Sparse representation of neurons for encoding complex sounds in the auditory cortex

Listening in complex sound environments requires rapid segregation of different sound sources, e.g., having a conversation with multiple speakers or other environmental sounds. Efficient processing requires fast encoding of inputs to adapt to target sounds and identify relevant information from past experiences. This adaptation process represents an early phase of implicit learning of the sound statistics to form auditory memory. The auditory cortex (ACtx) plays a crucial role in this implicit learning process, but the underlying circuits are unknown. In awake mice, we recorded neuronal responses in different ACtx subfields using in vivo 2-photon imaging of excitatory and inhibitory (parvalbumin; PV) neurons. We used a paradigm adapted from human studies that induced rapid implicit learning from passively presented 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 randomly re-occurred within a stream of other random complex sounds. All ACtx subregions contained distinct groups of cells specifically responsive to complex acoustic sequences, indicating that even thalamocortical input layers (A1 L4) respond to complex sounds. Subgroups of excitatory and inhibitory cells in all subfields showed decreased responses for re-occurring Target sounds, indicating that ACtx is highly involved in the early implicit learning phase. At the population level, activity was more decorrelated to Target sounds independent of the duration of frozen token, subregions, and cell type. These findings suggest that ACtx and its input layers contribute to the early phase of auditory memory for complex sounds, suggesting a parallel strategy across ACtx areas and between excitatory and inhibitory neurons.

A Dual Role for the Dorsolateral Prefrontal Cortex (DLPFC) in Auditory Deviance Detection

BACKGROUND

In the oddball paradigm, the dorsolateral prefrontal cortex (DLPFC) is often associated with active cognitive responses, such as maintaining information in working memory or adapting response strategies. While some evidence points to the DLPFC's role in passive auditory deviance perception, a detailed understanding of the spatiotemporal neurodynamics involved remains unclear.

METHODS

In this study, event-related optical signals (EROS) and event-related potentials (ERPs) were simultaneously recorded for the first time over the prefrontal cortex using a 64-channel electroencephalography (EEG) system, during passive auditory deviance perception in 12 right-handed young adults (7 women and 5 men). In this oddball paradigm, deviant stimuli (a 1500 Hz pure tone) elicited a negative shift in the N1 ERP component, related to mismatch negativity (MMN), and a significant positive deflection associated with the P300, compared to standard stimuli (a 1000 Hz tone).

RESULTS

We hypothesize that the DLPFC not only participates in active tasks but also plays a critical role in processing deviant stimuli in passive conditions, shifting from pre-attentive to attentive processing. We detected enhanced neural activity in the left middle frontal gyrus (MFG), at the same timing of the MMN component, followed by later activation at the timing of the P3a ERP component in the right MFG.

CONCLUSIONS

Understanding these dynamics will provide deeper insights into the DLPFC's role in evaluating the novelty or unexpectedness of the deviant stimulus, updating its cognitive value, and adjusting future predictions accordingly. However, the small number of subjects could limit the generalizability of the observations, in particular with respect to the effect of handedness, and additional studies with larger and more diverse samples are necessary to validate our conclusions.

Decoding contextual influences on auditory perception from primary auditory cortex

Perception can be highly dependent on stimulus context, but whether and how sensory areas encode the context remains uncertain. We used an ambiguous auditory stimulus - a tritone pair - to investigate the neural activity associated with a preceding contextual stimulus that strongly influenced the tritone pair's perception: either as an ascending or a descending step in pitch. We recorded single-unit responses from a population of auditory cortical cells in awake ferrets listening to the tritone pairs preceded by the contextual stimulus. We find that the responses adapt locally to the contextual stimulus, consistent with human MEG recordings from the auditory cortex under the same conditions. Decoding the population responses demonstrates that cells responding to pitch-class-changes are able to predict well the context-sensitive percept of the tritone pairs. Conversely, decoding the individual pitch-class representations and taking their distance in the circular Shepard tone space predicts the opposite of the percept. The various percepts can be readily captured and explained by a neural model of cortical activity based on populations of adapting, pitch-class and pitch-class-direction cells, aligned with the neurophysiological responses. Together, these decoding and model results suggest that contextual influences on perception may well be already encoded at the level of the primary sensory cortices, reflecting basic neural response properties commonly found in these areas.

Auditory discrimination learning differentially modulates neural representation in auditory cortex subregions and inter-areal connectivity

Changes in sound-evoked responses in the auditory cortex (ACtx) occur during learning, but how learning alters neural responses in different ACtx subregions and changes their interactions is unclear. To address these questions, we developed an automated training and widefield imaging system to longitudinally track the neural activity of all mouse ACtx subregions during a tone discrimination task. We find that responses in primary ACtx are highly informative of learned stimuli and behavioral outcomes throughout training. In contrast, representations of behavioral outcomes in the dorsal posterior auditory field, learned stimuli in the dorsal anterior auditory field, and inter-regional correlations between primary and higher-order areas are enhanced with training. Moreover, ACtx response changes vary between stimuli, and such differences display lag synchronization with the learning rate. These results indicate that learning alters functional connections between ACtx subregions, inducing region-specific modulations by propagating behavioral information from primary to higher-order areas.

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.

