Adaptation in the auditory system: an overview

Concurrent Encoding of Sequence Predictability and Event-Evoked Prediction Error in Unfolding Auditory Patterns

Human listeners possess an innate capacity to discern patterns within rapidly unfolding sensory input. Core questions, guiding ongoing research, focus on the mechanisms through which these representations are acquired and whether the brain prioritizes or suppresses predictable sensory signals. Previous work, using fast auditory sequences (tone-pips presented at a rate of 20 Hz), revealed sustained response effects that appear to track the dynamic predictability of the sequence. Here, we extend the investigation to slower sequences (4 Hz), permitting the isolation of responses to individual tones. Stimuli were 50 ms tone-pips, ordered into random (RND) and regular (REG; a repeating pattern of 10 frequencies) sequences; Two timing profiles were created: in "fast" sequences, tone-pips were presented in direct succession (20 Hz); in "slow" sequences, tone-pips were separated by a 200 ms silent gap (4 Hz). Naive participants (N = 22; both sexes) passively listened to these sequences, while brain responses were recorded using magnetoencephalography (MEG). Results unveiled a heightened magnitude of sustained brain responses in REG when compared to RND patterns. This manifested from three tones after the onset of the pattern repetition, even in the context of slower sequences characterized by extended pattern durations (2,500 ms). This observation underscores the remarkable implicit sensitivity of the auditory brain to acoustic regularities. Importantly, brain responses evoked by single tones exhibited the opposite pattern-stronger responses to tones in RND than REG sequences. The demonstration of simultaneous but opposing sustained and evoked response effects reveals concurrent processes that shape the representation of unfolding auditory patterns.

Digging into the intrinsic capacity concept: Can it be applied to Alzheimer's disease?

Historically, aging research has largely centered on disease pathology rather than promoting healthy aging. The World Health Organization's (WHO) policy framework (2015-2030) underscores the significance of fostering the contributions of older individuals to their families, communities, and economies. The WHO has introduced the concept of intrinsic capacity (IC) as a key metric for healthy aging, encompassing five primary domains: locomotion, vitality, sensory, cognitive, and psychological. Past AD research, constrained by methodological limitations, has focused on single outcome measures, sidelining the complexity of the disease. Our current scientific milieu, however, is primed to adopt the IC concept. This is due to three critical considerations: (I) the decline in IC is linked to neurocognitive disorders, including AD, (II) cognition, a key component of IC, is deeply affected in AD, and (III) the cognitive decline associated with AD involves multiple factors and pathophysiological pathways. Our study explores the application of the IC concept to AD patients, offering a comprehensive model that could revolutionize the disease's diagnosis and prognosis. There is a dearth of information on the biological characteristics of IC, which are a result of complex interactions within biological systems. Employing a systems biology approach, integrating omics technologies, could aid in unraveling these interactions and understanding IC from a holistic viewpoint. This comprehensive analysis of IC could be leveraged in clinical settings, equipping healthcare providers to assess AD patients' health status more effectively and devise personalized therapeutic interventions in accordance with the precision medicine paradigm. We aimed to determine whether the IC concept could be extended from older individuals to patients with AD, thereby presenting a model that could significantly enhance the diagnosis and prognosis of this disease.

Time-resolved dynamic computational modeling of human EEG recordings reveals gradients of generative mechanisms for the MMN response

Despite attempts to unify the different theoretical accounts of the mismatch negativity (MMN), there is still an ongoing debate on the neurophysiological mechanisms underlying this complex brain response. On one hand, neuronal adaptation to recurrent stimuli is able to explain many of the observed properties of the MMN, such as its sensitivity to controlled experimental parameters. On the other hand, several modeling studies reported evidence in favor of Bayesian learning models for explaining the trial-to-trial dynamics of the human MMN. However, direct comparisons of these two main hypotheses are scarce, and previous modeling studies suffered from methodological limitations. Based on reports indicating spatial and temporal dissociation of physiological mechanisms within the timecourse of mismatch responses in animals, we hypothesized that different computational models would best fit different temporal phases of the human MMN. Using electroencephalographic data from two independent studies of a simple auditory oddball task (n = 82), we compared adaptation and Bayesian learning models' ability to explain the sequential dynamics of auditory deviance detection in a time-resolved fashion. We first ran simulations to evaluate the capacity of our design to dissociate the tested models and found that they were sufficiently distinguishable above a certain level of signal-to-noise ratio (SNR). In subjects with a sufficient SNR, our time-resolved approach revealed a temporal dissociation between the two model families, with high evidence for adaptation during the early MMN window (from 90 to 150-190 ms post-stimulus depending on the dataset) and for Bayesian learning later in time (170-180 ms or 200-220ms). In addition, Bayesian model averaging of fixed-parameter models within the adaptation family revealed a gradient of adaptation rates, resembling the anatomical gradient in the auditory cortical hierarchy reported in animal studies.

Laminar neural dynamics of auditory evoked responses: Computational modeling of local field potentials in auditory cortex of non-human primates

Evoked neural responses to sensory stimuli have been extensively investigated in humans and animal models both to enhance our understanding of brain function and to aid in clinical diagnosis of neurological and neuropsychiatric conditions. Recording and imaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG), local field potentials (LFPs), and calcium imaging provide complementary information about different aspects of brain activity at different spatial and temporal scales. Modeling and simulations provide a way to integrate these different types of information to clarify underlying neural mechanisms. In this study, we aimed to shed light on the neural dynamics underlying auditory evoked responses by fitting a rate-based model to LFPs recorded via multi-contact electrodes which simultaneously sampled neural activity across cortical laminae. Recordings included neural population responses to best-frequency (BF) and non-BF tones at four representative sites in primary auditory cortex (A1) of awake monkeys. The model considered major neural populations of excitatory, parvalbumin-expressing (PV), and somatostatin-expressing (SOM) neurons across layers 2/3, 4, and 5/6. Unknown parameters, including the connection strength between the populations, were fitted to the data. Our results revealed similar population dynamics, fitted model parameters, predicted equivalent current dipoles (ECD), tuning curves, and lateral inhibition profiles across recording sites and animals, in spite of quite different extracellular current distributions. We found that PV firing rates were higher in BF than in non-BF responses, mainly due to different strengths of tonotopic thalamic input, whereas SOM firing rates were higher in non-BF than in BF responses due to lateral inhibition. In conclusion, we demonstrate the feasibility of the model-fitting approach in identifying the contributions of cell-type specific population activity to stimulus-evoked LFPs across cortical laminae, providing a foundation for further investigations into the dynamics of neural circuits underlying cortical sensory processing.

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.

Predictive Mouse Ultrasonic Vocalization Sequences: Uncovering Behavioral Significance, Auditory Cortex Neuronal Preferences, and Social-Experience-Driven Plasticity

Mouse ultrasonic vocalizations (USVs) contain predictable sequential structures like bird songs and speech. Neural representation of USVs in the mouse primary auditory cortex (Au1) and its plasticity with experience has been largely studied with single-syllables or dyads, without using the predictability in USV sequences. Studies using playback of USV sequences have used randomly selected sequences from numerous possibilities. The current study uses mutual information to obtain context-specific natural sequences (NSeqs) of USV syllables capturing the observed predictability in male USVs in different contexts of social interaction with females. Behavioral and physiological significance of NSeqs over random sequences (RSeqs) lacking predictability were examined. Female mice, never having the social experience of being exposed to males, showed higher selectivity for NSeqs behaviorally and at cellular levels probed by expression of immediate early gene c-fos in Au1. The Au1 supragranular single units also showed higher selectivity to NSeqs over RSeqs. Social-experience-driven plasticity in encoding NSeqs and RSeqs in adult females was probed by examining neural selectivities to the same sequences before and after the above social experience. Single units showed enhanced selectivity for NSeqs over RSeqs after the social experience. Further, using two-photon Ca2+ imaging, we observed social experience-dependent changes in the selectivity of sequences of excitatory and somatostatin-positive inhibitory neurons but not parvalbumin-positive inhibitory neurons of Au1. Using optogenetics, somatostatin-positive neurons were identified as a possible mediator of the observed social-experience-driven plasticity. Our study uncovers the importance of predictive sequences and introduces mouse USVs as a promising model to study context-dependent speech like communications.SIGNIFICANCE STATEMENT Humans need to detect patterns in the sensory world. For instance, speech is meaningful sequences of acoustic tokens easily differentiated from random ordered tokens. The structure derives from the predictability of the tokens. Similarly, mouse vocalization sequences have predictability and undergo context-dependent modulation. Our work investigated whether mice differentiate such informative predictable sequences (NSeqs) of communicative significance from RSeqs at the behavioral, molecular, and neuronal levels. Following a social experience in which NSeqs occur as a crucial component, mouse auditory cortical neurons become more sensitive to differences between NSeqs and RSeqs, although preference for individual tokens is unchanged. Thus, speech-like communication and its dysfunction may be studied in circuit, cellular, and molecular levels in mice.

