Stimulus-specific adaptation and deviance detection in the auditory system: experiments and models

Midbrain sensitivity to auditory motion studied with dichotic sweeps of broadband noise

Many neurons in the central nucleus of the inferior colliculus (IC) show sensitivity to interaural time differences (ITDs), which is thought to be relayed from the brainstem. However, studies with interaural phase modulation of pure tones showed that IC neurons have a sensitivity to changes in ITD that is not present at the level of the brainstem. This sensitivity has been interpreted as a form of sensitivity to motion. A new type of stimulus is used here to study the sensitivity of IC neurons to dynamic changes in ITD, in which broad- or narrowband stimuli are swept through a range of ITDs with arbitrary start-ITD, end-ITD, speed, and direction. Extracellular recordings were obtained under barbiturate anesthesia in the cat. We applied the same analyses as previously introduced for the study of responses to tones. We find effects of motion which are similar to those described in response to interaural phase modulation of tones. The size of the effects strongly depended on the motion parameters but was overall smaller than reported for tones. We found that the effects of motion could largely be explained by the temporal response pattern of the neuron such as adaptation and build-up. Our data add to previous evidence questioning true coding of motion at the level of the IC.

Involuntary motor responses are elicited both by rare sounds and rare pitch changes

Unpredictable deviations from an otherwise regular auditory sequence, as well as rare sounds following a period of silence, are detected automatically. Recent evidence suggests that the latter also elicit quick involuntary modulations of ongoing motor activity emerging as early as 100 ms following sound onset, which was attributed to supramodal processing. We explored such force modulations for both rare and deviant sounds. Participants (N = 29) pinched a force sensitive device and maintained a force of 1-2 N for periods of 1 min. Task-irrelevant tones were presented under two conditions. In the Rare condition, 4000 Hz tones were presented every 8-to-16 s. In the Roving condition, 4000 Hz and 2996 Hz tones were presented at rate of 1 s, with infrequent (p = 1/12) frequency changes. In the Rare condition, transient force modulations were observed with a significant increase at ~ 234 ms, and a decrease at ~ 350 ms. In the Roving condition with low frequency deviant tones, an increase in force was observed at ~ 277 ms followed by a decrease at ~ 413 ms. No significant modulations were observed during perception of high frequency deviants. These results suggest that both rare silence-breaking sounds and low-pitched deviants evoke automatic fluctuations of motor responses, which opens up the possibility that these force modulations are triggered by stimulus-specific change-detection processes.

Single neuron responses to perceptual difficulty in the mouse auditory cortex

Perceptual learning leads to improvement in behavioral performance, yet how the brain supports challenging perceptual demands is unknown. We used two photon imaging in the mouse primary auditory cortex during behavior in a Go-NoGo task designed to test perceptual difficulty. Using general linear model analysis, we found a subset of neurons that increased their responses during high perceptual demands. Single neurons increased their responses to both Go and NoGo sounds when mice were engaged in the more difficult perceptual discrimination. This increased responsiveness contributes to enhanced cortical network discriminability for the learned sounds. Under passive listening conditions, the same neurons responded weaker to the more similar sound pairs of the difficult task, and the training protocol by itself induced specific suppression to the learned sounds. Our findings identify how neuronal activity in auditory cortex is modulated during high perceptual demands, which is a fundamental feature associated with perceptual improvement.

Tonotopic Ca2+ dynamics and sound processing in auditory interneurons of the bush-cricket Mecopoda elongata

Two auditory neurons, TN-1 and ON-1, in the bush-cricket, Mecopoda elongata, have large dendritic arborisations which receive excitatory synaptic inputs from tonotopically organised axonal terminals of auditory afferents in the prothoracic ganglion. By combining intracellular microelectrode recording with calcium imaging we demonstrate that the dendrites of both neurons show a clear Ca2+ signal in response to broad-frequency species-specific chirps. Due to the organisation of the afferents frequency specific auditory activation should lead to local Ca2+ increases in their dendrites. In response to 20 ms sound pulses the dendrites of both neurons showed tonotopically organised Ca2+ increases. In ON-1 we found no evidence for a tonotopic organisation of the Ca2+ signal related to axonal spike activity or for a Ca2+ response related to contralateral inhibition. The tonotopic organisation of the afferents may facilitate frequency-specific adaptation in these auditory neurons through localised Ca2+ increases in their dendrites. By combining 10 and 40 kHz test pulses and adaptation series, we provide evidence for frequency-specific adaptation in TN-1 and ON-1. By reversible deactivating of the auditory afferents and removing contralateral inhibition, we show that in ON-1 spike activity and Ca2+ responses increased but frequency-specific adaptation was not evident.

Acetylcholine modulates the precision of prediction error in the auditory cortex

A fundamental property of sensory systems is their ability to detect novel stimuli in the ambient environment. The auditory brain contains neurons that decrease their response to repetitive sounds but increase their firing rate to novel or deviant stimuli; the difference between both responses is known as stimulus-specific adaptation or neuronal mismatch (nMM). Here, we tested the effect of microiontophoretic applications of ACh on the neuronal responses in the auditory cortex (AC) of anesthetized rats during an auditory oddball paradigm, including cascade controls. Results indicate that ACh modulates the nMM, affecting prediction error responses but not repetition suppression, and this effect is manifested predominantly in infragranular cortical layers. The differential effect of ACh on responses to standards, relative to deviants (in terms of averages and variances), was consistent with the representational sharpening that accompanies an increase in the precision of prediction errors. These findings suggest that ACh plays an important role in modulating prediction error signaling in the AC and gating the access of these signals to higher cognitive levels.

