Stimulus-Specific Adaptation in Field Potentials and Neuronal Responses to Frequency-Modulated Tones in the Primary Auditory Cortex

Short-term neuronal and synaptic plasticity act in synergy for deviance detection in spiking networks

Sensory areas of cortex respond more strongly to infrequent stimuli when these violate previously established regularities, a phenomenon known as deviance detection (DD). Previous modeling work has mainly attempted to explain DD on the basis of synaptic plasticity. However, a large fraction of cortical neurons also exhibit firing rate adaptation, an underexplored potential mechanism. Here, we investigate DD in a spiking neuronal network model with two types of short-term plasticity, fast synaptic short-term depression (STD) and slower threshold adaptation (TA). We probe the model with an oddball stimulation paradigm and assess DD by evaluating the network responses. We find that TA is sufficient to elicit DD. It achieves this by habituating neurons near the stimulation site that respond earliest to the frequently presented standard stimulus (local fatigue), which diminishes the response and promotes the recovery (global fatigue) of the wider network. Further, we find a synergy effect between STD and TA, where they interact with each other to achieve greater DD than the sum of their individual effects. We show that this synergy is caused by the local fatigue added by STD, which inhibits the global response to the frequently presented stimulus, allowing greater recovery of TA-mediated global fatigue and making the network more responsive to the deviant stimulus. Finally, we show that the magnitude of DD strongly depends on the timescale of stimulation. We conclude that highly predictable information can be encoded in strong local fatigue, which allows greater global recovery and subsequent heightened sensitivity for DD.

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.

Predictive encoding of pure tones and FM-sweeps in the human auditory cortex

Expectations substantially influence perception, but the neural mechanisms underlying this influence are not fully understood. A prominent view is that sensory neurons encode prediction error with respect to expectations on upcoming sensory input. Although the encoding of prediction error has been previously demonstrated in the human auditory cortex (AC), previous studies often induced expectations using stimulus repetition, potentially confounding prediction error with neural habituation. These studies also measured AC as a single population, failing to consider possible predictive specializations of different AC fields. Moreover, the few studies that considered prediction error to stimuli other than pure tones yielded conflicting results. Here, we used functional magnetic resonance imaging (fMRI) to systematically investigate prediction error to subjective expectations in auditory cortical fields Te1.0, Te1.1, Te1.2, and Te3, and two types of stimuli: pure tones and frequency modulated (FM) sweeps. Our results show that prediction error is elicited with respect to the participants' expectations independently of stimulus repetition and similarly expressed across auditory fields. Moreover, despite the radically different strategies underlying the decoding of pure tones and FM-sweeps, both stimulus modalities were encoded as prediction error in most fields of AC. Altogether, our results provide unequivocal evidence that predictive coding is the general encoding mechanism in AC.

Stimulus-Specific Adaptation in Auditory Thalamus Is Modulated by the Thalamic Reticular Nucleus

A striking property of the auditory system is its capacity for the stimulus-specific adaptation (SSA), which is the reduction of neural response to repeated stimuli but a recuperative response to novel stimuli. SSA is found in both the medial geniculate body (MGB) and thalamic reticular nucleus (TRN). However, it remains unknown whether the SSA of MGB neurons is modulated by inhibitory inputs from the TRN, as it is difficult to investigate using the extracellular recording method. In the present study, we performed intracellular recordings in the MGB of anesthetized guinea pigs and examined whether and how the TRN modulates the SSA of MGB neurons with inhibitory inputs. This was accomplished by using microinjection of lidocaine to inactivate the neural activity of the TRN. We found that (1) MGB neurons with hyperpolarized membrane potentials exhibited SSA at both the spiking and subthreshold levels; (2) SSA of MGB neurons depends on the interstimulus interval (ISI), where a shorter ISI results in stronger SSA; and (3) the long-lasting hyperpolarization of MGB neurons decreased after the burst firing of the TRN was inactivated. As a result, SSA of these MGB neurons was diminished after inactivation of the TRN. Taken together, our results revealed that the SSA of the MGB is strongly modulated by the neural activity of the TRN, which suggests an alternative circuit mechanism underlying the SSA of the auditory thalamus.