Dynamic encoding of phonetic categories in zebra finch auditory forebrain

Vocal communication requires the formation of acoustic categories to enable invariant representations of sounds despite superficial variations. Humans form acoustic categories for speech phonemes, enabling the listener to recognize words independent of speakers; animals can also discriminate speech phonemes. We investigated the neural mechanisms of this process using electrophysiological recordings from the zebra finch secondary auditory area, caudomedial nidopallium (NCM), during passive exposure to human speech stimuli consisting of two naturally spoken words produced by multiple speakers. Analysis of neural distance and decoding accuracy showed improvements in neural discrimination between word categories over the course of exposure, and this improved representation transferred to the same words by novel speakers. We conclude that NCM neurons formed generalized representations of word categories independent of speaker-specific variations that became more refined over the course of passive exposure. The discovery of this dynamic encoding process in NCM suggests a general processing mechanism for forming categorical representations of complex acoustic signals that humans share with other animals.

Vowel and formant representation in the human auditory speech cortex

Vowels, a fundamental component of human speech across all languages, are cued acoustically by formants, resonance frequencies of the vocal tract shape during speaking. An outstanding question in neurolinguistics is how formants are processed neurally during speech perception. To address this, we collected high-density intracranial recordings from the human speech cortex on the superior temporal gyrus (STG) while participants listened to continuous speech. We found that two-dimensional receptive fields based on the first two formants provided the best characterization of vowel sound representation. Neural activity at single sites was highly selective for zones in this formant space. Furthermore, formant tuning is adjusted dynamically for speaker-specific spectral context. However, the entire population of formant-encoding sites was required to accurately decode single vowels. Overall, our results reveal that complex acoustic tuning in the two-dimensional formant space underlies local vowel representations in STG. As a population code, this gives rise to phonological vowel perception.

Perspectives on adaptive dynamical systems

Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems, such as the power grid, social, and neural networks, and they form the backbone of closed-loop control strategies and machine learning algorithms. In this article, we provide an interdisciplinary perspective on adaptive systems. We reflect on the notion and terminology of adaptivity in different disciplines and discuss which role adaptivity plays for various fields. We highlight common open challenges and give perspectives on future research directions, looking to inspire interdisciplinary approaches.

Induced alpha and beta electroencephalographic rhythms covary with single-trial speech intelligibility in competition

Neurophysiological studies suggest that intrinsic brain oscillations influence sensory processing, especially of rhythmic stimuli like speech. Prior work suggests that brain rhythms may mediate perceptual grouping and selective attention to speech amidst competing sound, as well as more linguistic aspects of speech processing like predictive coding. However, we know of no prior studies that have directly tested, at the single-trial level, whether brain oscillations relate to speech-in-noise outcomes. Here, we combined electroencephalography while simultaneously measuring intelligibility of spoken sentences amidst two different interfering sounds: multi-talker babble or speech-shaped noise. We find that induced parieto-occipital alpha (7-15 Hz; thought to modulate attentional focus) and frontal beta (13-30 Hz; associated with maintenance of the current sensorimotor state and predictive coding) oscillations covary with trial-wise percent-correct scores; importantly, alpha and beta power provide significant independent contributions to predicting single-trial behavioral outcomes. These results can inform models of speech processing and guide noninvasive measures to index different neural processes that together support complex listening.

Outdoor residential noise exposure and sleep in preadolescents from two European birth cohorts

OBJECTIVE

To examine whether outdoor residential exposure to annual average road traffic and multiple (i.e., road traffic, railway, aircraft, industry) noise levels is related with preadolescents' sleep using maternal-reported and wrist-actigraphy data in two European birth cohorts.

METHODS

This cross-sectional study used data of 1245 preadolescents from the Dutch Generation R Study and 232 from the Spanish INMA-Sabadell cohort with a mean age of 12.3 years old. We used noise maps to assess average outdoor road traffic and multiple noise levels (day-evening-night noise indicator, L_DEN) at each child's residential address for the year before the sleep assessment. Sleep disturbances were reported by mothers through the Sleep Disturbance Scale for Children and objectively recorded using GeneActiv wrist-actigraphy during seven subsequent days. Linear and Poisson regression models adjusted for several potential confounding variables were performed.

RESULTS

The mean (SD) exposure to road traffic noise was 53.2 dB (7.3) in the Generation R Study and 61.3 dB (5.9) in the INMA-Sabadell cohort. Exposure to road traffic was related with reduced total sleep time and longer wake after sleep onset (e.g. -3.62 min (95%CI -6.87; -0.37) and 6.88 min (95%CI 1.15; 12.61) per an increase of 10 dB in road traffic noise, respectively) collected by wrist-actigraphy. We observed no association between road traffic exposure and maternal-reported sleep disturbances. Results were similar for multiple noise exposure.

CONCLUSIONS

These findings indicate that sleep may be compromised for preadolescents living in areas highly exposed to outdoor residential noise. Future studies using longitudinal designs to further explore these associations during the different stages of sleep development across childhood and adolescence are warranted. Also, wrist-actigraphy measurements which provide more accurate information and may be complementary to the parental- and self-reported data should be considered.

Perceptual warping exposes categorical representations for speech in human brainstem responses

The brain transforms continuous acoustic events into discrete category representations to downsample the speech signal for our perceptual-cognitive systems. Such phonetic categories are highly malleable, and their percepts can change depending on surrounding stimulus context. Previous work suggests these acoustic-phonetic mapping and perceptual warping of speech emerge in the brain no earlier than auditory cortex. Here, we examined whether these auditory-category phenomena inherent to speech perception occur even earlier in the human brain, at the level of auditory brainstem. We recorded speech-evoked frequency following responses (FFRs) during a task designed to induce more/less warping of listeners' perceptual categories depending on stimulus presentation order of a speech continuum (random, forward, backward directions). We used a novel clustered stimulus paradigm to rapidly record the high trial counts needed for FFRs concurrent with active behavioral tasks. We found serial stimulus order caused perceptual shifts (hysteresis) near listeners' category boundary confirming identical speech tokens are perceived differentially depending on stimulus context. Critically, we further show neural FFRs during active (but not passive) listening are enhanced for prototypical vs. category-ambiguous tokens and are biased in the direction of listeners' phonetic label even for acoustically-identical speech stimuli. These findings were not observed in the stimulus acoustics nor model FFR responses generated via a computational model of cochlear and auditory nerve transduction, confirming a central origin to the effects. Our data reveal FFRs carry category-level information and suggest top-down processing actively shapes the neural encoding and categorization of speech at subcortical levels. These findings suggest the acoustic-phonetic mapping and perceptual warping in speech perception occur surprisingly early along the auditory neuroaxis, which might aid understanding by reducing ambiguity inherent to the speech signal.