From psychophysiology to brain imaging: forty-five years MMN history of investigating acoustic change sensitivity

Forty-five years have passed since the first publication of the mismatch negativity (MMN) event-related brain potential (ERP) component. The first 10 years of research hardly gained any particular attention of the scientific community interested in acoustic perception. Debates on the nature of sensation versus perception were going on, and the technical possibilities to record ERPs, called in general evoked potentials, were very limited. Subtle changes in pure tone frequency or intensity giving rise to the MMN component were first investigated in humans. The background of the theoretical model developed by Risto Näätänen was the orientation reaction model of E.N. Sokolov published in 1963 so that the MMN was seen first as an electrophysiological correlate of auditory change detection. This fundamental ability of the auditory system seen as crucial for survival led to the development of the first animal model of the MMN (Csépe et al. in Clin Neurophysiol 66: 571-578, 1987). Indeed, it was confirmed that the MMN was the brain correlate of subtle changes detected that might alert to potential threats in the environment and direct the behavioral orientation. The investigations performed after 2000 introduced complex models and more sophisticated methods, both in animal and human studies, so that the MMN method was on the way to become a tool on the first place and not the main goal of research. This approach was further strengthened by the increasing number of studies on different clinical populations aiming at future applications. The aim of our review is to describe and redefine what the MMN may reflect in auditory perception and to show why and how this brain correlate of changes in the auditory scene can be used as a valuable tool in cognitive neuroscience research. We refer to publications selected to underly the argument the MMN cannot be classified anymore as a sign of simple change detection and not all the indicators used to confirm how genuine the MMN elicited by variations of tones are valid for those to  speech contrasts. We provide a fresh view on the broadly used MMN models, provided by some influential publications as well as on the unwritten history of MMN research aiming to give revised picture on what the MMN may truly reflect. We show how the focus and terminology of the MMN research have changed and what kind of misunderstandings and seemingly contradictive results prevent the MMN community to accept a generally usable cognitive model.

Probing Beat Perception with Event-Related Potentials (ERPs) in Human Adults, Newborns, and Nonhuman Primates

The aim of this chapter is to give an overview of how the perception of rhythmic temporal regularity such as a regular beat in music can be studied in human adults, human newborns, and nonhuman primates using event-related brain potentials (ERPs). First, we discuss different aspects of temporal structure in general, and musical rhythm in particular, and we discuss the possible mechanisms underlying the perception of regularity (e.g., a beat) in rhythm. Additionally, we highlight the importance of dissociating beat perception from the perception of other types of structure in rhythm, such as predictable sequences of temporal intervals, ordinal structure, and rhythmic grouping. In the second section of the chapter, we start with a discussion of auditory ERPs elicited by infrequent and frequent sounds: ERP responses to regularity violations, such as mismatch negativity (MMN), N2b, and P3, as well as early sensory responses to sounds, such as P1 and N1, have been shown to be instrumental in probing beat perception. Subsequently, we discuss how beat perception can be probed by comparing ERP responses to sounds in regular and irregular sequences, and by comparing ERP responses to sounds in different metrical positions in a rhythm, such as on and off the beat or on strong and weak beats. Finally, we will discuss previous research that has used the aforementioned ERPs and paradigms to study beat perception in human adults, human newborns, and nonhuman primates. In doing so, we consider the possible pitfalls and prospects of the technique, as well as future perspectives.

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.

Spectral and phase-coherence correlates of impaired auditory mismatch negativity (MMN) in schizophrenia: A MEG study

BACKGROUND

Reduced auditory mismatch negativity (MMN) is robustly impaired in schizophrenia. However, mechanisms underlying dysfunctional MMN generation remain incompletely understood. This study aimed to examine the role of evoked spectral power and phase-coherence towards deviance detection and its impairments in schizophrenia.

METHODS

Magnetoencephalography data was collected in 16 male schizophrenia patients and 16 male control participants during an auditory MMN paradigm. Analyses of event-related fields (ERF), spectral power and inter-trial phase-coherence (ITPC) focused on Heschl's gyrus, superior temporal gyrus, inferior/medial frontal gyrus and thalamus.

RESULTS

MMNm ERF amplitudes were reduced in patients in temporal, frontal and subcortical regions, accompanied by decreased theta-band responses, as well as by a diminished gamma-band response in auditory cortex. At theta/alpha frequencies, ITPC to deviant tones was reduced in patients in frontal cortex and thalamus. Patients were also characterized by aberrant responses to standard tones as indexed by reduced theta-/alpha-band power and ITPC in temporal and frontal regions. Moreover, stimulus-specific adaptation was decreased at theta/alpha frequencies in left temporal regions, which correlated with reduced MMNm spectral power and ERF amplitude. Finally, phase-reset of alpha-oscillations after deviant tones in left thalamus was impaired, which correlated with impaired MMNm generation in auditory cortex. Importantly, both non-rhythmic and rhythmic components of spectral activity contributed to the MMNm response.

CONCLUSIONS

Our data indicate that deficits in theta-/alpha- and gamma-band activity in cortical and subcortical regions as well as impaired spectral responses to standard sounds could constitute potential mechanisms for dysfunctional MMN generation in schizophrenia, providing a novel perspective towards MMN deficits in the disorder.