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.

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.

Markov chains as a proxy for the predictive memory representations underlying mismatch negativity

Events not conforming to a regularity inherent to a sequence of events elicit prediction error signals of the brain such as the Mismatch Negativity (MMN) and impair behavioral task performance. Events conforming to a regularity lead to attenuation of brain activity such as stimulus-specific adaptation (SSA) and behavioral benefits. Such findings are usually explained by theories stating that the information processing system predicts the forthcoming event of the sequence via detected sequential regularities. A mathematical model that is widely used to describe, to analyze and to generate event sequences are Markov chains: They contain a set of possible events and a set of probabilities for transitions between these events (transition matrix) that allow to predict the next event on the basis of the current event and the transition probabilities. The accuracy of such a prediction depends on the distribution of the transition probabilities. We argue that Markov chains also have useful applications when studying cognitive brain functions. The transition matrix can be regarded as a proxy for generative memory representations that the brain uses to predict the next event. We assume that detected regularities in a sequence of events correspond to (a subset of) the entries in the transition matrix. We apply this idea to the Mismatch Negativity (MMN) research and examine three types of MMN paradigms: classical oddball paradigms emphasizing sound probabilities, between-sound regularity paradigms manipulating transition probabilities between adjacent sounds, and action-sound coupling paradigms in which sounds are associated with actions and their intended effects. We show that the Markovian view on MMN yields theoretically relevant insights into the brain processes underlying MMN and stimulates experimental designs to study the brain's processing of event sequences.

The impact of spatial variance on precision estimates in an auditory oddball paradigm

Predictive processing theories suggest that a principal function of the brain is to reduce the surprise of incoming sensory information by creating accurate and precise models of the environment. These models are commonly explored by looking at the prediction errors elicited when experience departs from predictions. One such prediction error is the mismatch negativity (MMN). Using this component, it is possible to examine the effect of external noise on the precision of the developed model. Recent studies have shown that the brain may not update its model every time there is a change in the environment, rather it will only update it when doing so will increase precision and or accuracy of the model. The current study examined this process using oddball sound sequences with high and low spatial variability and examining how this affected the elicited MMN to a duration deviant sound. The results showed a strong null effect of spatial variance both at a local and sequence levels. These results indicate that variability in the sound sequence will not invariably affect model precision estimates and thus the amplitude of the MMN component.

Auditory cortex ensembles jointly encode sound and locomotion speed to support sound perception during movement

The ability to process and act upon incoming sounds during locomotion is critical for survival and adaptive behavior. Despite the established role that the auditory cortex (AC) plays in behavior- and context-dependent sound processing, previous studies have found that auditory cortical activity is on average suppressed during locomotion as compared to immobility. While suppression of auditory cortical responses to self-generated sounds results from corollary discharge, which weakens responses to predictable sounds, the functional role of weaker responses to unpredictable external sounds during locomotion remains unclear. In particular, whether suppression of external sound-evoked responses during locomotion reflects reduced involvement of the AC in sound processing or whether it results from masking by an alternative neural computation in this state remains unresolved. Here, we tested the hypothesis that rather than simple inhibition, reduced sound-evoked responses during locomotion reflect a tradeoff with the emergence of explicit and reliable coding of locomotion velocity. To test this hypothesis, we first used neural inactivation in behaving mice and found that the AC plays a critical role in sound-guided behavior during locomotion. To investigate the nature of this processing, we used two-photon calcium imaging of local excitatory auditory cortical neural populations in awake mice. We found that locomotion had diverse influences on activity of different neurons, with a net suppression of baseline-subtracted sound-evoked responses and neural stimulus detection, consistent with previous studies. Importantly, we found that the net inhibitory effect of locomotion on baseline-subtracted sound-evoked responses was strongly shaped by elevated ongoing activity that compressed the response dynamic range, and that rather than reflecting enhanced "noise," this ongoing activity reliably encoded the animal's locomotion speed. Decoding analyses revealed that locomotion speed and sound are robustly co-encoded by auditory cortical ensemble activity. Finally, we found consistent patterns of joint coding of sound and locomotion speed in electrophysiologically recorded activity in freely moving rats. Together, our data suggest that rather than being suppressed by locomotion, auditory cortical ensembles explicitly encode it alongside sound information to support sound perception during locomotion.

Modelling novelty detection in the thalamocortical loop

In complex natural environments, sensory systems are constantly exposed to a large stream of inputs. Novel or rare stimuli, which are often associated with behaviorally important events, are typically processed differently than the steady sensory background, which has less relevance. Neural signatures of such differential processing, commonly referred to as novelty detection, have been identified on the level of EEG recordings as mismatch negativity (MMN) and on the level of single neurons as stimulus-specific adaptation (SSA). Here, we propose a multi-scale recurrent network with synaptic depression to explain how novelty detection can arise in the whisker-related part of the somatosensory thalamocortical loop. The "minimalistic" architecture and dynamics of the model presume that neurons in cortical layer 6 adapt, via synaptic depression, specifically to a frequently presented stimulus, resulting in reduced population activity in the corresponding cortical column when compared with the population activity evoked by a rare stimulus. This difference in population activity is then projected from the cortex to the thalamus and amplified through the interaction between neurons of the primary and reticular nuclei of the thalamus, resulting in rhythmic oscillations. These differentially activated thalamic oscillations are forwarded to cortical layer 4 as a late secondary response that is specific to rare stimuli that violate a particular stimulus pattern. Model results show a strong analogy between this late single neuron activity and EEG-based mismatch negativity in terms of their common sensitivity to presentation context and timescales of response latency, as observed experimentally. Our results indicate that adaptation in L6 can establish the thalamocortical dynamics that produce signatures of SSA and MMN and suggest a mechanistic model of novelty detection that could generalize to other sensory modalities.