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 simple model of the electrosensory electromotor loop in Gymnotus omarorum

This article introduces and tests a simple model that describes a neural network found in nature, the electrosensory control of an electromotor pacemaker. The cornerstone of the model is an early-stage filter based on the subtraction of a feedforward integrated version of the recent sensory past from the present input signal. The output of this filter governs the modulation of a premotor pacemaker command driving the sensory signal carrier generation and, in consequence, the timing of subsequent electrosensory input. This early filter has a biological parallel in the known connectivity of the first electrosensory relay within the brain stem of the weakly electric fish Gymnotus omarorum. Our biomimetic model of this active, perception-driven action-sensation cycle was contrasted with previously published and here provided new data. When the amplitude of the electrosensory input was manipulated to mimic previous experiments on the novelty detection characteristics, the model reproduces them rather faithfully. In addition, when we applied continuous variations to the input it shows that increases in stimulus amplitudes are followed by increases in the EOD rate, but decreases do not cause rate modulation suggesting a rectification in some stage of the loop. These behavioral experiments confirmed results generated the simulations suggesting that beyond explaining the novelty detection process this simple model is a good description of the electrosensory -electromotor loop in pulse weakly electric fish.

The Understanding of ON-Edge Motion Detection Through the Simulation Based on the Connectome of ’s Optic Lobe

The optic lobe of the fly is one of the prominent model systems for the neural mechanism of the motion detection. How a fly who lives under various visual situations of the nature processes the information from at most a few thousands of ommatidia in their neural circuit for the detection of moving objects is not exactly clear though many computational models of the fly optic lobe as a moving objects detector were suggested. Here we attempted to elucidate the mechanisms of ON-edge motion detection by a simulation approach based on the TEM connectome of Drosophila. Our simulation model of the optic lobe with the NEURON simulator that covers the full scale of ommatidia, reproduced the characteristics of the receptor neurons, lamina monopolar neurons, and T4 cells in the lobula. The contribution of each neuron can be estimated by changing synaptic connection strengths in the simulation and measuring the response to the motion stimulus. Those show the paradelle pathway provide motion detection in the fly optic lobe has more robustness and is more sophisticated than a simple combination of HR and BL systems.

Auditory cortex modelled as a dynamical network of oscillators: understanding event-related fields and their adaptation

Adaptation, the reduction of neuronal responses by repetitive stimulation, is a ubiquitous feature of auditory cortex (AC). It is not clear what causes adaptation, but short-term synaptic depression (STSD) is a potential candidate for the underlying mechanism. In such a case, adaptation can be directly linked with the way AC produces context-sensitive responses such as mismatch negativity and stimulus-specific adaptation observed on the single-unit level. We examined this hypothesis via a computational model based on AC anatomy, which includes serially connected core, belt, and parabelt areas. The model replicates the event-related field (ERF) of the magnetoencephalogram as well as ERF adaptation. The model dynamics are described by excitatory and inhibitory state variables of cell populations, with the excitatory connections modulated by STSD. We analysed the system dynamics by linearising the firing rates and solving the STSD equation using time-scale separation. This allows for characterisation of AC dynamics as a superposition of damped harmonic oscillators, so-called normal modes. We show that repetition suppression of the N1m is due to a mixture of causes, with stimulus repetition modifying both the amplitudes and the frequencies of the normal modes. In this view, adaptation results from a complete reorganisation of AC dynamics rather than a reduction of activity in discrete sources. Further, both the network structure and the balance between excitation and inhibition contribute significantly to the rate with which AC recovers from adaptation. This lifetime of adaptation is longer in the belt and parabelt than in the core area, despite the time constants of STSD being spatially homogeneous. Finally, we critically evaluate the use of a single exponential function to describe recovery from adaptation.

The influence of phoneme contexts on adaptation in vowel-evoked envelope following responses

Repeated stimulus presentation leads to neural adaptation and consequent amplitude reduction in vowel-evoked envelope following responses (EFRs)-a response that reflects neural activity phase-locked to envelope periodicity. EFRs are elicited by vowels presented in isolation or in the context of other phonemes such as in syllables. While context phonemes could exert some forward influence on vowel-evoked EFRs, they may reduce the degree of adaptation. Here, we evaluated whether the properties of context phonemes between consecutive vowel stimuli influence adaptation. EFRs were elicited by the low-frequency first formant (resolved harmonics) and mid-to-high frequency second and higher formants (unresolved harmonics) of a male-spoken/i/when the presence, number, and predictability of context phonemes (/s/, /a/, /∫/, /u/) between vowel repetitions varied. Monitored over four iterations of /i/, adaptation was evident only for EFRs elicited by the unresolved harmonics. EFRs elicited by the unresolved harmonics decreased in amplitude by ~16-20 nV (10-17%) after the first presentation of/i/and remained stable thereafter. EFR adaptation was reduced by the presence of a context phoneme, but the reduction did not change with their number or predictability. The presence of a context phoneme, however, attenuated EFRs by a degree similar to that caused by adaptation (~21-23 nV). Such a trade-off in the short- and long-term influence of context phonemes suggests that the benefit of interleaving EFR-eliciting vowels with other context phonemes depends on whether the use of consonant-vowel syllables is critical to improve the validity of EFR applications.

Alzheimer's Disease, Hearing Loss, and Deviance Detection

Age-related hearing loss is a widespread condition among the elderly, affecting communication and social participation. Given its high incidence, it is not unusual that individuals suffering from age-related hearing loss also suffer from other age-related neurodegenerative diseases, a scenario which severely impacts their quality of life. Furthermore, recent studies have identified hearing loss as a relevant risk factor for the development of dementia due to Alzheimer’s disease, although the underlying associations are still unclear. In order to cope with the continuous flow of auditory information, the brain needs to separate repetitive sounds from rare, unexpected sounds, which may be relevant. This process, known as deviance detection, is a key component of the sensory perception theory of predictive coding. According to this framework, the brain would use the available incoming information to make predictions about the environment and signal the unexpected stimuli that break those predictions. Such a system can be easily impaired by the distortion of auditory information processing that accompanies hearing loss. Changes in cholinergic neuromodulation have been found to alter auditory deviance detection both in humans and animal models. Interestingly, some theories propose a role for acetylcholine in the development of Alzheimer’s disease, the most common type of dementia. Acetylcholine is involved in multiple neurobiological processes such as attention, learning, memory, arousal, sleep and/or cognitive reinforcement, and has direct influence on the auditory system at the levels of the inferior colliculus and auditory cortex. Here we comment on the possible links between acetylcholine, hearing loss, and Alzheimer’s disease, and association that is worth further investigation.

Separate Functional Subnetworks of Excitatory Neurons Show Preference to Periodic and Random Sound Structures

Auditory cortex (ACX) neurons are sensitive to spectro-temporal sound patterns and violations in patterns induced by rare stimuli embedded within streams of sounds. We investigate the auditory cortical representation of repeated presentations of sequences of sounds with standard stimuli (common) with an embedded deviant (rare) stimulus in two conditions, Periodic (Fixed deviant position) or Random (Random deviant position). We used extracellular single-unit and two-photon Ca2+ imaging recordings in layer 2/3 neurons of the mouse (Mus musculus) ACX of either sex. Population single-unit average responses increased over repetitions in the Random condition and were suppressed or did not change in the Periodic condition, showing general irregularity preference. A subset of neurons showed the opposite behavior, indicating regularity preference. Furthermore, pairwise noise correlations were higher in the Random condition than in the Periodic condition, suggesting a role of recurrent connections in the observed differential adaptation. Functional two-photon Ca2+ imaging showed that excitatory (EX), and inhibitory (IN) neurons [parvalbumin-positive (PV) and somatostatin-positive (SOM)] also had different categories of long-term adaptation as observed with single-units. However, examination of functional connectivity between pairs of neurons of different categories showed that EX-PV connected pairs behaved opposite to the EX-EX and EX-SOM pairs, with more connections outside category in Random condition than Periodic condition. Finally, considering Regularity, Irregularity, and no preference of connected pairs of neurons showed that EX-EX and EX-SOM pairs were in largely separate functional subnetworks with different preferences, not EX-PV pairs. Thus, separate subnetworks underlie coding of periodic and random sound sequences.SIGNIFICANCE STATEMENT Studying how the auditory cortex (ACX) neurons respond to streams of sound sequences help us understand the importance of changes in dynamic acoustic noisy scenes around us. Humans and animals are sensitive to regularity and its violations in sound sequences. Psychophysical tasks in humans show that the auditory brain differentially responds to Periodic and Random structures, independent of the listener's attentional states. Here, we show that mouse ACX L2/3 neurons detect changes and respond differently to patterns over long-time scales. The differential functional connectivity profile obtained in response to two different sound contexts suggests the vital role of recurrent connections in the auditory cortical network. Furthermore, the excitatory-inhibitory neuronal interactions can contribute to detecting the changing sound patterns.