Novelty detection in an auditory oddball task on freely moving rats

The relative importance or saliency of sensory inputs depend on the animal's environmental context and the behavioural responses to these same inputs can vary over time. Here we show how freely moving rats, trained to discriminate between deviant tones embedded in a regular pattern of repeating stimuli and different variations of the classic oddball paradigm, can detect deviant tones, and this discriminability resembles the properties that are typical of neuronal adaptation described in previous studies. Moreover, the auditory brainstem response (ABR) latency decreases after training, a finding consistent with the notion that animals develop a type of plasticity to auditory stimuli. Our study suggests the existence of a form of long-term memory that may modulate the level of neuronal adaptation according to its behavioural relevance, and sets the ground for future experiments that will help to disentangle the functional mechanisms that govern behavioural habituation and its relation to neuronal adaptation.

Extensive representation of sensory deviance in the responses to auditory gaps in unanesthetized rats

Unexpected changes in incoming sensory streams are associated with large errors in predicting the deviant stimulus relative to a memory trace of past stimuli. Mismatch negativity (MMN) in human studies and the release from stimulus-specific adaptation (SSA) in animal models correlate with prediction errors and deviance detection.¹ In human studies, violation of expectations elicited by an unexpected stimulus omission resulted in an omission MMN.^2,3,4,5 These responses are evoked after the expected occurrence time of the omitted stimulus, implying that they reflect the violation of a temporal expectancy.⁶ Because they are often time locked to the end of the omitted stimulus,^4,6,7 they resemble off responses. Indeed, suppression of cortical activity after the termination of the gap disrupts gap detection, suggesting an essential role for offset responses.⁸ Here, we demonstrate that brief gaps in short noise bursts in the auditory cortex of unanesthetized rats frequently evoke offset responses. Importantly, we show that omission responses are elicited when these gaps are expected but are omitted. These omission responses, together with the release from SSA of both onset and offset responses to rare gaps, form a rich and varied representation of prediction-related signals in the auditory cortex of unanesthetized rats, extending substantially and refining the representations described previously in anesthetized rats.

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.

Auditory evoked response to an oddball paradigm in children wearing cochlear implants

OBJECTIVE

Although children with cochlear implants (CI) achieve remarkable success with their device, considerable variability remains in individual outcomes. Here, we explored whether auditory evoked potentials recorded during an oddball paradigm could provide useful markers of auditory processing in this pediatric population.

METHODS

High-density electroencephalography (EEG) was recorded in 75 children listening to standard and odd noise stimuli: 25 had normal hearing (NH) and 50 wore a CI, divided between high language (HL) and low language (LL) abilities. Three metrics were extracted: the first negative and second positive components of the standard waveform (N1-P2 complex) close to the vertex, the mismatch negativity (MMN) around Fz and the late positive component (P3) around Pz of the difference waveform.

RESULTS

While children with CIs generally exhibited a well-formed N1-P2 complex, those with language delays typically lacked reliable MMN and P3 components. But many children with CIs with age-appropriate skills showed MMN and P3 responses similar to those of NH children. Moreover, larger and earlier P3 (but not MMN) was linked to better literacy skills.

CONCLUSIONS

Auditory evoked responses differentiated children with CIs based on their good or poor skills with language and literacy.

SIGNIFICANCE

This short paradigm could eventually serve as a clinical tool for tracking the developmental outcomes of implanted children.

Electrically evoked mismatch negativity responses to loudness and pitch cues in cochlear implant users

Objective measurements could improve cochlear implant (CI) fitting, especially for CI users who have difficulty assessing their hearing impressions. In this study, we investigated the electrically evoked mismatch negativity (eMMN) brain potential as a mainly preattentive response to pitch and loudness changes. In an electrophysiological exploratory study with 21 CI users, pitch and loudness cues were presented in controlled oddball paradigms that directly electrically stimulated the CI via software. Out of them 17 valid data sets were analyzed. A pitch cue was produced by changing the stimulating CI electrodes (pairs of adjacent electrodes). A loudness cue originated from changing the stimulation amplitude on one CI electrode. MMN responses were measured unsing clinical electroencephalography recording according to a standard recording protocol. At the group level, significant eMMN responses were elicited for loudness cues and for pitch cues at basal electrode pairs but not at apical electrode pairs. The effect of deviance direction was not significant and no stimulus artifacts were observed. Recording an electrically evoked MMN in response to loudness changes in CI users is generally feasible, and is, therefore, promising to support CI fitting procedures in the future. Detection of pitch cues would require a greater electrode distance between selected electrodes for standard and deviant stimuli, especially in apical regions. A routine clinical setup can be used to measure eMMN.

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.

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.