Stimulus-Specific Adaptation (SSA) in the Auditory System: Functional Relevance and Underlying Mechanisms

Rapid detection of novel stimuli that appear suddenly in the surrounding environment is crucial for an animal's survival. Stimulus-specific adaptation (SSA) may be an important mechanism underlying novelty detection. In this review, we discuss the latest advances in SSA research by addressing four main aspects: 1) the frequency dependence of SSA and the origin of SSA in the auditory cortex: 2) spatial SSA and its comparison with frequency SSA: 3) feature integration in SSA and its implications in novelty detection: 4) functional significance and the physiological mechanism of SSA. Although SSA has been extensively investigated, the cognitive insights from SSA studies are extremely limited. Future work should aim to bridge these gaps.

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.

Temporal profiles of neuronal responses to repeated tone stimuli in the mouse primary auditory cortex

How the auditory system processes temporal information of sound has been investigated extensively using repeated stimuli. Recent studies on how the response of neurons in the primary auditory cortex (A1) changes with the progression of stimulus repetition, have reported response temporal profiles of two categories: "adaptation", i.e., gradual decrease, and "facilitation", i.e., gradual increase. To explore the existence of profiles of other categories and to examine the tone-frequency-dependence of the profile category in single neurons, here we studied the response of mouse A1 neurons to four or five tone-trains; each train comprised 10 identical tone pips, with 0.5-s inter-tone-intervals, and the four or five trains differed only in tone frequency. The response to each tone in a train was evaluated using the peak of the ON response, and how the peak response changed with the tone number in the train, i.e., the response temporal profile, was examined. We confirmed the existence of profiles of both "adaptation" and "facilitation" categories; "adaptation" could be further subcategorized into "slow adaptation" and "fast adaptation" profiles, with the latter being encountered more frequently. Moreover, two new categories of non-monotonic profiles were identified: an "adaptation with recovery" profile and a "facilitation followed by adaptation" profile. Examination of single neurons with trains of different tone frequencies revealed that some A1 neurons exhibited profiles of the same category to tone trains of different tone frequencies, whereas others exhibited profiles of different categories, depending on the tone frequency. These results demonstrate the variety in the response temporal profiles of mouse A1 neurons, which may benefit the encoding of individual tones in a train.

Auditory memory of complex sounds in sparsely distributed, highly correlated neurons in the auditory cortex

Listening in complex sound environments requires rapid segregation of different sound sources e.g., speakers from each other, speakers from other sounds, or different instruments in an orchestra, and also adjust auditory processing on the prevailing sound conditions. Thus, fast encoding of inputs and identifying and adapting to reoccurring sounds are necessary for efficient and agile sound perception. This adaptation process represents an early phase of developing implicit learning of sound statistics and thus represents a form of auditory memory. The auditory cortex (ACtx) is known to play a key role in this encoding process but the underlying circuits and if hierarchical processing exists are not known. To identify ACtx regions and cells involved in this process, we simultaneously imaged population of neurons in different ACtx subfields using in vivo 2-photon imaging in awake mice. We used an experimental stimulus paradigm adapted from human studies that triggers rapid and robust implicit learning to passively present complex sounds and imaged A1 Layer 4 (L4), A1 L2/3, and A2 L2/3. In this paradigm, a frozen spectro-temporally complex 'Target' sound would be randomly re-occurring within a stream of random other complex sounds. We find distinct groups of cells that are specifically responsive to complex acoustic sequences across all subregions indicating that even the initial thalamocortical input layers (A1 L4) respond to complex sounds. Cells in all imaged regions showed decreased response amplitude for reoccurring Target sounds indicating that a memory signature is present even in the thalamocortical input layers. On the population level we find increased synchronized activity across cells to the Target sound and that this synchronized activity was more consistent across cells regardless of the duration of frozen token within Target sounds in A2, compared to A1. These findings suggest that ACtx and its input layers play a role in auditory memory for complex sounds and suggest a hierarchical structure of processes for auditory memory.

Temporal hierarchies in the predictive processing of melody - From pure tones to songs

Listening to musical melodies is a complex task that engages perceptual and memoryrelated processes. The processes underlying melody cognition happen simultaneously on different timescales, ranging from milliseconds to minutes. Although attempts have been made, research on melody perception is yet to produce a unified framework of how melody processing is achieved in the brain. This may in part be due to the difficulty of integrating concepts such as perception, attention and memory, which pertain to different temporal scales. Recent theories on brain processing, which hold prediction as a fundamental principle, offer potential solutions to this problem and may provide a unifying framework for explaining the neural processes that enable melody perception on multiple temporal levels. In this article, we review empirical evidence for predictive coding on the levels of pitch formation, basic pitch-related auditory patterns,more complex regularity processing extracted from basic patterns and long-term expectations related to musical syntax. We also identify areas that would benefit from further inquiry and suggest future directions in research on musical melody perception.