Loss of central mineralocorticoid or glucocorticoid receptors impacts auditory nerve processing in the cochlea

The key auditory signature that may associate peripheral hearing with central auditory cognitive defects remains elusive. Suggesting the involvement of stress receptors, we here deleted the mineralocorticoid and glucocorticoid receptors (MR and GR) using a CaMKIIα-based tamoxifen-inducible Cre^ERT2/loxP approach to generate mice with single or double deletion of central but not cochlear MR and GR. Hearing thresholds of MRGR^{CaMKIIαCreERT2} conditional knockouts (cKO) were unchanged, whereas auditory nerve fiber (ANF) responses were larger and faster and auditory steady state responses were improved. Subsequent analysis of single MR or GR cKO revealed discrete roles for both, central MR and GR on cochlear functions. Limbic MR deletion reduced inner hair cell (IHC) ribbon numbers and ANF responses. In contrast, GR deletion shortened the latency and improved the synchronization to amplitude-modulated tones without affecting IHC ribbon numbers. These findings imply that stress hormone-dependent functions of central MR/GR contribute to “precognitive” sound processing in the cochlea.

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Top-down MR/GR signaling differentially contributes to cochlear sound processing

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Limbic MR stimulates auditory nerve fiber discharge rates

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Central GR deteriorates auditory nerve fiber synchrony

Memory-Paced Tapping to Auditory Rhythms: Effects of Rate, Speech, and Motor Engagement

PURPOSE

Humans have a near-automatic tendency to entrain their motor actions to rhythms in the environment. Entrainment has been hypothesized to play an important role in processing naturalistic stimuli, such as speech and music, which have intrinsically rhythmic properties. Here, we studied two facets of entraining one's rhythmic motor actions to an external stimulus: (a) synchronized finger tapping to auditory rhythmic stimuli and (b) memory-paced reproduction of a previously heard rhythm.

METHOD

Using modifications of the Synchronization-Continuation tapping paradigm, we studied how these two rhythmic behaviors were affected by different stimulus and task features. We tested synchronization and memory-paced tapping for a broad range of rates, from stimulus onset asynchrony of subsecond to suprasecond, both for strictly isochronous tone sequences and for rhythmic speech stimuli (counting from 1 to 10), which are more ecological yet less isochronous. We also asked what role motor engagement plays in forming a stable internal representation for rhythms and guiding memory-paced tapping.

RESULTS AND CONCLUSIONS

Our results show that individuals can flexibly synchronize their motor actions to a very broad range of rhythms. However, this flexibility does not extend to memory-paced tapping, which is accurate only in a narrower range of rates, around ~1.5 Hz. This pattern suggests that intrinsic rhythmic defaults in the auditory and/or motor system influence the internal representation of rhythms, in the absence of an external pacemaker. Interestingly, memory-paced tapping for speech rhythms and simple tone sequences shared similar "optimal rates," although with reduced accuracy, suggesting that internal constraints on rhythmic entrainment generalize to more ecological stimuli. Last, we found that actively synchronizing to tones versus passively listening to them led to more accurate memory-paced tapping performance, which emphasizes the importance of action-perception interactions in forming stable entrainment to external rhythms.

Changes in the spatiotemporal pattern of spontaneous activity across a cortical column after noise trauma

In the auditory modality, noise trauma has often been used to investigate cortical plasticity as it causes cochlear hearing loss. One limitation of these past studies, however, is that the effects of noise trauma have been mostly documented at the granular layer, which is the main cortical recipient of thalamic inputs. Importantly, the cortex is composed of six different layers each having its own pattern of connectivity and specific role in sensory processing. The present study aims at investigating the effects of acute and chronic noise trauma on the laminar pattern of spontaneous activity in primary auditory cortex of the anesthetized guinea pig. We show that spontaneous activity is dramatically altered across cortical layers after acute and chronic noise-induced hearing loss. First, spontaneous activity was globally enhanced across cortical layers, both in terms of firing rate and amplitude of spike-triggered average of local field potentials. Second, current source density on (spontaneous) spike-triggered average of local field potentials indicates that current sinks develop in the supra- and infragranular layers. These latter results suggest that supragranular layers become a major input recipient and that the propagation of spontaneous activity over a cortical column is greatly enhanced after acute and chronic noise-induced hearing loss. We discuss the possible mechanisms and functional implications of these changes.

Vocal emotion adaptation aftereffects within and across speaker genders: Roles of timbre and fundamental frequency

While the human perceptual system constantly adapts to the environment, some of the underlying mechanisms are still poorly understood. For instance, although previous research demonstrated perceptual aftereffects in emotional voice adaptation, the contribution of different vocal cues to these effects is unclear. In two experiments, we used parameter-specific morphing of adaptor voices to investigate the relative roles of fundamental frequency (F0) and timbre in vocal emotion adaptation, using angry and fearful utterances. Participants adapted to voices containing emotion-specific information in either F0 or timbre, with all other parameters kept constant at an intermediate 50% morph level. Full emotional voices and ambiguous voices were used as reference conditions. All adaptor stimuli were either of the same (Experiment 1) or opposite speaker gender (Experiment 2) of subsequently presented target voices. In Experiment 1, we found consistent aftereffects in all adaptation conditions. Crucially, aftereffects following timbre adaptation were much larger than following F0 adaptation and were only marginally smaller than those following full adaptation. In Experiment 2, adaptation aftereffects appeared massively and proportionally reduced, with differences between morph types being no longer significant. These results suggest that timbre plays a larger role than F0 in vocal emotion adaptation, and that vocal emotion adaptation is compromised by eliminating gender-correspondence between adaptor and target stimuli. Our findings also add to mounting evidence suggesting a major role of timbre in auditory adaptation.

Corticothalamic projections deliver enhanced responses to medial geniculate body as a function of the temporal reliability of the stimulus

Ageing and challenging signal-in-noise conditions are known to engage the use of cortical resources to help maintain speech understanding. Extensive corticothalamic projections are thought to provide attentional, mnemonic and cognitive-related inputs in support of sensory inferior colliculus (IC) inputs to the medial geniculate body (MGB). Here we show that a decrease in modulation depth, a temporally less distinct periodic acoustic signal, leads to a jittered ascending temporal code, changing MGB unit responses from adapting responses to responses showing repetition enhancement, posited to aid identification of important communication and environmental sounds. Young-adult male Fischer Brown Norway rats, injected with the inhibitory opsin archaerhodopsin T (ArchT) into the primary auditory cortex (A1), were subsequently studied using optetrodes to record single-units in MGB. Decreasing the modulation depth of acoustic stimuli significantly increased repetition enhancement. Repetition enhancement was blocked by optical inactivation of corticothalamic terminals in MGB. These data support a role for corticothalamic projections in repetition enhancement, implying that predictive anticipation could be used to improve neural representation of weakly modulated sounds. KEY POINTS: In response to a less temporally distinct repeating sound with low modulation depth, medial geniculate body (MGB) single units show a switch from adaptation towards repetition enhancement. Repetition enhancement was reversed by blockade of MGB inputs from the auditory cortex. Collectively, these data argue that diminished acoustic temporal cues such as weak modulation engage cortical processes to enhance coding of those cues in auditory thalamus.