Cortico-fugal regulation of predictive coding

Sensory systems must account for both contextual factors and prior experience to adaptively engage with the dynamic external environment. In the central auditory system, neurons modulate their responses to sounds based on statistical context. These response modulations can be understood through a hierarchical predictive coding lens: responses to repeated stimuli are progressively decreased, in a process known as repetition suppression, whereas unexpected stimuli produce a prediction error signal. Prediction error incrementally increases along the auditory hierarchy from the inferior colliculus (IC) to the auditory cortex (AC), suggesting that these regions may engage in hierarchical predictive coding. A potential substrate for top-down predictive cues is the massive set of descending projections from the auditory cortex to subcortical structures, although the role of this system in predictive processing has never been directly assessed. We tested the effect of optogenetic inactivation of the auditory cortico-collicular feedback in awake mice on responses of IC neurons to stimuli designed to test prediction error and repetition suppression. Inactivation of the cortico-collicular pathway led to a decrease in prediction error in IC. Repetition suppression was unaffected by cortico-collicular inactivation, suggesting that this metric may reflect fatigue of bottom-up sensory inputs rather than predictive processing. We also discovered populations of IC units that exhibit repetition enhancement, a sequential increase in firing with stimulus repetition. Cortico-collicular inactivation led to a decrease in repetition enhancement in the central nucleus of IC, suggesting that it is a top-down phenomenon. Negative prediction error, a stronger response to a tone in a predictable rather than unpredictable sequence, was suppressed in shell IC units during cortico-collicular inactivation. These changes in predictive coding metrics arose from bidirectional modulations in the response to the standard and deviant contexts, such that units in IC responded more similarly to each context in the absence of cortical input. We also investigated how these metrics compare between the anesthetized and awake states by recording from the same units under both conditions. We found that metrics of predictive coding and deviance detection differ depending on the anesthetic state of the animal, with negative prediction error emerging in the central IC and repetition enhancement and prediction error being more prevalent in the absence of anesthesia. Overall, our results demonstrate that the auditory cortex provides cues about the statistical context of sound to subcortical brain regions via direct feedback, regulating processing of both prediction and repetition.

Visual Mismatch Negativity Reflects Enhanced Response to the Deviant: Evidence From Event-Related Potentials and Electroencephalogram Time-Frequency Analysis

Automatic detection of information changes in the visual environment is crucial for individual survival. Researchers use the oddball paradigm to study the brain’s response to frequently presented (standard) stimuli and occasionally presented (deviant) stimuli. The component that can be observed in the difference wave is called visual mismatch negativity (vMMN), which is obtained by subtracting event-related potentials (ERPs) evoked by the deviant from ERPs evoked by the standard. There are three hypotheses to explain the vMMN. The sensory fatigue (or refractoriness) hypothesis considers that weakened neural activity caused by repetition results in decreased ERPs of the standard. The memory trace hypothesis proposes that vMMN results from increased responses to the deviant. The predictive coding hypothesis attributes the difference to enhanced responses for deviants and suppression for standards. However, when distinguishing between these effects, previous researchers did not consider the effect of low-level features on the vMMN. In this experiment, we used face sequences composed of different emotions (e.g., neutral and fearful face) and presented an oddball sequence, a reverse oddball sequence, and an equiprobable sequence to participants. The deviant of the oddball sequence was subtracted from the standard of the oddball sequence, the reverse oddball sequence, and the same type of stimulus of the equiprobable sequence to get oddball-vMMN (vMMN1), reverse oddball-vMMN (vMMN2), and equiprobable-vMMN (vMMN3), respectively. The results showed no significant difference between vMMN2 and vMMN3 in 100–350 ms following stimulus onset, while the vMMN effect was significant, indicating that the probability of the standard did not affect vMMN, which supported the memory trace hypothesis. Additionally, the fearful-related vMMN were more negative than the neutral-related vMMN within the range of 100–150 ms, suggesting a negative bias. We analyzed the source location of different vMMNs. There was no significant difference in brain regions between different vMMNs. Time-frequency analysis showed that the deviant had stronger theta-band oscillatory than the standard (visual mismatch oscillatory responses, vMORs). However, there was no difference between vMORs2 and vMORs3, indicating that vMORs reflect an enhanced response to the deviant in terms of neural oscillation, supporting the memory trace hypothesis.

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.

Sensitivity of neural responses in the inferior colliculus to statistical features of sound textures

Previous psychophysical studies have identified a hierarchy of time-averaged statistics which determine the identity of natural sound textures. However, it is unclear whether the neurons in the inferior colliculus (IC) are sensitive to each of these statistical features in the natural sound textures. We used 13 representative sound textures spanning the space of 3 statistics extracted from over 200 natural textures. The synthetic textures were generated by incorporating the statistical features in a step-by-step manner, in which a particular statistical feature was changed while the other statistical features remain unchanged. The extracellular activity in response to the synthetic texture stimuli was recorded in the IC of anesthetized rats. Analysis of the transient and sustained multiunit activity after each transition of statistical feature showed that the IC units were sensitive to the changes of all types of statistics, although to a varying extent. For example, we found that more neurons were sensitive to the changes in variance than that in the modulation correlations. Our results suggest that the sensitivity of the statistical features in the subcortical levels contributes to the identification and discrimination of natural sound textures.

Auditory oddball responses in Tursiops truncatus

Two previous studies suggest that bottlenose dolphins exhibit an "oddball" auditory evoked potential (AEP) to stimulus trains where one of two stimuli has a low probability of occurrence relative to another. However, they reported oddball AEPs at widely different latency ranges (50 vs 500 ms). The present work revisited this experiment in a single dolphin to report the AEPs in response to two tones each assigned probabilities of 0.2, 0.8, and 1 across sessions. The AEP was further isolated from background EEG using independent component analysis, and showed condition effects in the 40-60 ms latency range.