Rule-based and stimulus-based cues bias auditory decisions via different computational and physiological mechanisms

Expectations, such as those arising from either learned rules or recent stimulus regularities, can bias subsequent auditory perception in diverse ways. However, it is not well understood if and how these diverse effects depend on the source of the expectations. Further, it is unknown whether different sources of bias use the same or different computational and physiological mechanisms. We examined how rule-based and stimulus-based expectations influenced behavior and pupil-linked arousal, a marker of certain forms of expectation-based processing, of human subjects performing an auditory frequency-discrimination task. Rule-based cues consistently biased choices and response times (RTs) toward the more-probable stimulus. In contrast, stimulus-based cues had a complex combination of effects, including choice and RT biases toward and away from the frequency of recently presented stimuli. These different behavioral patterns also had: 1) distinct computational signatures, including different modulations of key components of a novel form of a drift-diffusion decision model and 2) distinct physiological signatures, including substantial bias-dependent modulations of pupil size in response to rule-based but not stimulus-based cues. These results imply that different sources of expectations can modulate auditory processing via distinct mechanisms: one that uses arousal-linked, rule-based information and another that uses arousal-independent, stimulus-based information to bias the speed and accuracy of auditory perceptual decisions.

Prior information about upcoming stimuli can bias our perception of those stimuli. Whether different sources of prior information bias perception in similar or distinct ways is not well understood. We compared the influence of two kinds of prior information on tone-frequency discrimination: rule-based cues, in the form of explicit information about the most-likely identity of the upcoming tone; and stimulus-based cues, in the form of sequences of tones presented before the to-be-discriminated tone. Although both types of prior information biased auditory decision-making, they demonstrated distinct behavioral, computational, and physiological signatures. Our results suggest that the brain processes prior information in a form-specific manner rather than utilizing a general-purpose prior. Such form-specific processing has implications for understanding decision biases real-world contexts, in which prior information comes from many different sources and modalities.

Object specific adaptation in the auditory cortex of bats

To identify behaviourally relevant sounds is an important function of the auditory system. Echolocating bats have to negotiate a wealth of sounds in the context of navigation and foraging. They must be able to detect relatively rare but behaviourally important echoes and segregate them from a large number of unimportant background echoes. For this, the bat auditory system might rely on neural deviance detection, a process influencing the excitability of a neuron depending on the frequency of occurrence of a stimulus. To investigate neural deviance detection in the auditory cortex (AC) of anaesthetised bats (Phyllostomus discolor), we designed sequences of repetitive naturalistic virtual echoes differing in spectro-temporal envelope, resembling those bats might perceive in their natural environment. In these sequences, one echo (standard) was repeated ten times and another echo (deviant) was presented at the end. Temporal intervals between echoes within the sequences varied. Our results show, that neurons in the AC of the bat P. discolor are sensitive to novel virtual echoes presented at the end of these repetitive sequences: In 49 % (62/126) of cortical neurons, extracellularly recorded responses adapted to the standard echo, but showed a strong response to the finally presented deviant echo. This effect depended strongly on the temporal intervals between echoes, with stronger adaptation at shorter intervals. This type of response behavior might represent a form of neuronal deviance detection in the AC that could help the bats to detect echoes of novel and potentially important objects within a stream of homogeneous background echoes.

Enhanced stability of complex sound representations relative to simple sounds in the auditory cortex

Typical everyday sounds, such as those of speech or running water, are spectrotemporally complex. The ability to recognize complex sounds (CxS) and their associated meaning is presumed to rely on their stable neural representations across time. The auditory cortex is critical for processing of CxS, yet little is known of the degree of stability of auditory cortical representations of CxS across days. Previous studies have shown that the auditory cortex represents CxS identity with a substantial degree of invariance to basic sound attributes such as frequency. We therefore hypothesized that auditory cortical representations of CxS are more stable across days than those of sounds that lack spectrotemporal structure such as pure tones (PTs). To test this hypothesis, we recorded responses of identified L2/3 auditory cortical excitatory neurons to both PTs and CxS across days using two-photon calcium imaging in awake mice. Auditory cortical neurons showed significant daily changes of responses to both types of sounds, yet responses to CxS exhibited significantly lower rates of daily change than those of PTs. Furthermore, daily changes in response profiles to PTs tended to be more stimulus-specific, reflecting changes in sound selectivity, as compared to changes of CxS responses. Lastly, the enhanced stability of responses to CxS was evident across longer time intervals as well. Together, these results suggest that spectrotemporally CxS are more stably represented in the auditory cortex across time than PTs. These findings support a role of the auditory cortex in representing CxS identity across time.Significance statementThe ability to recognize everyday complex sounds such as those of speech or running water is presumed to rely on their stable neural representations. Yet, little is known of the degree of stability of single-neuron sound responses across days. As the auditory cortex is critical for complex sound perception, we hypothesized that the auditory cortical representations of complex sounds are relatively stable across days. To test this, we recorded sound responses of identified auditory cortical neurons across days in awake mice. We found that auditory cortical responses to complex sounds are significantly more stable across days as compared to those of simple pure tones. These findings support a role of the auditory cortex in representing complex sound identity across time.