Mechanisms of Long-Latency Paired Pulse Suppression: MEG Study

Paired pulse suppression is an electrophysiological method used to evaluate sensory suppression and often applied to patients with psychiatric disorders. However, it remains unclear whether the suppression comes from specific inhibitory mechanisms, refractoriness, or fatigue. In the present study, to investigate mechanisms of suppression induced by an auditory paired pulse paradigm in 19 healthy subjects, magnetoencephalography was employed. The control stimulus was a train of 25-ms pure tones of 65 dB SPL for 2500 ms. In order to evoke a test response, the sound pressure of two consecutive tones at 2200 ms in the control sound was increased to 80 dB (Test stimulus). Similar sound pressure changes were also inserted at 1000 (CS2) and 1600 (CS1) ms as conditioning stimuli. Four stimulus conditions were used; (1) Test alone, (2) Test + CS1, (3) Test + CS1 + CS2, and (4) Test + CS2, with the four sound stimuli randomly presented and cortical responses averaged at least 100 times for each condition. The baseline-to-peak and peak-to-peak amplitudes of the P50m, N100m, and P200m components of the test response were compared among the four conditions. In addition, the response to CS1 was compared between conditions (2) and (3). The results showed significant test response suppression by CS1. While the response to CS1 was significantly suppressed when CS2 was present, it did not affect suppression of the test response by CS1. It was thus suggested that the amplitude of the response to a conditioning stimulus is not a factor to determine the inhibitory effects of the test response, indicating that suppression is due to an external influence on the excitatory pathway.

Corollary discharge enables proprioception from lateral line sensory feedback

Animals modulate sensory processing in concert with motor actions. Parallel copies of motor signals, called corollary discharge (CD), prepare the nervous system to process the mixture of externally and self-generated (reafferent) feedback that arises during locomotion. Commonly, CD in the peripheral nervous system cancels reafference to protect sensors and the central nervous system from being fatigued and overwhelmed by self-generated feedback. However, cancellation also limits the feedback that contributes to an animal's awareness of its body position and motion within the environment, the sense of proprioception. We propose that, rather than cancellation, CD to the fish lateral line organ restructures reafference to maximize proprioceptive information content. Fishes' undulatory body motions induce reafferent feedback that can encode the body's instantaneous configuration with respect to fluid flows. We combined experimental and computational analyses of swimming biomechanics and hair cell physiology to develop a neuromechanical model of how fish can track peak body curvature, a key signature of axial undulatory locomotion. Without CD, this computation would be challenged by sensory adaptation, typified by decaying sensitivity and phase distortions with respect to an input stimulus. We find that CD interacts synergistically with sensor polarization to sharpen sensitivity along sensors' preferred axes. The sharpening of sensitivity regulates spiking to a narrow interval coinciding with peak reafferent stimulation, which prevents adaptation and homogenizes the otherwise variable sensor output. Our integrative model reveals a vital role of CD for ensuring precise proprioceptive feedback during undulatory locomotion, which we term external proprioception.

Arousal State-Dependence of Interactions Between Short- and Long-Term Auditory Novelty Responses in Human Subjects

In everyday life, predictable sensory stimuli are generally not ecologically informative. By contrast, novel or unexpected stimuli signal ecologically salient changes in the environment. This idea forms the basis of the predictive coding hypothesis: efficient sensory encoding minimizes neural activity associated with predictable backgrounds and emphasizes detection of changes in the environment. In real life, the brain must resolve multiple unexpected sensory events occurring over different time scales. The local/global deviant experimental paradigm examines auditory predictive coding over multiple time scales. For short-term novelty [hundreds of milliseconds; local deviance (LD)], sequences of identical sounds (/xxxxx/) are interspersed with sequences that contain deviants (/xxxxy/). Long-term novelty [several seconds; global deviance (GD)] is created using either (a) frequent /xxxxx/ and infrequent /xxxxy/ sequences, or (b) frequent /xxxxy/ and infrequent /xxxxx/ sequences. In scenario (a), there is both an LD and a GD effect (LDGD, "double surprise"). In (b), the global deviant is a local standard, i.e., sequence of identical sounds (LSGD). Cortical responses reflecting LD and GD originate in different brain areas, have a different time course, and are differentially sensitive to general anesthesia. Neural processes underlying LD and GD have been shown to interact, reflecting overlapping networks subserving the detection of novel auditory stimuli. This study examined these interactions using intracranial electroencephalography in neurosurgical patients. Subjects performed a GD target detection task before and during induction of anesthesia with propofol. Recordings were made from the auditory cortex, surrounding auditory-related and prefrontal cortex in awake, sedated, and unresponsive states. High gamma activity was used to measure the neural basis of local-by-global novelty interactions. Positive interaction was defined as a greater response to the double surprise LDGD condition compared to LSGD. Negative interaction was defined as a weaker response to LDGD. Positive interaction was more frequent than negative interaction and was primarily found in auditory cortex. Negative interaction typically occurred in prefrontal cortex and was more sensitive to general anesthesia. Temporo-parietal auditory-related areas exhibited both types of interaction. These interactions may have relevance in a clinical setting as biomarkers of conscious perception in the assessment of depth of anesthesia and disorders of consciousness.

Effect of Noise on Sleep and Autonomic Activity in Children according to Source

BACKGROUND

Noise has been a major issue in children due to its effect on emotional symptoms and sleep problems. The present study investigated the effect of noise on sleep and autonomic activity in children according to three variables, namely, road traffic noise, aircraft noise, and noise sensitivity (NS).

METHODS

The study is epidemiological in nature. A total of 474 subjects of four elementary schools were evaluated in conjunction with the 2014 noise map data gathered from two metropolitan regions, Seoul and Ulsan, in South Korea. Each subject completed the children's sleep habits questionnaire, and heart rate variability (HRV) was recorded. Analysis of covariance was performed using monthly income as a covariate.

RESULTS

Aircraft noise was associated with night waking (P = 0.047), whereas no significant association was observed between sleep and road traffic noise. After stratifying by NS, no significant results were obtained for road traffic noise. However, high levels of aircraft noise in the high-NS group were associated with high degrees of bedtime resistance (P = 0.049). In terms of HRV, no significant difference was observed in the results between groups.

CONCLUSION

Road traffic noise did not significantly alter sleep or autonomic activity in children, whereas aircraft noise exerted a negative effect on sleep. The findings suggest that the impact of noise on sleep in children varies depending on noise sources.

Neural Field Theory of Evoked Response Sequences and Mismatch Negativity With Adaptation

Physiologically based neural field theory of the corticothalamic system is used to calculate the responses evoked by trains of auditory stimuli that correspond to different cortical locations via the tonotopic map. The results are shown to account for standard and deviant evoked responses to frequent and rare stimuli, respectively, in the auditory oddball paradigms widely used in human cognitive studies, and the so-called mismatch negativity between them. It also reproduces a wide range of other effects and variants, including the mechanism by which a change in standard responses relative to deviants can develop through adaptation, different responses when two deviants are presented in a row or a standard is presented after two deviants, relaxation of standard responses back to deviant form after a stimulus-free period, and more complex sequences. Some cases are identified in which adaptation does not account for the whole difference between standard and deviant responses. The results thus provide a systematic means to determine how much of the response is due to adaptation in the system comprising the primary auditory cortex and medial geniculate nucleus, and how much requires involvement of higher-level processing.

The influence of variability on mismatch negativity amplitude

Mismatch Negativity (MMN) to pattern deviations reveals exquisite pattern detection ability in the brain. MMN amplitude is proposed to be precision-weighted, being inversely proportional to variability within a patterned sound sequence. Two experiments were conducted to determine whether pattern variability, shown to influence MMN to simple pattern deviance, also extends to MMN elicited to abstract pattern deviants. Participants were presented with 3-tone triplet sequences that were defined by regular frequency ascendance with adjacent (A<B<C) or non-adjacent (A<C) dependency. The triplets were defined by an abstract pattern in that the starting frequency of A roamed randomly between 500-3700 Hz. Using variants of these sequences over two studies the results show that MMN was elicited to rare A > C deviants for adjacent and non-adjacent dependencies, was smaller for the latter, was impervious to variance in tone loudness, but showed prolonged sensitivity to the level of variability at sequence onset.