A Critical Review of the Deviance Detection Theory of Mismatch Negativity

Mismatch negativity (MMN) is a component of the difference waveform derived from passive auditory oddball stimulation. Since its inception in 1978, this has become one of the most popular event-related potential techniques, with over two-thousand published studies using this method. This is a testament to the ingenuity and commitment of generations of researchers engaging in basic, clinical and animal research. Despite this intensive effort, high-level descriptions of the mechanisms theorized to underpin mismatch negativity have scarcely changed over the past four decades. The prevailing deviance detection theory posits that MMN reflects inattentive detection of difference between repetitive standard and infrequent deviant stimuli due to a mismatch between the unexpected deviant and a memory representation of the standard. Evidence for these mechanisms is inconclusive, and a plausible alternative sensory processing theory considers fundamental principles of sensory neurophysiology to be the primary source of differences between standard and deviant responses evoked during passive oddball stimulation. By frequently being restated without appropriate methods to exclude alternatives, the potentially flawed deviance detection theory has remained largely dominant, which could lead some researchers and clinicians to assume its veracity implicitly. It is important to have a more comprehensive understanding of the source(s) of MMN generation before its widespread application as a clinical biomarker. This review evaluates issues of validity concerning the prevailing theoretical account of mismatch negativity and the passive auditory oddball paradigm, highlighting several limitations regarding its interpretation and clinical application.

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.

Adjudicating Between Local and Global Architectures of Predictive Processing in the Subcortical Auditory Pathway

Predictive processing, a leading theoretical framework for sensory processing, suggests that the brain constantly generates predictions on the sensory world and that perception emerges from the comparison between these predictions and the actual sensory input. This requires two distinct neural elements: generative units, which encode the model of the sensory world; and prediction error units, which compare these predictions against the sensory input. Although predictive processing is generally portrayed as a theory of cerebral cortex function, animal and human studies over the last decade have robustly shown the ubiquitous presence of prediction error responses in several nuclei of the auditory, somatosensory, and visual subcortical pathways. In the auditory modality, prediction error is typically elicited using so-called oddball paradigms, where sequences of repeated pure tones with the same pitch are at unpredictable intervals substituted by a tone of deviant frequency. Repeated sounds become predictable promptly and elicit decreasing prediction error; deviant tones break these predictions and elicit large prediction errors. The simplicity of the rules inducing predictability make oddball paradigms agnostic about the origin of the predictions. Here, we introduce two possible models of the organizational topology of the predictive processing auditory network: (1) the global view, that assumes that predictions on the sensory input are generated at high-order levels of the cerebral cortex and transmitted in a cascade of generative models to the subcortical sensory pathways; and (2) the local view, that assumes that independent local models, computed using local information, are used to perform predictions at each processing stage. In the global view information encoding is optimized globally but biases sensory representations along the entire brain according to the subjective views of the observer. The local view results in a diminished coding efficiency, but guarantees in return a robust encoding of the features of sensory input at each processing stage. Although most experimental results to-date are ambiguous in this respect, recent evidence favors the global model.

Visual mismatch responses index surprise signalling but not expectation suppression

The ability to distinguish between commonplace and unusual sensory events is critical for efficient learning and adaptive behaviour. This has been investigated using oddball designs in which sequences of often-appearing (i.e., expected) stimuli are interspersed with rare (i.e., surprising) deviants. Resulting differences in electrophysiological responses following surprising compared to expected stimuli are known as visual mismatch responses (VMRs). VMRs are thought to index co-occurring contributions of stimulus repetition effects, expectation suppression (that occurs when one's expectations are fulfilled), and expectation violation (i.e., surprise) responses; however, these different effects have been conflated in existing oddball designs. To better isolate and quantify effects of expectation suppression and surprise, we adapted an oddball design based on Fast Periodic Visual Stimulation (FPVS) that controls for stimulus repetition effects. We recorded electroencephalography (EEG) while participants (N = 48) viewed stimulation sequences in which a single face identity was periodically presented at 6 Hz. Critically, one of two different face identities (termed oddballs) appeared as every 7th image throughout the sequence. The presentation probabilities of each oddball image within a sequence varied between 10 and 90%, such that participants could form expectations about which oddball face identity was more likely to appear within each sequence. We also included 'expectation neutral' 50% probability sequences, whereby consistently biased expectations would not be formed for either oddball face identity. We found that VMRs indexed surprise responses, and effects of expectation suppression were absent. That is, ERPs were more negative-going at occipitoparietal electrodes for surprising compared to neutral oddballs, but did not differ between expected and neutral oddballs. Surprising oddball-evoked ERPs were also highly similar across the 10-40% appearance probability conditions. Our findings indicate that VMRs which are not accounted for by repetition effects are best described as an all-or-none surprise response, rather than a minimisation of prediction error responses associated with expectation suppression.