The Neuronal Basis of Predictive Coding Along the Auditory Pathway: From the Subcortical Roots to Cortical Deviance Detection

In this review, we attempt to integrate the empirical evidence regarding stimulus-specific adaptation (SSA) and mismatch negativity (MMN) under a predictive coding perspective (also known as Bayesian or hierarchical-inference model). We propose a renewed methodology for SSA study, which enables a further decomposition of deviance detection into repetition suppression and prediction error, thanks to the use of two controls previously introduced in MMN research: the many-standards and the cascade sequences. Focusing on data obtained with cellular recordings, we explain how deviance detection and prediction error are generated throughout hierarchical levels of processing, following two vectors of increasing computational complexity and abstraction along the auditory neuraxis: from subcortical toward cortical stations and from lemniscal toward nonlemniscal divisions. Then, we delve into the particular characteristics and contributions of subcortical and cortical structures to this generative mechanism of hierarchical inference, analyzing what is known about the role of neuromodulation and local microcircuitry in the emergence of mismatch signals. Finally, we describe how SSA and MMN are occurring at similar time frame and cortical locations, and both are affected by the manipulation of N-methyl- D-aspartate receptors. We conclude that there is enough empirical evidence to consider SSA and MMN, respectively, as the microscopic and macroscopic manifestations of the same physiological mechanism of deviance detection in the auditory cortex. Hence, the development of a common theoretical framework for SSA and MMN is all the more recommendable for future studies. In this regard, we suggest a shared nomenclature based on the predictive coding interpretation of deviance detection.

Auditory-evoked potentials to changes in sound duration in urethane-anaesthetized mice

Spectrotemporally complex sounds carry important information for acoustic communication. Among the important features of these sounds is the temporal duration. An event-related potential called mismatch negativity indexes auditory change detection in humans. An analogous response (mismatch response) has been found to duration changes in speech sounds in rats but not yet in mice. We addressed whether mice show this response, and, if elicited, whether this response is functionally analogous to mismatch negativity or whether adaptation-based models suffice to explain them. Auditory-evoked potentials were epidurally recorded above the mice auditory cortex. The differential response to the changes in a repeated human speech sound /a/ was elicited 53-259 ms post-change (oddball condition). The differential response was observable to the largest duration change (from 200 to 110 ms). Any smaller (from 200 to 120-180 ms at 10 ms steps) duration changes did elicit an observable response. The response to the largest duration change did not robustly differ in amplitude from the response to the change-inducing sound presented without its repetitive background (equiprobable condition). The findings suggest that adaptation may suffice to explain responses to duration changes in spectrotemporally complex sounds in anaesthetized mice. The results pave way for development of a variety of murine models of acoustic communication.

Deviance sensitivity in the auditory cortex of freely moving rats

Deviance sensitivity is the specific response to a surprising stimulus, one that violates expectations set by the past stimulation stream. In audition, deviance sensitivity is often conflated with stimulus-specific adaptation (SSA), the decrease in responses to a common stimulus that only partially generalizes to other, rare stimuli. SSA is usually measured using oddball sequences, where a common (standard) tone and a rare (deviant) tone are randomly intermixed. However, the larger responses to a tone when deviant does not necessarily represent deviance sensitivity. Deviance sensitivity is commonly tested using a control sequence in which many different tones serve as the standard, eliminating the expectations set by the standard ('deviant among many standards'). When the response to a tone when deviant (against a single standard) is larger than the responses to the same tone in the control sequence, it is concluded that true deviance sensitivity occurs. In primary auditory cortex of anesthetized rats, responses to deviants and to the same tones in the control condition are comparable in size. We recorded local field potentials and multiunit activity from the auditory cortex of awake, freely moving rats, implanted with 32-channel drivable microelectrode arrays and using telemetry. We observed highly significant SSA in the awake state. Moreover, the responses to a tone when deviant were significantly larger than the responses to the same tone in the control condition. These results establish the presence of true deviance sensitivity in primary auditory cortex in awake rats.

[Effects of auditory response patterns on stimulus-specific adaptation of inferior colliculus neurons in awake mice]

OBJECTIVE

To explore whether the pattern of neuron's auditory response to a sound stimulus affects the characteristics of stimulus-specific adaptation (SSA) in awake mice.