Sensory adaptation at ribbon synapses in the zebrafish lateral line

Adaptation is used by sensory systems to adjust continuously their sensitivity to match changes in environmental stimuli. In the auditory and vestibular systems, the release properties of glutamate-containing vesicles at the hair-cell ribbon synapses play a crucial role in sensory adaptation, thus shaping the neural response to sustained stimulation. How ribbon synapses regulate the release of glutamate and how they modulate afferent responses in vivo is still largely unknown. Here, we have used two-photon imaging and electrophysiology to investigate the synaptic transfer characteristics of the hair cells in the context of sensory adaptation in live zebrafish. Prolonged and repeated water-jet stimulation of the hair-cell stereociliary bundles caused adaptation of the action potential firing rate elicited in the afferent neurons. By monitoring glutamate at ribbon synapses using time-lapse imaging, we identified two kinetically distinct release components: a rapid response that was exhausted within 50-100 ms and a slower and sustained response lasting the entire stimulation. After repeated stimulations, the recovery of the fast component followed a biphasic time course. Depression of glutamate release was largely responsible for the rapid firing rate adaptation recorded in the afferent neurons. However, postsynaptic Ca²⁺ responses had a slower recovery time course than that of glutamate release, indicating that they are also likely to contribute to the afferent firing adaptation. Hair cells also exhibited a form of adaptation during inhibitory bundle stimulations. We conclude that hair cells have optimised their synaptic machinery to encode prolonged stimuli and to maintain their sensitivity to new incoming stimuli.

Contralateral proximal interference

A contralateral "cue" tone presented in continuous broadband noise both lowers the threshold of a signal tone by guiding attention to it and raises its threshold by interference. Here, signal tones were fixed in duration (40 ms, 52 ms with ramps), frequency (1500 Hz), timing, and level, so attention did not need guidance. Interference by contralateral cues was studied in relation to cue-signal proximity, cue-signal temporal overlap, and cue-signal order (cue after: backward interference, BI; or cue first: forward interference, FI). Cues, also ramped, were 12 dB above the signal level. Long cues (300 or 600 ms) raised thresholds by 5.3 dB when the signal and cue overlapped and by 5.1 dB in FI and 3.2 dB in BI when cues and signals were separated by 40 ms. Short cues (40 ms) raised thresholds by 4.5 dB in FI and 4.0 dB in BI for separations of 7 to 40 ms, but by ∼13 dB when simultaneous and in phase. FI and BI are comparable in magnitude and hardly increase when the signal is close in time to abrupt cue transients. These results do not support the notion that masking of the signal is due to the contralateral cue onset/offset transient response. Instead, sluggish attention or temporal integration may explain contralateral proximal interference.

Predicting Dementia With Prefrontal Electroencephalography and Event-Related Potential

Objective: To examine whether prefrontal electroencephalography (EEG) can be used for screening dementia.

Methods: We estimated the global cognitive decline using the results of Mini-Mental Status Examination (MMSE), measurements of brain activity from resting-state EEG, responses elicited by auditory stimulation [sensory event-related potential (ERP)], and selective attention tasks (selective-attention ERP) from 122 elderly participants (dementia, 35; control, 87). We investigated that the association between MMSE and each EEG/ERP variable by using Pearson’s correlation coefficient and performing univariate linear regression analysis. Kernel density estimation was used to examine the distribution of each EEG/ERP variable in the dementia and non-dementia groups. Both Univariate and multiple logistic regression analyses with the estimated odds ratios were conducted to assess the associations between the EEG/ERP variables and dementia prevalence. To develop the predictive models, five-fold cross-validation was applied to multiple classification algorithms.

Results: Most prefrontal EEG/ERP variables, previously known to be associated with cognitive decline, show correlations with the MMSE score (strongest correlation has |r| = 0.68). Although variables such as the frontal asymmetry of the resting-state EEG are not well correlated with the MMSE score, they indicate risk factors for dementia. The selective-attention ERP and resting-state EEG variables outperform the MMSE scores in dementia prediction (areas under the receiver operating characteristic curve of 0.891, 0.824, and 0.803, respectively). In addition, combining EEG/ERP variables and MMSE scores improves the model predictive performance, whereas adding demographic risk factors do not improve the prediction accuracy.

Conclusion: Prefrontal EEG markers outperform MMSE scores in predicting dementia, and additional prediction accuracy is expected when combining them with MMSE scores.

Significance: Prefrontal EEG is effective for screening dementia when used independently or in combination with MMSE.

Inverted central auditory hierarchies for encoding local intervals and global temporal patterns

In sensory systems, representational features of increasing complexity emerge at successive stages of processing. In the mammalian auditory pathway, the clearest change from brainstem to cortex is defined by what is lost, not by what is gained, in that high-fidelity temporal coding becomes increasingly restricted to slower acoustic modulation rates.^1,2 Here, we explore the idea that sluggish temporal processing is more than just an inability for fast processing, but instead reflects an emergent specialization for encoding sound features that unfold on very slow timescales.^3,4 We performed simultaneous single unit ensemble recordings from three hierarchical stages of auditory processing in awake mice - the inferior colliculus (IC), medial geniculate body of the thalamus (MGB) and primary auditory cortex (A1). As expected, temporal coding of brief local intervals (0.001 - 0.1 s) separating consecutive noise bursts was robust in the IC and declined across MGB and A1. By contrast, slowly developing (∼1 s period) global rhythmic patterns of inter-burst interval sequences strongly modulated A1 spiking, were weakly captured by MGB neurons, and not at all by IC neurons. Shifts in stimulus regularity were not represented by changes in A1 spike rates, but rather in how the spikes were arranged in time. These findings show that low-level auditory neurons with fast timescales encode isolated sound features but not the longer gestalt, while the extended timescales in higher-level areas can facilitate sensitivity to slower contextual changes in the sensory environment.

Pre-attentive auditory change detection for rapid auditory transient combinations: Insight from age-related processing changes

The N1 event-related potential (ERP) enhancement to auditory transients preceded briefly by another transient has been interpreted as a reflection of latent inhibition, or alternatively, as a superimposing mismatch negativity (MMN) to rare transient event combinations. In a previous study (Volosin, Gaál, & Horváth, 2017a), when rare glides preceded frequent gaps by 150 ms in continuous tones, gap-related N1 was enhanced in younger adults while P2 was attenuated both in younger and older adults, which could be parsimoniously explained by MMN overlap which was delayed with aging. The present study replicated and extended these results with a condition in which the roles of the two event types were reversed. Transients separated by 150 ms elicited delayed MMN in older adults, supporting the MMN interpretation over the latent inhibition account. Furthermore, the divergence of N1 and MMN elicitation patterns demonstrated the independence of N1 and MMN.

A role of oligodendrocytes in information processing

Myelinating oligodendrocytes enable fast propagation of action potentials along the ensheathed axons. In addition, oligodendrocytes play diverse non-canonical roles including axonal metabolic support and activity-dependent myelination. An open question remains whether myelination also contributes to information processing in addition to speeding up conduction velocity. Here, we analyze the role of myelin in auditory information processing using paradigms that are also good predictors of speech understanding in humans. We compare mice with different degrees of dysmyelination using acute multiunit recordings in the auditory cortex, in combination with behavioral readouts. We find complex alterations of neuronal responses that reflect fatigue and temporal acuity deficits. We observe partially discriminable but similar deficits in well myelinated mice in which glial cells cannot fully support axons metabolically. We suggest a model in which myelination contributes to sustained stimulus perception in temporally complex paradigms, with a role of metabolically active oligodendrocytes in cortical information processing.

Early cortical processing of pitch height and the role of adaptation and musicality

Pitch is an important perceptual feature; however, it is poorly understood how its cortical correlates are shaped by absolute vs relative fundamental frequency (f₀), and by neural adaptation. In this study, we assessed transient and sustained auditory evoked fields (AEFs) at the onset, progression, and offset of short pitch height sequences, taking into account the listener's musicality. We show that neuromagnetic activity reflects absolute f₀ at pitch onset and offset, and relative f₀ at transitions within pitch sequences; further, sequences with fixed f₀ lead to larger response suppression than sequences with variable f₀ contour, and to enhanced offset activity. Musical listeners exhibit stronger f₀-related AEFs and larger differences between their responses to fixed vs variable sequences, both within sequences and at pitch offset. The results resemble prominent psychoacoustic phenomena in the perception of pitch contours; moreover, they suggest a strong influence of adaptive mechanisms on cortical pitch processing which, in turn, might be modulated by a listener's musical expertise.