Adaptation Modulates Spike-Phase Coupling Tuning Curve in the Rat Primary Auditory Cortex

Adaptation is an important mechanism that causes a decrease in the neural response both in terms of local field potentials (LFP) and spiking activity. We previously showed this reduction effect in the tuning curve of the primary auditory cortex. Moreover, we revealed that a repeated stimulus reduces the neural response in terms of spike-phase coupling (SPC). In the current study, we examined the effect of adaptation on the SPC tuning curve. To this end, employing the phase-locking value (PLV) method, we estimated the spike-LFP coupling. The data was obtained by a simultaneous recording from four single-electrodes in the primary auditory cortex of 15 rats. We first investigated whether the neural system may use spike-LFP phase coupling in the primary auditory cortex to encode sensory information. Secondly, we investigated the effect of adaptation on this potential SPC tuning. Our data showed that the coupling between spikes’ times and the LFP phase in beta oscillations represents sensory information (different stimulus frequencies), with an inverted bell-shaped tuning curve. Furthermore, we showed that adaptation to a specific frequency modulates SPC tuning curve of the adapter and its neighboring frequencies. These findings could be useful for interpretation of feature representation in terms of SPC and the underlying neural mechanism of adaptation.

The Thalamocortical Circuit of Auditory Mismatch Negativity

BACKGROUND

Mismatch negativity (MMN) is an extensively validated biomarker of cognitive function across both normative and clinical populations and has previously been localized to supratemporal auditory cortex. MMN is thought to represent a comparison of the features of the present stimulus versus a mnemonic template formed by the prior stimuli.

METHODS

We used concurrent thalamic and primary auditory cortical (A1) laminar recordings in 7 macaques to evaluate the relative contributions of core (lemniscal) and matrix (nonlemniscal) thalamic afferents to MMN generation.

RESULTS

We demonstrated that deviance-related activity is observed mainly in matrix regions of auditory thalamus, MMN generators are most prominent in layer 1 of cortex as opposed to sensory responses that activate layer 4 first and sequentially all cortical layers, and MMN is elicited independent of the frequency tuning of A1 neuronal ensembles. Consistent with prior reports, MMN-related thalamocortical activity was strongly inhibited by ketamine.

CONCLUSIONS

Taken together, our results demonstrate distinct matrix versus core thalamocortical circuitry underlying the generation of a higher-order brain response (MMN) versus sensory responses.

Ensemble modeling of auditory streaming reveals potential sources of bistability across the perceptual hierarchy

Perceptual bistability-the spontaneous, irregular fluctuation of perception between two interpretations of a stimulus-occurs when observing a large variety of ambiguous stimulus configurations. This phenomenon has the potential to serve as a tool for, among other things, understanding how function varies across individuals due to the large individual differences that manifest during perceptual bistability. Yet it remains difficult to interpret the functional processes at work, without knowing where bistability arises during perception. In this study we explore the hypothesis that bistability originates from multiple sources distributed across the perceptual hierarchy. We develop a hierarchical model of auditory processing comprised of three distinct levels: a Peripheral, tonotopic analysis, a Central analysis computing features found more centrally in the auditory system, and an Object analysis, where sounds are segmented into different streams. We model bistable perception within this system by applying adaptation, inhibition and noise into one or all of the three levels of the hierarchy. We evaluate a large ensemble of variations of this hierarchical model, where each model has a different configuration of adaptation, inhibition and noise. This approach avoids the assumption that a single configuration must be invoked to explain the data. Each model is evaluated based on its ability to replicate two hallmarks of bistability during auditory streaming: the selectivity of bistability to specific stimulus configurations, and the characteristic log-normal pattern of perceptual switches. Consistent with a distributed origin, a broad range of model parameters across this hierarchy lead to a plausible form of perceptual bistability.

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.

Emergence of prediction error along the human auditory hierarchy

Auditory prediction errors have been extensively associated with the mismatch negativity (MMN), a cortical auditory evoked potential that denotes deviance detection. Yet, many studies lacked the appropriate controls to disentangle sensory adaptation from prediction error. Furthermore, subcortical deviance detection has been shown in humans through recordings of the frequency-following response (FFR), an early auditory evoked potential that reflects the neural tracking of the periodic characteristics of a sound, suggesting the possibility that prediction errors emerge subcortically in the auditory pathway. The present study aimed at investigating the emergence of prediction error along the auditory hierarchy in humans through combined recordings of the FFR and the MMN, tapping at subcortical and cortical levels, respectively, while disentangling prediction error from sensory adaptation with the use of appropriate controls. "Oddball" sequences of pure tones featuring repeated "standard" stimuli (269 Hz; p = 0.8) and rare "deviant" stimuli (p = 0.2; of 289, 329 and 409 Hz delivered in separated blocks to test "frequency separation" effects) were presented to nineteen healthy young participants. "Reversed" oddball sequences (where standard and deviant tones swapped their roles) were presented allowing comparison of responses to same physical stimuli as a function of functional role (i.e., standard, deviant). Critically, control sequences featuring five equiprobable tones (p = 0.2) allowed to dissociate sensory adaptation from prediction error. Results revealed that the MMN amplitude increased as a function of frequency separation yet displayed the same amplitude when retrieved against the control sequences, confirming previous results. FFRs showed repetition enhancement effects across all frequency separations, as supported by larger spectral amplitude to standard than to deviant and control stimuli. This pattern of results provides insights into the hierarchy of the human prediction error system in audition, suggesting that prediction errors in humans emerge at cortical level.

