frequency, f_s, was 40 or 80 Hz, and the masker AM frequency ranged from 0.25 to 4 times f_s. Contralateral forward AM masking did occur, but it was smaller than ipsilateral AM masking. Tuning in the AM domain was slightly sharper for ipsilateral than for contralateral masking, perhaps reflecting confusion of the signal and masker AM in the ipsilateral condition when their AM frequencies were the same. The results suggest that there might be an MFB both before and after the point in the auditory pathway where binaural interaction occurs.

Developmentally Regulated Rebound Depolarization Enhances Spike Timing Precision in Auditory Midbrain Neurons

The inferior colliculus (IC) is an auditory midbrain structure involved in processing biologically important temporal features of sounds. The responses of IC neurons to these temporal features reflect an interaction of synaptic inputs and neuronal biophysical properties. One striking biophysical property of IC neurons is the rebound depolarization produced following membrane hyperpolarization. To understand how the rebound depolarization is involved in spike timing, we made whole-cell patch clamp recordings from IC neurons in brain slices of P9-21 rats. We found that the percentage of rebound neurons was developmentally regulated. The precision of the timing of the first spike on the rebound increased when the neuron was repetitively injected with a depolarizing current following membrane hyperpolarization. The average jitter of the first spikes was only 0.5 ms. The selective T-type Ca²⁺ channel antagonist, mibefradil, significantly increased the jitter of the first spike of neurons in response to repetitive depolarization following membrane hyperpolarization. Furthermore, the rebound was potentiated by one to two preceding rebounds within a few hundred milliseconds. The first spike generated on the potentiated rebound was more precise than that on the non-potentiated rebound. With the addition of a calcium chelator, BAPTA, into the cell, the rebound potentiation no longer occurred, and the precision of the first spike on the rebound was not improved. These results suggest that the postinhibitory rebound mediated by T-type Ca²⁺ channel promotes spike timing precision in IC neurons. The rebound potentiation and precise spikes may be induced by increases in intracellular calcium levels.

Extracellular voltage thresholds for maximizing information extraction in primate auditory cortex: implications for a brain computer interface

OBJECTIVE

Research by Oby et al (2016) demonstrated that the optimal threshold for extracting information from visual and motor cortices may differ from the optimal threshold for identifying single neurons via spike sorting methods. The optimal threshold for extracting information from auditory cortex has yet to be identified, nor has the optimal temporal scale for representing auditory cortical activity. Here, we describe a procedure to jointly optimize the extracellular threshold and bin size with respect to the decoding accuracy achieved by a linear classifier for a diverse set of auditory stimuli.

APPROACH

We used linear multichannel arrays to record extracellular neural activity from the auditory cortex of awake squirrel monkeys passively listening to both simple and complex sounds. We executed a grid search of the coordinate space defined by the voltage threshold (in units of standard deviation) and the bin size (in units of milliseconds), and computed decoding accuracy at each point.

MAIN RESULTS

The optimal threshold for information extraction was consistently near two standard deviations below the voltage trace mean, which falls significantly below the range of three to five standard deviations typically used as inputs to spike sorting algorithms in basic research and in brain-computer interface (BCI) applications. The optimal binwidth was minimized at the optimal voltage threshold, particularly for acoustic stimuli dominated by temporally dynamic features, indicating that permissive thresholding permits readout of cortical responses with temporal precision on the order of a few milliseconds.

SIGNIFICANCE

The improvements in decoding accuracy we observed for optimal readout parameters suggest that standard thresholding methods substantially underestimate the information present in auditory cortical spiking patterns. The fact that optimal thresholds were relatively low indicates that local populations of cortical neurons exhibit high temporal coherence that could be leveraged in service of future auditory BCI applications.

Amplitude modulation coding in awake mice and squirrel monkeys

Both mice and primates are used to model the human auditory system. The primate order possesses unique cortical specializations that govern auditory processing. Given the power of molecular and genetic tools available in the mouse model, it is essential to understand the similarities and differences in auditory cortical processing between mice and primates. To address this issue, we directly compared temporal encoding properties of neurons in the auditory cortex of awake mice and awake squirrel monkeys (SQMs). Stimuli were drawn from a sinusoidal amplitude modulation (SAM) paradigm, which has been used previously both to characterize temporal precision and to model the envelopes of natural sounds. Neural responses were analyzed with linear template-based decoders. In both species, spike timing information supported better modulation frequency discrimination than rate information, and multiunit responses generally supported more accurate discrimination than single-unit responses from the same site. However, cortical responses in SQMs supported better discrimination overall, reflecting superior temporal precision and greater rate modulation relative to the spontaneous baseline and suggesting that spiking activity in mouse cortex was less strictly regimented by incoming acoustic information. The quantitative differences we observed between SQM and mouse cortex support the idea that SQMs offer advantages for modeling precise responses to fast envelope dynamics relevant to human auditory processing. Nevertheless, our results indicate that cortical temporal processing is qualitatively similar in mice and SQMs and thus recommend the mouse model for mechanistic questions, such as development and circuit function, where its substantial methodological advantages can be exploited. NEW & NOTEWORTHY To understand the advantages of different model organisms, it is necessary to directly compare sensory responses across species. Contrasting temporal processing in auditory cortex of awake squirrel monkeys and mice, with parametrically matched amplitude-modulated tone stimuli, reveals a similar role of timing information in stimulus encoding. However, disparities in response precision and strength suggest that anatomical and biophysical differences between squirrel monkeys and mice produce quantitative but not qualitative differences in processing strategy.