Perceptual variability: Implications for learning and generalization

The generalization of learned behavior has been extensively investigated, but accounting for variance in generalized responding remains a challenge. Based on recent advances, we demonstrate that the inclusion of perceptual measures in generalization research may lead to a better understanding of both intra- and interindividual differences in generalization. We explore various ways through which perceptual variability can influence generalized responding. We investigate its impact on the ability to discriminate between stimuli and how similarity between stimuli may be variable, rather than fixed, because of it. Subsequently, we argue that perceptual variations can yield different learning experiences and that interindividual differences in generalized responding may be understood from this perspective. Finally, we point to the role of memory and decision-making within this context. Throughout this paper, we argue that accounting for perception in current generalization protocols will improve the precision of obtained generalization gradients and the ability to infer latent mechanisms. This can inspire future attempts to use generalization gradients as a (clinical) predictor or to relate them to individual traits and neural correlates and, ultimately, may lead to new theoretical and clinical insights.

Assessing the perceived reverberation in different rooms for a set of musical instrument sounds

Previous research has shown that the perceived reverberation in a room, or reverberance, depends on the sound source that is being listened to. In a study by Osses Vecchi, Kohlrausch, Lachenmayr, and Mommertz [(2017). J. Acoust. Soc. Am. 141(4), EL381-EL387], reverberance estimates obtained from an auditory model for 23 musical instrument sounds in 8 rooms predicted a sound-source dependency. As a follow-up to that study, a listening experiment with 24 participants was conducted using a subset of the original sounds with the purpose of mapping each test sound onto a reverberance scale. Consistent with the literature, the experimental reverberance estimates were significantly dependent on the instrument sound being listened to, but on the top of that, the estimates were significantly correlated with simulated reverberance estimates for the test stimuli as well as for the previously reported long-duration sounds.

Do rat auditory event related potentials exhibit human mismatch negativity attributes related to predictive coding?

Rodent models play a significant role in understanding disease mechanisms and the screening of new treatments. With regard to psychiatric disorders such as schizophrenia, however, it is difficult to replicate the human symptoms in rodents because these symptoms are often either 'uniquely human' or are only conveyed via self-report. There is a growing interest in rodent mismatch responses (MMRs) as a translatable 'biomarker' for disorders such as schizophrenia. In this review, we will summarize the attributes of human MMN, and discuss the scope of exploring the attributes of human MMN in rodents. Here, we examine how reliably MMRs that are measured in rats mimic human attributes, and present original data examining whether manipulations of stimulus conditions known to modulate human MMN, do the same for rat MMRs. Using surgically-implanted epidural electroencephalographic electrodes and wireless telemetry in freely-moving rats, we observed human-like modulations of MMRs, namely that larger MMRs were elicited to unexpected (deviant) stimuli that a) had a larger change in pitch compared to the expected (standard) stimulus, b) were less frequently presented (lower probability), and c) had no jitter (stable stimulus onset asynchrony) compared to high jitter. Overall, these findings contribute to the mounting evidence for rat MMRs as a good analogue of human MMN, bolstering the development of a novel approach in future to validate the preclinical models based on a translatable biomarker, MMN.

Deviance detection in physiologically identified cell types in the rat auditory cortex

Auditory deviance detection is a function of the auditory system that allows reduction of the processing demand for repetitive stimuli while stressing unpredictable ones, which are potentially more informative. Deviance detection has been extensively studied in humans using the oddball paradigm, which evokes an event-related potential known as mismatch negativity (MMN). The same stimulation paradigms are used in animal studies that aim to elucidate the neuronal mechanisms underlying deviance detection. In order to understand the circuitry responsible for deviance detection in the auditory cortex (AC), it is necessary to determine the properties of excitatory and inhibitory neurons separately. Measuring the spike widths of neurons recorded extracellularly from the anaesthetized rat AC, we classified them as fast spiking or regular spiking units. These two neuron types are generally considered as putative inhibitory or excitatory, respectively. In response to an oddball paradigm, we found that both types of units showed similar amounts of deviance detection overall. When considering each AC field separately, we found that only in A1 fast spiking neurons showed higher deviance detection levels than regular spiking neurons, while in the rest of the fields there was no such distinction. Interpreting these responses in the context of the predictive coding framework, we found that the responses of both types of units reflect mainly prediction error signaling (i.e., genuine deviance detection) rather than repetition suppression.

In vivo whole-cell recordings of stimulus-specific adaptation in the inferior colliculus

The inferior colliculus is an auditory structure where inputs from multiple lower centers converge, allowing the emergence of complex coding properties of auditory information such as stimulus-specific adaptation. Stimulus-specific adaptation is the adaptation of neuronal responses to a specific repeated stimulus, which does not entirely generalize to other new stimuli. This phenomenon provides a mechanism to emphasize saliency and potentially informative sensory inputs. Stimulus-specific adaptation has been traditionally studied analyzing the somatic spiking output. However, studies that correlate within the same inferior colliculus neurons their intrinsic properties, subthreshold responses and the level of acoustic stimulus-specific adaptation are still pending. For this, we recorded in vivo whole-cell patch-clamp neurons in the mouse inferior colliculus while stimulating with current injections or the classic auditory oddball paradigm. Our data based on cases of ten neuron, suggest that although passive properties were similar, intrinsic properties differed between adapting and non-adapting neurons. Non-adapting neurons showed a sustained-regular firing pattern that corresponded to central nucleus neurons and adapting neurons at the inferior colliculus cortices showed variable firing patterns. Our current results suggest that synaptic stimulus-specific adaptation was variable and could not be used to predict the presence of spiking stimulus-specific adaptation. We also observed a small trend towards hyperpolarized membrane potentials in adapting neurons and increased synaptic inhibition with consecutive stimulus repetitions in all neurons. This finding indicates a more simple type of adaptation, potentially related to potassium conductances. Hence, these data represent a modest first step in the intracellular study of stimulus-specific adaptation in inferior colliculus neurons in vivo that will need to be expanded with pharmacological manipulations to disentangle specific ionic channels participation.

Streaming of Repeated Noise in Primary and Secondary Fields of Auditory Cortex

Statistical regularities in natural sounds facilitate the perceptual segregation of auditory sources, or streams. Repetition is one cue that drives stream segregation in humans, but the neural basis of this perceptual phenomenon remains unknown. We demonstrated a similar perceptual ability in animals by training ferrets of both sexes to detect a stream of repeating noise samples (foreground) embedded in a stream of random samples (background). During passive listening, we recorded neural activity in primary auditory cortex (A1) and secondary auditory cortex (posterior ectosylvian gyrus, PEG). We used two context-dependent encoding models to test for evidence of streaming of the repeating stimulus. The first was based on average evoked activity per noise sample and the second on the spectro-temporal receptive field. Both approaches tested whether differences in neural responses to repeating versus random stimuli were better modeled by scaling the response to both streams equally (global gain) or by separately scaling the response to the foreground versus background stream (stream-specific gain). Consistent with previous observations of adaptation, we found an overall reduction in global gain when the stimulus began to repeat. However, when we measured stream-specific changes in gain, responses to the foreground were enhanced relative to the background. This enhancement was stronger in PEG than A1. In A1, enhancement was strongest in units with low sparseness (i.e., broad sensory tuning) and with tuning selective for the repeated sample. Enhancement of responses to the foreground relative to the background provides evidence for stream segregation that emerges in A1 and is refined in PEG.SIGNIFICANCE STATEMENT To interact with the world successfully, the brain must parse behaviorally important information from a complex sensory environment. Complex mixtures of sounds often arrive at the ears simultaneously or in close succession, yet they are effortlessly segregated into distinct perceptual sources. This process breaks down in hearing-impaired individuals and speech recognition devices. By identifying the underlying neural mechanisms that facilitate perceptual segregation, we can develop strategies for ameliorating hearing loss and improving speech recognition technology in the presence of background noise. Here, we present evidence to support a hierarchical process, present in primary auditory cortex and refined in secondary auditory cortex, in which sound repetition facilitates segregation.