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.

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.

The Role of Top-Down Modulation in Shaping Sensory Processing Across Brain States: Implications for Consciousness

Top-down, feedback projections account for a large portion of all connections between neurons in the thalamocortical system, yet their precise role remains the subject of much discussion. A large number of studies has focused on investigating how sensory information is transformed across hierarchically-distributed processing stages in a feedforward fashion, and computational models have shown that purely feedforward artificial neural networks can even outperform humans in pattern classification tasks. What is then the functional role of feedback connections? Several key roles have been identified, ranging from attentional modulation to, crucially, conscious perception. Specifically, most of the major theories on consciousness postulate that feedback connections would play an essential role in enabling sensory information to be consciously perceived. Consequently, it follows that their efficacy in modulating target regions should drastically decrease in nonconscious brain states [non-rapid eye movement (REM) sleep, anesthesia] compared to conscious ones (wakefulness), and also in instances when a given sensory stimulus is not perceived compared to when it is. Until recently, however, this prediction could only be tested with correlative experiments, due to the lack of techniques to selectively manipulate and measure the activity of feedback pathways. In this article, we will review the most recent literature on the functions of feedback connections across brain states and based on the presence or absence of perception. We will focus on experiments studying mismatch negativity, a phenomenon which has been hypothesized to rely on top-down modulation but which persists during nonconscious states. While feedback modulation is generally dampened in nonconscious states and enhanced when perception occurs, there are clear deviations from this rule. As we will discuss, this may pose a challenge to most theories of consciousness, and possibly require a change in how the level of consciousness in supposedly nonconscious states is assessed.

Stimulus-Specific Adaptation Decreases the Coupling of Spikes to LFP Phase

Stimulus repetition suppresses the neural activity in different sensory areas of the brain. This mechanism of so-called stimulus-specific adaptation (SSA) has been observed in both spiking activity and local field potential (LFP) responses. However, much remains to be known about the effect of SSA on the spike–LFP relation. In this study, we approached this issue by investigating the spike-phase coupling (SPC) in control and adapting paradigms. For the control paradigm, pure tones were presented in a random unbiased sequence. In the adapting paradigm, the same stimuli were presented in a random pattern but it was biased to an adapter stimulus. In fact, the adapter occupied 80% of the adapting sequence. During the tasks, LFP and multi-unit activity were recorded simultaneously from the primary auditory cortex of 15 anesthetized rats. To clarify the effect of adaptation on the relation between spike and LFP responses, the SPC of the adapter stimulus in these two paradigms was evaluated. Here, we employed phase locking value method for calculating the SPC. Our data show a strong coupling of spikes to LFP phase most prominently in beta band. This coupling was observed to decrease in the adapting condition compared to the control one. Importantly, we found that adaptation reduces spikes dominantly from the preferred phase of LFP in which spikes are more likely to be present there. As a result, the preferred phase of LFP may play a key role in coordinating neuronal spiking activity in neural adaptation mechanism. This finding is important for interpretation of the underlying neural mechanism of adaptation and also can be used in the context of the network and related connectivity models.

Associations between sounds and actions in early auditory cortex of nonhuman primates

An individual may need to take different actions to the same stimulus in different situations to achieve a given goal. The selection of the appropriate action hinges on the previously learned associations between stimuli, actions, and outcomes in the situations. Here, using a go/no-go paradigm and a symmetrical reward, we show that early auditory cortex of nonhuman primates represents such associations, in both the spiking activity and the local field potentials. Sound-evoked neuronal responses changed with sensorimotor associations shortly after sound onset, and the neuronal responses were largest when the sound signaled that a no-go response was required in a trial to obtain a reward. Our findings suggest that association processes take place in the auditory system and do not necessarily rely on association cortex. Thus, auditory cortex may contribute to a rapid selection of the appropriate motor responses to sounds during goal-directed behavior.

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

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

Capacities and neural mechanisms for auditory statistical learning across species

Statistical learning has been proposed as a possible mechanism by which individuals can become sensitive to the structures of language fundamental for speech perception. Since its description in human infants, statistical learning has been described in human adults and several non-human species as a general process by which animals learn about stimulus-relevant statistics. The neurobiology of statistical learning is beginning to be understood, but many questions remain about the underlying mechanisms. Why is the developing brain particularly sensitive to stimulus and environmental statistics, and what neural processes are engaged in the adult brain to enable learning from statistical regularities in the absence of external reward or instruction? This review will survey the statistical learning abilities of humans and non-human animals with a particular focus on communicative vocalizations. We discuss the neurobiological basis of statistical learning, and specifically what can be learned by exploring this process in both humans and laboratory animals. Finally, we describe advantages of studying vocal communication in rodents as a means to further our understanding of the cortical plasticity mechanisms engaged during statistical learning. We examine the use of rodents in the context of pup retrieval, which is an auditory-based and experience-dependent form of maternal behavior.