METHODS

The auditory responses of the neurons in the inferior colliculus to sound stimuli were recorded using microelectrodes in awake mice. The sequence of sound stimuli consisted of random combinations of pure tones of two different frequencies (f1 and f2) with different repetition rates. The auditory responses of the neurons to standard and deviant stimuli were calculated, namely s(f2)/s(f2) and d(f1)/d(f2), respectively. Three indexes of the responses were also calculated, including the firing difference index (FDI), frequency-specific index (SI), and common SSA index(CSI).

RESULTS

The CSI of neurons with a greater FDI was significantly higher than that of neurons with a smaller FDI (P < 0.05). The primary-like neurons showed different characteristics of SSAs in different time periods; SSA was significantly increased in the phase of sustained response compared with that at the onset of response (P < 0.05).

CONCLUSIONS

The auditory response pattern to sound stimuli is also an important factor that affect SSA of inferior colliculus neurons in awake mice.

Deviant Processing in the Primary Somatosensory Cortex

Stimulus-specific adaptation (SSA) to repetitive stimulation has been proposed to separate behaviorally relevant features from a stream of continuous sensory information. However, the exact mechanisms giving rise to SSA and cortical deviance detection are not well understood. We therefore used an oddball paradigm and multicontact electrodes to characterize single-neuron and local field potential responses to various deviant stimuli across the rat somatosensory cortex. Changing different single-whisker stimulus features evoked robust SSA in individual cortical neurons over a wide range of stimulus repetition rates (0.25-80 Hz). Notably, SSA was weakest in the granular input layer and significantly stronger in the supra- and infragranular layers, suggesting that a major part of SSA is generated within cortex. Moreover, we found a small subset of neurons in the granular layer with a deviant-specific late response, occurring roughly 200 ms after stimulus offset. This late deviant response exhibited true-deviance detection properties that were not explained by depression of sensory inputs. Our results show that deviant responses are actively amplified within cortex and contain an additional late component that is sensitive for context-specific sensory deviations. This strongly implicates deviance detection as a feature of intracortical stimulus processing beyond simple sensory input depression.

Neurons along the auditory pathway exhibit a hierarchical organization of prediction error

Perception is characterized by a reciprocal exchange of predictions and prediction error signals between neural regions. However, the relationship between such sensory mismatch responses and hierarchical predictive processing has not yet been demonstrated at the neuronal level in the auditory pathway. We recorded single-neuron activity from different auditory centers in anaesthetized rats and awake mice while animals were played a sequence of sounds, designed to separate the responses due to prediction error from those due to adaptation effects. Here we report that prediction error is organized hierarchically along the central auditory pathway. These prediction error signals are detectable in subcortical regions and increase as the signals move towards auditory cortex, which in turn demonstrates a large-scale mismatch potential. Finally, the predictive activity of single auditory neurons underlies automatic deviance detection at subcortical levels of processing. These results demonstrate that prediction error is a fundamental component of singly auditory neuron responses.

Laminar differences in response to simple and spectro-temporally complex sounds in the primary auditory cortex of ketamine-anesthetized gerbils

In mammals, acoustic communication plays an important role during social behaviors. Despite their ethological relevance, the mechanisms by which the auditory cortex represents different communication call properties remain elusive. Recent studies have pointed out that communication-sound encoding could be based on discharge patterns of neuronal populations. Following this idea, we investigated whether the activity of local neuronal networks, such as those occurring within individual cortical columns, is sufficient for distinguishing between sounds that differed in their spectro-temporal properties. To accomplish this aim, we analyzed simple pure-tone and complex communication call elicited multi-unit activity (MUA) as well as local field potentials (LFP), and current source density (CSD) waveforms at the single-layer and columnar level from the primary auditory cortex of anesthetized Mongolian gerbils. Multi-dimensional scaling analysis was used to evaluate the degree of "call-specificity" in the evoked activity. The results showed that whole laminar profiles segregated 1.8-2.6 times better across calls than single-layer activity. Also, laminar LFP and CSD profiles segregated better than MUA profiles. Significant differences between CSD profiles evoked by different sounds were more pronounced at mid and late latencies in the granular and infragranular layers and these differences were based on the absence and/or presence of current sinks and on sink timing. The stimulus-specific activity patterns observed within cortical columns suggests that the joint activity of local cortical populations (as local as single columns) could indeed be important for encoding sounds that differ in their acoustic attributes.