The Ecological View of Selective Attention

Accumulating evidence is supporting the hypothesis that our selective attention is a manifestation of mechanisms that evolved early in evolution and are shared by many organisms from different taxa. This surge of new data calls for the re-examination of our notions about attention, which have been dominated mostly by human psychology. Here, we present an hypothesis that challenges, based on evolutionary grounds, a common view of attention as a means to manage limited brain resources. We begin by arguing that evolutionary considerations do not favor the basic proposition of the limited brain resources view of attention, namely, that the capacity of the sensory organs to provide information exceeds the capacity of the brain to process this information. Moreover, physiological studies in animals and humans show that mechanisms of selective attention are highly demanding of brain resources, making it paradoxical to see attention as a means to release brain resources. Next, we build on the above arguments to address the question why attention evolved in evolution. We hypothesize that, to a certain extent, limiting sensory processing is adaptive irrespective of brain capacity. We call this hypothesis the ecological view of attention (EVA) because it is centered on interactions of an animal with its environment rather than on internal brain resources. In its essence is the notion that inherently noisy and degraded sensory inputs serve the animal's adaptive, dynamic interactions with its environment. Attention primarily functions to resolve behavioral conflicts and false distractions. Hence, we evolved to focus on a particular target at the expense of others, not because of internal limitations, but to ensure that behavior is properly oriented and committed to its goals. Here, we expand on this notion and review evidence supporting it. We show how common results in human psychophysics and physiology can be reconciled with an EVA and discuss possible implications of the notion for interpreting current results and guiding future research.

Neurophysiology in psychosis: The quest for disease biomarkers

Psychotic disorders affect 3% of the population at some stage in life, are a leading cause of disability, and impose a great economic burden on society. Major breakthroughs in the genetics of psychosis have not yet been matched by an understanding of its neurobiology. Biomarkers of perception and cognition obtained through non-invasive neurophysiological tools, especially EEG, offer a unique opportunity to gain mechanistic insights. Techniques for measuring neurophysiological markers are inexpensive and ubiquitous, thus having the potential as an accessible tool for patient stratification towards early treatments leading to better outcomes. In this paper, we review the literature on neurophysiological markers for psychosis and their relevant disease mechanisms, mainly covering event-related potentials including P50/N100 sensory gating, mismatch negativity, and the N100 and P300 waveforms. While several neurophysiological deficits are well established in patients with psychosis, more research is needed to study neurophysiological markers in their unaffected relatives and individuals at clinical high risk. We need to harness EEG to investigate markers of disease risk as key steps to elucidate the aetiology of psychosis and facilitate earlier detection and treatment.

Hearing in Complex Environments: Auditory Gain Control, Attention, and Hearing Loss

Listening in noisy or complex sound environments is difficult for individuals with normal hearing and can be a debilitating impairment for those with hearing loss. Extracting meaningful information from a complex acoustic environment requires the ability to accurately encode specific sound features under highly variable listening conditions and segregate distinct sound streams from multiple overlapping sources. The auditory system employs a variety of mechanisms to achieve this auditory scene analysis. First, neurons across levels of the auditory system exhibit compensatory adaptations to their gain and dynamic range in response to prevailing sound stimulus statistics in the environment. These adaptations allow for robust representations of sound features that are to a large degree invariant to the level of background noise. Second, listeners can selectively attend to a desired sound target in an environment with multiple sound sources. This selective auditory attention is another form of sensory gain control, enhancing the representation of an attended sound source while suppressing responses to unattended sounds. This review will examine both “bottom-up” gain alterations in response to changes in environmental sound statistics as well as “top-down” mechanisms that allow for selective extraction of specific sound features in a complex auditory scene. Finally, we will discuss how hearing loss interacts with these gain control mechanisms, and the adaptive and/or maladaptive perceptual consequences of this plasticity.

Neural Substrates and Models of Omission Responses and Predictive Processes

Predictive coding theories argue that deviance detection phenomena, such as mismatch responses and omission responses, are generated by predictive processes with possibly overlapping neural substrates. Molecular imaging and electrophysiology studies of mismatch responses and corollary discharge in the rodent model allowed the development of mechanistic and computational models of these phenomena. These models enable translation between human and non-human animal research and help to uncover fundamental features of change-processing microcircuitry in the neocortex. This microcircuitry is characterized by stimulus-specific adaptation and feedforward inhibition of stimulus-selective populations of pyramidal neurons and interneurons, with specific contributions from different interneuron types. The overlap of the substrates of different types of responses to deviant stimuli remains to be understood. Omission responses, which are observed both in corollary discharge and mismatch response protocols in humans, are underutilized in animal research and may be pivotal in uncovering the substrates of predictive processes. Omission studies comprise a range of methods centered on the withholding of an expected stimulus. This review aims to provide an overview of omission protocols and showcase their potential to integrate and complement the different models and procedures employed to study prediction and deviance detection.This approach may reveal the biological foundations of core concepts of predictive coding, and allow an empirical test of the framework's promise to unify theoretical models of attention and perception.

Inhibition in the auditory cortex

The auditory system provides us with extremely rich and precise information about the outside world. Once a sound reaches our ears, the acoustic information it carries travels from the cochlea all the way to the auditory cortex, where its complexity and nuances are integrated. In the auditory cortex, functional circuits are formed by subpopulations of intermingled excitatory and inhibitory cells. In this review, we discuss recent evidence of the specific contributions of inhibitory neurons in sound processing and integration. We first examine intrinsic properties of three main classes of inhibitory interneurons in the auditory cortex. Then, we describe how inhibition shapes the responsiveness of the auditory cortex to sound. Finally, we discuss how inhibitory interneurons contribute to the sensation and perception of sounds. Altogether, this review points out the crucial role of cortical inhibitory interneurons in integrating information about the context, history, or meaning of a sound. It also highlights open questions to be addressed for increasing our understanding of the staggering complexity leading to the subtlest auditory perception.