Cascaded Amplitude Modulations in Sound Texture Perception

Sound textures, such as crackling fire or chirping crickets, represent a broad class of sounds defined by their homogeneous temporal structure. It has been suggested that the perception of texture is mediated by time-averaged summary statistics measured from early auditory representations. In this study, we investigated the perception of sound textures that contain rhythmic structure, specifically second-order amplitude modulations that arise from the interaction of different modulation rates, previously described as “beating” in the envelope-frequency domain. We developed an auditory texture model that utilizes a cascade of modulation filterbanks that capture the structure of simple rhythmic patterns. The model was examined in a series of psychophysical listening experiments using synthetic sound textures—stimuli generated using time-averaged statistics measured from real-world textures. In a texture identification task, our results indicated that second-order amplitude modulation sensitivity enhanced recognition. Next, we examined the contribution of the second-order modulation analysis in a preference task, where the proposed auditory texture model was preferred over a range of model deviants that lacked second-order modulation rate sensitivity. Lastly, the discriminability of textures that included second-order amplitude modulations appeared to be perceived using a time-averaging process. Overall, our results demonstrate that the inclusion of second-order modulation analysis generates improvements in the perceived quality of synthetic textures compared to the first-order modulation analysis considered in previous approaches.

Cluster-based analysis improves predictive validity of spike-triggered receptive field estimates

Spectrotemporal receptive field (STRF) characterization is a central goal of auditory physiology. STRFs are often approximated by the spike-triggered average (STA), which reflects the average stimulus preceding a spike. In many cases, the raw STA is subjected to a threshold defined by gain values expected by chance. However, such correction methods have not been universally adopted, and the consequences of specific gain-thresholding approaches have not been investigated systematically. Here, we evaluate two classes of statistical correction techniques, using the resulting STRF estimates to predict responses to a novel validation stimulus. The first, more traditional technique eliminated STRF pixels (time-frequency bins) with gain values expected by chance. This correction method yielded significant increases in prediction accuracy, including when the threshold setting was optimized for each unit. The second technique was a two-step thresholding procedure wherein clusters of contiguous pixels surviving an initial gain threshold were then subjected to a cluster mass threshold based on summed pixel values. This approach significantly improved upon even the best gain-thresholding techniques. Additional analyses suggested that allowing threshold settings to vary independently for excitatory and inhibitory subfields of the STRF resulted in only marginal additional gains, at best. In summary, augmenting reverse correlation techniques with principled statistical correction choices increased prediction accuracy by over 80% for multi-unit STRFs and by over 40% for single-unit STRFs, furthering the interpretational relevance of the recovered spectrotemporal filters for auditory systems analysis.

Comodulation Enhances Signal Detection via Priming of Auditory Cortical Circuits

Acoustic environments are composed of complex overlapping sounds that the auditory system is required to segregate into discrete perceptual objects. The functions of distinct auditory processing stations in this challenging task are poorly understood. Here we show a direct role for mouse auditory cortex in detection and segregation of acoustic information. We measured the sensitivity of auditory cortical neurons to brief tones embedded in masking noise. By altering spectrotemporal characteristics of the masker, we reveal that sensitivity to pure tone stimuli is strongly enhanced in coherently modulated broadband noise, corresponding to the psychoacoustic phenomenon comodulation masking release. Improvements in detection were largest following priming periods of noise alone, indicating that cortical segregation is enhanced over time. Transient opsin-mediated silencing of auditory cortex during the priming period almost completely abolished these improvements, suggesting that cortical processing may play a direct and significant role in detection of quiet sounds in noisy environments.

SIGNIFICANCE STATEMENT Auditory systems are adept at detecting and segregating competing sound sources, but there is little direct evidence of how this process occurs in the mammalian auditory pathway. We demonstrate that coherent broadband noise enhances signal representation in auditory cortex, and that prolonged exposure to noise is necessary to produce this enhancement. Using optogenetic perturbation to selectively silence auditory cortex during early noise processing, we show that cortical processing plays a crucial role in the segregation of competing sounds.