Decomposing neural responses to melodic surprise in musicians and non-musicians: Evidence for a hierarchy of predictions in the auditory system

Neural responses to auditory surprise are typically studied with highly unexpected, disruptive sounds. Consequently, little is known about auditory prediction in everyday contexts that are characterized by fine-grained, non-disruptive fluctuations of auditory surprise. To address this issue, we used IDyOM, a computational model of auditory expectation, to obtain continuous surprise estimates for a set of newly composed melodies. Our main goal was to assess whether the neural correlates of non-disruptive surprising sounds in a musical context are affected by musical expertise. Using magnetoencephalography (MEG), auditory responses were recorded from musicians and non-musicians while they listened to the melodies. Consistent with a previous study, the amplitude of the N1m component increased with higher levels of computationally estimated surprise. This effect, however, was not different between the two groups. Further analyses offered an explanation for this finding: Pitch interval size itself, rather than probabilistic prediction, was responsible for the modulation of the N1m, thus pointing to low-level sensory adaptation as the underlying mechanism. In turn, the formation of auditory regularities and proper probabilistic prediction were reflected in later components: The mismatch negativity (MMNm) and the P3am, respectively. Overall, our findings reveal a hierarchy of expectations in the auditory system and highlight the need to properly account for sensory adaptation in research addressing statistical learning.

Cortical Microcircuit Mechanisms of Mismatch Negativity and Its Underlying Subcomponents

In the neocortex, neuronal processing of sensory events is significantly influenced by context. For instance, responses in sensory cortices are suppressed to repetitive or redundant stimuli, a phenomenon termed “stimulus-specific adaptation” (SSA). However, in a context in which that same stimulus is novel, or deviates from expectations, neuronal responses are augmented. This augmentation is termed “deviance detection” (DD). This contextual modulation of neural responses is fundamental for how the brain efficiently processes the sensory world to guide immediate and future behaviors. Notably, context modulation is deficient in some neuropsychiatric disorders such as schizophrenia (SZ), as quantified by reduced “mismatch negativity” (MMN), an electroencephalography waveform reflecting a combination of SSA and DD in sensory cortex. Although the role of NMDA-receptor function and other neuromodulatory systems on MMN is established, the precise microcircuit mechanisms of MMN and its underlying components, SSA and DD, remain unknown. When coupled with animal models, the development of powerful precision neurotechnologies over the past decade carries significant promise for making new progress into understanding the neurobiology of MMN with previously unreachable spatial resolution. Currently, rodent models represent the best tool for mechanistic study due to the vast genetic tools available. While quantifying human-like MMN waveforms in rodents is not straightforward, the “oddball” paradigms used to study it in humans and its underlying subcomponents (SSA/DD) are highly translatable across species. Here we summarize efforts published so far, with a focus on cortically measured SSA and DD in animals to maintain relevance to the classically measured MMN, which has cortical origins. While mechanistic studies that measure and contrast both components are sparse, we synthesize a potential set of microcircuit mechanisms from the existing rodent, primate, and human literature. While MMN and its subcomponents likely reflect several mechanisms across multiple brain regions, understanding fundamental microcircuit mechanisms is an important step to understand MMN as a whole. We hypothesize that SSA reflects adaptations occurring at synapses along the sensory-thalamocortical pathways, while DD depends on both SSA inherited from afferent inputs and resulting disinhibition of non-adapted neurons arising from the distinct physiology and wiring properties of local interneuronal subpopulations and NMDA-receptor function.

The release from refractoriness hypothesis of N1 of event-related potentials needs reassessment

N1 of event-related potentials (ERPs) is augmented in amplitude in ∼50-150 ms by occasional changes (deviants) in the physical features of a sound repeated at intervals of from ∼400 ms to seconds (standard). The release-from-refractoriness hypothesis links the N1 augmentation to a deviant-feature-specific neural population that is fresh to fully respond as opposed to a standard-feature-specific neural population that is unresponsive due to its post-response refractoriness. The present work explored this hypothesis in the context of ERP studies, behavioral habituation studies and studies on stimulus-specific adaptation (SSA). The idea of hundreds of milliseconds neural population-level refractoriness was observed to be founded upon negative N1 evidence (no observable effect of dishabituating stimuli on N1 to standards - the null hypothesis retained) and merely supported by positive N1 evidence (null hypotheses rejected). This idea was also found to be directly challenged by positive N1 evidence. No conclusive network- or single-neuron-level evidence was found for the refractoriness. Therefore, the validity of the release-from-refractoriness hypothesis of N1 to guide psychophysiological research needs reassessment.

The Role of Glutamate Neurotransmission in Mismatch Negativity (MMN), A Measure of Auditory Synaptic Plasticity and Change-detection

Mismatch negativity (MMN) is an electrophysiological signature that occurs in response to unexpected stimuli. It is often referred to as a measure of memory-based change detection, because the elicitation of a prediction error response relies on the formation of a prediction, which in turn, is dependent upon intact memory of previous auditory stimulation. As such, the MMN is altered in conditions in which memory is affected, such as Alzheimer's disease, schizophrenia and healthy aging. The most prominent pharmacological finding for MMN strengthens the link between MMN and synaptic plasticity, as glutamate N-methyl-d-aspartate receptor (NMDA-R) antagonists reduce the MMN response. However, recent data has begun to demonstrate that the link between NMDA-R function and MMN is not as clear as once thought, with low dose and low affinity NMDA-R antagonists observed to facilitate MMN.

Neural entrainment to music is sensitive to melodic spectral complexity

During auditory perception, neural oscillations are known to entrain to acoustic dynamics but their role in the processing of auditory information remains unclear. As a complex temporal structure that can be parameterized acoustically, music is particularly suited to address this issue. In a combined behavioral and EEG experiment in human participants, we investigated the relative contribution of temporal (acoustic dynamics) and nontemporal (melodic spectral complexity) dimensions of stimulation on neural entrainment, a stimulus-brain coupling phenomenon operationally defined here as the temporal coherence between acoustical and neural dynamics. We first highlight that low-frequency neural oscillations robustly entrain to complex acoustic temporal modulations, which underscores the fine-grained nature of this coupling mechanism. We also reveal that enhancing melodic spectral complexity, in terms of pitch, harmony, and pitch variation, increases neural entrainment. Importantly, this manipulation enhances activity in the theta (5 Hz) range, a frequency-selective effect independent of the note rate of the melodies, which may reflect internal temporal constraints of the neural processes involved. Moreover, while both emotional arousal ratings and neural entrainment were positively modulated by spectral complexity, no direct relationship between arousal and neural entrainment was observed. Overall, these results indicate that neural entrainment to music is sensitive to the spectral content of auditory information and indexes an auditory level of processing that should be distinguished from higher-order emotional processing stages.NEW & NOTEWORTHY Low-frequency (<10 Hz) cortical neural oscillations are known to entrain to acoustic dynamics, the so-called neural entrainment phenomenon, but their functional implication in the processing of auditory information remains unclear. In a behavioral and EEG experiment capitalizing on parameterized musical textures, we disentangle the contribution of stimulus dynamics, melodic spectral complexity, and emotional judgments on neural entrainment and highlight their respective spatial and spectral neural signature.

The role of adaptation in generating monotonic rate codes in auditory cortex

In primary auditory cortex, slowly repeated acoustic events are represented temporally by the stimulus-locked activity of single neurons. Single-unit studies in awake marmosets (Callithrix jacchus) have shown that a sub-population of these neurons also monotonically increase or decrease their average discharge rate during stimulus presentation for higher repetition rates. Building on a computational single-neuron model that generates stimulus-locked responses with stimulus evoked excitation followed by strong inhibition, we find that stimulus-evoked short-term depression is sufficient to produce synchronized monotonic positive and negative responses to slowly repeated stimuli. By exploring model robustness and comparing it to other models for adaptation to such stimuli, we conclude that short-term depression best explains our observations in single-unit recordings in awake marmosets. Together, our results show how a simple biophysical mechanism in single neurons can generate complementary neural codes for acoustic stimuli.