Sound level context modulates neural activity in the human brainstem

Optimal perception requires adaptation to sounds in the environment. Adaptation involves representing the acoustic stimulation history in neural response patterns, for example, by altering response magnitude or latency as sound-level context changes. Neurons in the auditory brainstem of rodents are sensitive to acoustic stimulation history and sound-level context (often referred to as sensitivity to stimulus statistics), but the degree to which the human brainstem exhibits such neural adaptation is unclear. In six electroencephalography experiments with over 125 participants, we demonstrate that the response latency of the human brainstem is sensitive to the history of acoustic stimulation over a few tens of milliseconds. We further show that human brainstem responses adapt to sound-level context in, at least, the last 44 ms, but that neural sensitivity to sound-level context decreases when the time window over which acoustic stimuli need to be integrated becomes wider. Our study thus provides evidence of adaptation to sound-level context in the human brainstem and of the timescale over which sound-level information affects neural responses to sound. The research delivers an important link to studies on neural adaptation in non-human animals.

Adaptive auditory brightness perception

Perception adapts to the properties of prior stimulation, as illustrated by phenomena such as visual color constancy or speech context effects. In the auditory domain, only little is known about adaptive processes when it comes to the attribute of auditory brightness. Here, we report an experiment that tests whether listeners adapt to spectral colorations imposed on naturalistic music and speech excerpts. Our results indicate consistent contrastive adaptation of auditory brightness judgments on a trial-by-trial basis. The pattern of results suggests that these effects tend to grow with an increase in the duration of the adaptor context but level off after around 8 trials of 2 s duration. A simple model of the response criterion yields a correlation of r = .97 with the measured data and corroborates the notion that brightness perception adapts on timescales that fall in the range of auditory short-term memory. Effects turn out to be similar for spectral filtering based on linear spectral filter slopes and filtering based on a measured transfer function from a commercially available hearing device. Overall, our findings demonstrate the adaptivity of auditory brightness perception under realistic acoustical conditions.

Encoding of acquired sound-sequence salience by auditory cortical offset responses

Behaviorally relevant sounds are often composed of distinct acoustic units organized into specific temporal sequences. The meaning of such sound sequences can therefore be fully recognized only when they have terminated. However, the neural mechanisms underlying the perception of sound sequences remain unclear. Here, we use two-photon calcium imaging in the auditory cortex of behaving mice to test the hypothesis that neural responses to termination of sound sequences ("Off-responses") encode their acoustic history and behavioral salience. We find that auditory cortical Off-responses encode preceding sound sequences and that learning to associate a sound sequence with a reward induces enhancement of Off-responses relative to responses during the sound sequence ("On-responses"). Furthermore, learning enhances network-level discriminability of sound sequences by Off-responses. Last, learning-induced plasticity of Off-responses but not On-responses lasts to the next day. These findings identify auditory cortical Off-responses as a key neural signature of acquired sound-sequence salience.

The generation of cortical novelty responses through inhibitory plasticity

Animals depend on fast and reliable detection of novel stimuli in their environment. Neurons in multiple sensory areas respond more strongly to novel in comparison to familiar stimuli. Yet, it remains unclear which circuit, cellular, and synaptic mechanisms underlie those responses. Here, we show that spike-timing-dependent plasticity of inhibitory-to-excitatory synapses generates novelty responses in a recurrent spiking network model. Inhibitory plasticity increases the inhibition onto excitatory neurons tuned to familiar stimuli, while inhibition for novel stimuli remains low, leading to a network novelty response. The generation of novelty responses does not depend on the periodicity but rather on the distribution of presented stimuli. By including tuning of inhibitory neurons, the network further captures stimulus-specific adaptation. Finally, we suggest that disinhibition can control the amplification of novelty responses. Therefore, inhibitory plasticity provides a flexible, biologically plausible mechanism to detect the novelty of bottom-up stimuli, enabling us to make experimentally testable predictions.

Visuo-Acoustic Stimulation's Role in Synaptic Plasticity: A Review of the Literature

Brain plasticity is the capacity of cerebral neurons to change, structurally and functionally, in response to experiences. This is an essential property underlying the maturation of sensory functions, learning and memory processes, and brain repair in response to the occurrence of diseases and trauma. In this field, the visual system emerges as a paradigmatic research model, both for basic research studies and for translational investigations. The auditory system remains capable of reorganizing itself in response to different auditory stimulations or sensory organ modification. Acoustic biofeedback training can be an effective way to train patients with the central scotoma, who have poor fixation stability and poor visual acuity, in order to bring fixation on an eccentrical and healthy area of the retina: a pseudofovea. This review article is focused on the cellular and molecular mechanisms underlying retinal sensitivity changes and visual and auditory system plasticity.

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.

Shorter Contextual Timescale Rather Than Memory Deficit in Aging

Many aspects of cognitive ability and brain function that change as we age look like deficits on account of measurable differences in comparison to younger adult groups. One such difference occurs in auditory sensory responses that index perceptual learning. Meta-analytic findings show reliable age-related differences in auditory responses to repetitive patterns of sound and to rare violations of those patterns, variously attributed to deficits in auditory sensory memory and inhibition. Here, we determine whether proposed deficits would render older adults less prone to primacy effects, robustly observed in young adults, which present as a tendency for first learning to have a disproportionate influence over later perceptual inference. The results confirm this reduced sensitivity to primacy effects but do not support impairment in auditory sensory memory as the origin of this difference. Instead, the aging brain produces data consistent with shorter timescales of contextual reference. In conclusion, age-related differences observed previously for perceptual inference appear highly context-specific necessitating reconsideration of whether and to what function the notion of deficit should be attributed, and even whether the notion of deficit is appropriate at all.