Background noise exerts diverse effects on the cortical encoding of foreground sounds

In natural listening conditions, many sounds must be detected and identified in the context of competing sound sources, which function as background noise. Traditionally, noise is thought to degrade the cortical representation of sounds by suppressing responses and increasing response variability. However, recent studies of neural network models and brain slices have shown that background synaptic noise can improve the detection of signals. Because acoustic noise affects the synaptic background activity of cortical networks, it may improve the cortical responses to signals. We used spike train decoding techniques to determine the functional effects of a continuous white noise background on the responses of clusters of neurons in auditory cortex to foreground signals, specifically frequency-modulated sweeps (FMs) of different velocities, directions, and amplitudes. Whereas the addition of noise progressively suppressed the FM responses of some cortical sites in the core fields with decreasing signal-to-noise ratios (SNRs), the stimulus representation remained robust or was even significantly enhanced at specific SNRs in many others. Even though the background noise level was typically not explicitly encoded in cortical responses, significant information about noise context could be decoded from cortical responses on the basis of how the neural representation of the foreground sweeps was affected. These findings demonstrate significant diversity in signal in noise processing even within the core auditory fields that could support noise-robust hearing across a wide range of listening conditions.NEW & NOTEWORTHY The ability to detect and discriminate sounds in background noise is critical for our ability to communicate. The neural basis of robust perceptual performance in noise is not well understood. We identified neuronal populations in core auditory cortex of squirrel monkeys that differ in how they process foreground signals in background noise and that may contribute to robust signal representation and discrimination in acoustic environments with prominent background noise.

Effects of Signal-to-Noise Ratio on Auditory Cortical Frequency Processing

The neural mechanisms that support the robust processing of acoustic signals in the presence of background noise in the auditory system remain largely unresolved. Psychophysical experiments have shown that signal detection is influenced by the signal-to-noise ratio (SNR) and the overall stimulus level, but this relationship has not been fully characterized. We evaluated the neural representation of frequency in rat primary auditory cortex by constructing tonal frequency response areas (FRAs) in primary auditory cortex for different SNRs, tone levels, and noise levels. We show that response strength and selectivity for frequency and sound level depend on interactions between SNRs and tone levels. At low SNRs, jointly increasing the tone and noise levels reduced firing rates and narrowed FRA bandwidths; at higher SNRs, however, increasing the tone and noise levels increased firing rates and expanded bandwidths, as is usually seen for FRAs obtained without background noise. These changes in frequency and intensity tuning decreased tone level and tone frequency discriminability at low SNRs. By contrast, neither response onset latencies nor noise-driven steady-state firing rates meaningfully interacted with SNRs or overall sound levels. Speech detection performance in humans was also shown to depend on the interaction between overall sound level and SNR. Together, these results indicate that signal processing difficulties imposed by high noise levels are quite general and suggest that the neurophysiological changes we see for simple sounds generalize to more complex stimuli.

SIGNIFICANCE STATEMENT

Effective processing of sounds in background noise is an important feature of the mammalian auditory system and a necessary feature for successful hearing in many listening conditions. Even mild hearing loss strongly affects this ability in humans, seriously degrading the ability to communicate. The mechanisms involved in achieving high performance in background noise are not well understood. We investigated the effects of SNR and overall stimulus level on the frequency tuning of neurons in rat primary auditory cortex. We found that the effects of noise on frequency selectivity are not determined solely by the SNR but depend also on the levels of the foreground tones and background noise. These observations can lead to improvement in therapeutic approaches for hearing-impaired patients.

Synaptic plasticity as a cortical coding scheme

Processing of auditory information requires constant adjustment due to alterations of the environment and changing conditions in the nervous system with age, health, and experience. Consequently, patterns of activity in cortical networks have complex dynamics over a wide range of timescales, from milliseconds to days and longer. In the primary auditory cortex (AI), multiple forms of adaptation and plasticity shape synaptic input and action potential output. However, the variance of neuronal responses has made it difficult to characterize AI receptive fields and to determine the function of AI in processing auditory information such as vocalizations. Here we describe recent studies on the temporal modulation of cortical responses and consider the relation of synaptic plasticity to neural coding.

Deviance-Related Responses along the Auditory Hierarchy: Combined FFR, MLR and MMN Evidence

The mismatch negativity (MMN) provides a correlate of automatic auditory discrimination in human auditory cortex that is elicited in response to violation of any acoustic regularity. Recently, deviance-related responses were found at much earlier cortical processing stages as reflected by the middle latency response (MLR) of the auditory evoked potential, and even at the level of the auditory brainstem as reflected by the frequency following response (FFR). However, no study has reported deviance-related responses in the FFR, MLR and long latency response (LLR) concurrently in a single recording protocol. Amplitude-modulated (AM) sounds were presented to healthy human participants in a frequency oddball paradigm to investigate deviance-related responses along the auditory hierarchy in the ranges of FFR, MLR and LLR. AM frequency deviants modulated the FFR, the Na and Nb components of the MLR, and the LLR eliciting the MMN. These findings demonstrate that it is possible to elicit deviance-related responses at three different levels (FFR, MLR and LLR) in one single recording protocol, highlight the involvement of the whole auditory hierarchy in deviance detection and have implications for cognitive and clinical auditory neuroscience. Moreover, the present protocol provides a new research tool into clinical neuroscience so that the functional integrity of the auditory novelty system can now be tested as a whole in a range of clinical populations where the MMN was previously shown to be defective.