Topographic Distribution of Stimulus-Specific Adaptation across Auditory Cortical Fields in the Anesthetized Rat

Stimulus-specific adaptation (SSA) in single neurons of the auditory cortex was suggested to be a potential neural correlate of the mismatch negativity (MMN), a widely studied component of the auditory event-related potentials (ERP) that is elicited by changes in the auditory environment. However, several aspects on this SSA/MMN relation remain unresolved. SSA occurs in the primary auditory cortex (A1), but detailed studies on SSA beyond A1 are lacking. To study the topographic organization of SSA, we mapped the whole rat auditory cortex with multiunit activity recordings, using an oddball paradigm. We demonstrate that SSA occurs outside A1 and differs between primary and nonprimary cortical fields. In particular, SSA is much stronger and develops faster in the nonprimary than in the primary fields, paralleling the organization of subcortical SSA. Importantly, strong SSA is present in the nonprimary auditory cortex within the latency range of the MMN in the rat and correlates with an MMN-like difference wave in the simultaneously recorded local field potentials (LFP). We present new and strong evidence linking SSA at the cellular level to the MMN, a central tool in cognitive and clinical neuroscience.

This study of higher-order auditory cortex strengthens the case for long-latency stimulus-specific adaptation as a genuine neural correlate of the mismatch negativity, which flags salient stimuli.

Sensory systems automatically detect salient events in a monotonous ambient background. In humans, this change detection process is indexed by the mismatch negativity (MMN), a mid-late component of the auditory-evoked potentials that has become a central tool in cognitive and clinical neuroscience over the last 40 years. However, the neuronal correlate of MMN remains controversial. Stimulus-specific adaptation (SSA) is a special type of adaptation recorded at the neuronal level in the auditory pathway. Attenuating the response only to repetitive, background stimuli is a very efficient mechanism to enhance the saliency of any upcoming deviant or novel stimulus. Thus, SSA was originally proposed as a neural correlate of the MMN, but previous studies in the auditory cortex reported SSA only at very early latencies (circa 20–30 ms) and only within the primary auditory cortex (A1), whereas MMN analogs in the rat occur later, between 50 and 100 ms after change onset, and are generated mainly within nonprimary fields. Here, we report very strong SSA in nonprimary fields within the latency range of the MMN in the rat, providing empirical evidence of the missing link between single neuron response studies in animal models and the human MMN.

Cholinergic Modulation of Stimulus-Specific Adaptation in the Inferior Colliculus

Neural encoding of an ever-changing acoustic environment is a complex and demanding process that depends on modulation by neuroactive substances. Some neurons of the inferior colliculus (IC) exhibit "stimulus-specific adaptation" (SSA), i.e., a decrease in their response to a repetitive sound, but not to a rare one. Previous studies have demonstrated that acetylcholine (ACh) alters the frequency response areas of auditory neurons and therefore is important in the encoding of spectral information. Here, we address how microiontophoretic application of ACh modulates SSA in the IC of the anesthetized rat. We found that ACh decreased SSA in IC neurons by increasing the response to the repetitive tone. This effect was mainly mediated by muscarinic receptors. The strength of the cholinergic modulation depended on the baseline SSA level, exerting its greatest effect on neurons with intermediate SSA responses across IC subdivisions. Our data demonstrate that the increased availability of ACh exerts transient functional changes in partially adapting IC neurons, enhancing the sensory encoding of the ongoing stimulation. This effect potentially contributes to the propagation of ascending sensory-evoked afferent activity through the thalamus en route to the cortex.

SIGNIFICANCE STATEMENT

Neural encoding of an ever-changing acoustic environment is a complex and demanding task that may depend on the available levels of neuroactive substances. We explored how the cholinergic inputs affect the responses of neurons in the auditory midbrain that exhibit different degrees of stimulus-specific adaptation (SSA), i.e., a specific decrease in their response to a repeated sound that does not generalize to other, rare sounds. This work addresses the role of cholinergic synaptic inputs as well as the contribution of the muscarinic and nicotinic receptors on SSA. This is the first report on the role of neuromodulation on SSA, and the results contribute to our understanding of the cellular bases for processing low- and high-probability sounds.