The posterior auditory field is the chief generator of prediction error signals in the auditory cortex

The auditory cortex (AC) encompasses distinct fields subserving partly different aspects of sound processing. One essential function of the AC is the detection of unpredicted sounds, as revealed by differential neural activity to predictable and unpredictable sounds. According to the predictive coding framework, this effect can be explained by repetition suppression and/or prediction error signaling. The present study investigates functional specialization of the rat AC fields in repetition suppression and prediction error by combining a tone frequency oddball paradigm (involving high-probable standard and low-probable deviant tones) with two different control sequences (many-standards and cascade). Tones in the control sequences were comparable to deviant events with respect to neural adaptation but were not violating a regularity. Therefore, a difference in the neural activity between deviant and control tones indicates a prediction error effect, whereas a difference between control and standard tones indicates a repetition suppression effect. Single-unit recordings revealed by far the largest prediction error effects for the posterior auditory field, while the primary auditory cortex, the anterior auditory field, the ventral auditory field, and the suprarhinal auditory field were dominated by repetition suppression effects. Statistically significant repetition suppression effects occurred in all AC fields, whereas prediction error effects were less robust in the primary auditory cortex and the anterior auditory field. Results indicate that the non-lemniscal, posterior auditory field is more engaged in context-dependent processing underlying deviance-detection than the other AC fields, which are more sensitive to stimulus-dependent effects underlying differential degrees of neural adaptation.

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.

Emergence of abstract sound representations in the ascending auditory system

Auditory processing begins by decomposing sounds into their frequency components, raising the question of where the representation of sounds as wholes emerges in the auditory system. To address this question, we used stimulus-specific adaptation (SSA), the reduction in the responses of a neuron to a common sound (standard) which does not generalize to another, rare sound (deviant). SSA to tone frequency has been demonstrated in multiple stations of the auditory pathway, including the inferior colliculus (IC), medial geniculate body (MGB) and auditory cortex. We designed wideband stimuli (tone clouds) that have identical frequency components but are nevertheless distinct. Tone clouds evoked early and substantial SSA in primary auditory cortex (A1) but only late and minor SSA in IC and MGB. These results imply that while in IC and MGB sounds are largely represented in terms of their frequency components, in A1 they are represented as abstract entities.

An fMRI Study Using a Combined Task of Interval Discrimination and Oddball Could Reveal Common Brain Circuits of Cognitive Change

Recent functional neuroimaging studies suggest that the brain networks responsible for time processing are involved during other cognitive processes, leading to a hypothesis that time-related processing is needed to perform a range of tasks across various cognitive functions. To examine this hypothesis, we analyze whether, in healthy subjects, the brain structures activated or deactivated during performance of timing and oddball-detection type tasks coincide. To this end, we conducted two independent signed differential mapping (SDM) meta-analyses of functional magnetic resonance imaging (fMRI) studies assessing the cerebral generators of the responses elicited by tasks based on timing and oddball-detection paradigms. Finally, we undertook a multimodal meta-analysis to detect brain regions common to the findings of the two previous meta-analyses. We found that healthy subjects showed significant activation in cortical areas related to timing and salience networks. The patterns of activation and deactivation corresponding to each task type partially coincided. We hypothesize that there exists a time and change-detection network that serves as a common underlying resource used in a broad range of cognitive processes.

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.

Spatial Separation between Two Sounds of an Oddball Paradigm Affects Responses of Neurons in the Rat's Inferior Colliculus to the Sounds

The ability to sense occasionally occurring sounds in an environment is critical for animals. To understand this ability, we studied responses to acoustic oddball paradigms in the rat's midbrain auditory neurons. An oddball paradigm is a random sequence of stimuli created using two tone bursts, with one presented at a high probability (standard stimulus) and the other at a low probability (oddball stimulus). The sounds were either colocalized at the ear contralateral to a neuron under investigation (c90° azimuth) or separated with one at c90° while the other at another azimuth. We found that most neurons generated stronger responses to a sound at c90° when it was presented as an oddball than as a standard stimulus. Relocating one sound from c90° to another azimuth changed both responses to the relocated sound and the sound that remained at c90°. Most notably, the response to an oddball stimulus at c90° was increased when a standard stimulus was relocated from c90° to a location that was in front of the animal or on the ipsilateral side of recording. The increase was particularly large in neurons that displayed transient firing under contralateral stimulation but no firing under ipsilateral stimulation. These neurons likely play a particularly important role in using spatial cues to detect occasionally occurring sounds. Results suggest that effects of spatial separation between two sounds of an oddball paradigm on responses to the sounds were dependent on changes in the level of adaptation and binaural inhibition.

Pitch, Timbre and Intensity Interdependently Modulate Neural Responses to Salient Sounds

As we listen to everyday sounds, auditory perception is heavily shaped by interactions between acoustic attributes such as pitch, timbre and intensity; though it is not clear how such interactions affect judgments of acoustic salience in dynamic soundscapes. Salience perception is believed to rely on an internal brain model that tracks the evolution of acoustic characteristics of a scene and flags events that do not fit this model as salient. The current study explores how the interdependency between attributes of dynamic scenes affects the neural representation of this internal model and shapes encoding of salient events. Specifically, the study examines how deviations along combinations of acoustic attributes interact to modulate brain responses, and subsequently guide perception of certain sound events as salient given their context. Human volunteers have their attention focused on a visual task and ignore acoustic melodies playing in the background while their brain activity using electroencephalography is recorded. Ambient sounds consist of musical melodies with probabilistically-varying acoustic attributes. Salient notes embedded in these scenes deviate from the melody's statistical distribution along pitch, timbre and/or intensity. Recordings of brain responses to salient notes reveal that neural power in response to the melodic rhythm as well as cross-trial phase alignment in the theta band are modulated by degree of salience of the notes, estimated across all acoustic attributes given their probabilistic context. These neural nonlinear effects across attributes strongly parallel behavioral nonlinear interactions observed in perceptual judgments of auditory salience using similar dynamic melodies; suggesting a neural underpinning of nonlinear interactions that underlie salience perception.

Vagus nerve stimulation (VNS)-induced layer-specific modulation of evoked responses in the sensory cortex of rats

Neuromodulation achieved by vagus nerve stimulation (VNS) induces various neuropsychiatric effects whose underlying mechanisms of action remain poorly understood. Innervation of neuromodulators and a microcircuit structure in the cerebral cortex informed the hypothesis that VNS exerts layer-specific modulation in the sensory cortex and alters the balance between feedforward and feedback pathways. To test this hypothesis, we characterized laminar profiles of auditory-evoked potentials (AEPs) in the primary auditory cortex (A1) of anesthetized rats with an array of microelectrodes and investigated the effects of VNS on AEPs and stimulus specific adaptation (SSA). VNS predominantly increased the amplitudes of AEPs in superficial layers, but this effect diminished with depth. In addition, VNS exerted a stronger modulation of the neural responses to repeated stimuli than to deviant stimuli, resulting in decreased SSA across all layers of the A1. These results may provide new insights that the VNS-induced neuropsychiatric effects may be attributable to a sensory gain mechanism: VNS strengthens the ascending input in the sensory cortex and creates an imbalance in the strength of activities between superficial and deep cortical layers, where the feedfoward and feedback pathways predominantly originate, respectively.

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.

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.

Making Sense of Mismatch Negativity

Evoked potentials provide valuable insight into brain processes that are integral to our ability to interact effectively and efficiently in the world. The mismatch negativity (MMN) component of the evoked potential has proven highly informative on the ways in which sensitivity to regularity contributes to perception and cognition. This review offers a compendium of research on MMN with a view to scaffolding an appreciation for its use as a tool to explore the way regularities contribute to predictions about the sensory environment over many timescales. In compiling this work, interest in MMN as an index of sensory encoding and memory are addressed, as well as attention. Perspectives on the possible underlying computational processes are reviewed as well as recent observations that invite consideration of how MMN relates to how we learn, what we learn, and why.

Temporary Visual Deprivation Causes Decorrelation of Spatiotemporal Population Responses in Adult Mouse Auditory Cortex

Although within-modality sensory plasticity is limited to early developmental periods, cross-modal plasticity can occur even in adults. In vivo electrophysiological studies have shown that transient visual deprivation (dark exposure, DE) in adult mice improves the frequency selectivity and discrimination of neurons in thalamorecipient layer 4 (L4) of primary auditory cortex (A1). Since sound information is processed hierarchically in A1 by populations of neurons, we investigated whether DE alters network activity in A1 L4 and layer 2/3 (L2/3). We examined neuronal populations in both L4 and L2/3 using in vivo two-photon calcium (Ca²⁺) imaging of transgenic mice expressing GCaMP6s. We find that one week of DE in adult mice increased the sound evoked responses and frequency selectivity of both L4 and L2/3 neurons. Moreover, after DE the frequency representation changed with L4 and L2/3 showing a reduced representation of cells with best frequencies (BFs) between 8 and 16 kHz and an increased representation of cells with BFs above 32 kHz. Cells in L4 and L2/3 showed decreased pairwise signal correlations (SCs) consistent with sharper tuning curves. The decreases in SCs were larger in L4 than in L2/3. The decreased pairwise correlations indicate a sparsification of A1 responses to tonal stimuli. Thus, cross-modal experience in adults can both alter the sound-evoked responses of A1 neurons and change activity correlations within A1 potentially enhancing the encoding of auditory stimuli.

Spectral tuning of adaptation supports coding of sensory context in auditory cortex

Perception of vocalizations and other behaviorally relevant sounds requires integrating acoustic information over hundreds of milliseconds. Sound-evoked activity in auditory cortex typically has much shorter latency, but the acoustic context, i.e., sound history, can modulate sound evoked activity over longer periods. Contextual effects are attributed to modulatory phenomena, such as stimulus-specific adaption and contrast gain control. However, an encoding model that links context to natural sound processing has yet to be established. We tested whether a model in which spectrally tuned inputs undergo adaptation mimicking short-term synaptic plasticity (STP) can account for contextual effects during natural sound processing. Single-unit activity was recorded from primary auditory cortex of awake ferrets during presentation of noise with natural temporal dynamics and fully natural sounds. Encoding properties were characterized by a standard linear-nonlinear spectro-temporal receptive field (LN) model and variants that incorporated STP-like adaptation. In the adapting models, STP was applied either globally across all input spectral channels or locally to subsets of channels. For most neurons, models incorporating local STP predicted neural activity as well or better than LN and global STP models. The strength of nonlinear adaptation varied across neurons. Within neurons, adaptation was generally stronger for spectral channels with excitatory than inhibitory gain. Neurons showing improved STP model performance also tended to undergo stimulus-specific adaptation, suggesting a common mechanism for these phenomena. When STP models were compared between passive and active behavior conditions, response gain often changed, but average STP parameters were stable. Thus, spectrally and temporally heterogeneous adaptation, subserved by a mechanism with STP-like dynamics, may support representation of the complex spectro-temporal patterns that comprise natural sounds across wide-ranging sensory contexts.