Evolutionarily conserved coding properties favour the neuronal representation of heterospecific signals of a sympatric katydid species

To function as a mechanism in premating isolation, the divergent and species-specific calling songs of acoustic insects must be reliably processed by the afferent auditory pathway of receivers. Here, we analysed the responses of interneurons in a katydid species that uses long-lasting acoustic trills and compared these with previously reported data for homologous interneurons of a sympatric species that uses short chirps as acoustic signals. Some interneurons of the trilling species respond exclusively to the heterospecific chirp due to selective, low-frequency tuning and "novelty detection". These properties have been considered as evolutionary adaptations in the sensory system of the chirper, which allow it to detect signals effectively during the simultaneous calling of the sympatric sibling species. We propose that these two mechanisms, shared by the interneurons of both species, did not evolve in the chirper to guarantee its ability to detect the chirp under masking conditions. Instead we suggest that chirpers evolved an additional, 2-kHz component in their song and exploited pre-existing neuronal properties for detecting their song under masking noise. The failure of some interneurons to respond to the conspecific song in trillers does not prevent intraspecific communication, as other interneurons respond to the trill.

Processing of auditory novelty across the cortical hierarchy: An intracranial electrophysiology study

Under the predictive coding hypothesis, specific spatiotemporal patterns of cortical activation are postulated to occur during sensory processing as expectations generate feedback predictions and prediction errors generate feedforward signals. Establishing experimental evidence for this information flow within cortical hierarchy has been difficult, especially in humans, due to spatial and temporal limitations of non-invasive measures of cortical activity. This study investigated cortical responses to auditory novelty using the local/global deviant paradigm, which engages the hierarchical network underlying auditory predictive coding over short ('local deviance'; LD) and long ('global deviance'; GD) time scales. Electrocorticographic responses to auditory stimuli were obtained in neurosurgical patients from regions of interest (ROIs) including auditory, auditory-related and prefrontal cortex. LD and GD effects were assayed in averaged evoked potential (AEP) and high gamma (70-150 Hz) signals, the former likely dominated by local synaptic currents and the latter largely reflecting local spiking activity. AEP LD effects were distributed across all ROIs, with greatest percentage of significant sites in core and non-core auditory cortex. High gamma LD effects were localized primarily to auditory cortex in the superior temporal plane and on the lateral surface of the superior temporal gyrus (STG). LD effects exhibited progressively longer latencies in core, non-core, auditory-related and prefrontal cortices, consistent with feedforward signaling. The spatial distribution of AEP GD effects overlapped that of LD effects, but high gamma GD effects were more restricted to non-core areas. High gamma GD effects had shortest latencies in STG and preceded AEP GD effects in most ROIs. This latency profile, along with the paucity of high gamma GD effects in the superior temporal plane, suggest that the STG plays a prominent role in initiating novelty detection signals over long time scales. Thus, the data demonstrate distinct patterns of information flow in human cortex associated with auditory novelty detection over multiple time scales.

Rhesus Monkeys (Macaca mulatta) Sense Isochrony in Rhythm, but Not the Beat: Additional Support for the Gradual Audiomotor Evolution Hypothesis

Charles Darwin suggested the perception of rhythm to be common to all animals. While only recently experimental research is finding some support for this claim, there are also aspects of rhythm cognition that appear to be species-specific, such as the capability to perceive a regular pulse (or beat) in a varying rhythm. In the current study, using EEG, we adapted an auditory oddball paradigm that allows for disentangling the contributions of beat perception and isochrony to the temporal predictability of the stimulus. We presented two rhesus monkeys (Macaca mulatta) with a rhythmic sequence in two versions: an isochronous version, that was acoustically accented such that it could induce a duple meter (like a march), and a jittered version using the same acoustically accented sequence but that was presented in a randomly timed fashion, as such disabling beat induction. The results reveal that monkeys are sensitive to the isochrony of the stimulus, but not its metrical structure. The MMN was influenced by the isochrony of the stimulus, resulting in a larger MMN in the isochronous as opposed to the jittered condition. However, the MMN for both monkeys showed no interaction between metrical position and isochrony. So, while the monkey brain appears to be sensitive to the isochrony of the stimulus, we find no evidence in support of beat perception. We discuss these results in the context of the gradual audiomotor evolution (GAE) hypothesis (Merchant and Honing, 2014) that suggests beat-based timing to be omnipresent in humans but only weakly so or absent in non-human primates.

Deviance sensitivity in the auditory cortex of freely moving rats

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

Taking Attention Away from the Auditory Modality: Context-dependent Effects on Early Sensory Encoding of Speech

Increasing visual perceptual load can reduce pre-attentive auditory cortical activity to sounds, a reflection of the limited and shared attentional resources for sensory processing across modalities. Here, we demonstrate that modulating visual perceptual load can impact the early sensory encoding of speech sounds, and that the impact of visual load is highly dependent on the predictability of the incoming speech stream. Participants (n = 20, 9 females) performed a visual search task of high (target similar to distractors) and low (target dissimilar to distractors) perceptual load, while early auditory electrophysiological responses were recorded to native speech sounds. Speech sounds were presented either in a 'repetitive context', or a less predictable 'variable context'. Independent of auditory stimulus context, pre-attentive auditory cortical activity was reduced during high visual load, relative to low visual load. We applied a data-driven machine learning approach to decode speech sounds from the early auditory electrophysiological responses. Decoding performance was found to be poorer under conditions of high (relative to low) visual load, when the incoming acoustic stream was predictable. When the auditory stimulus context was less predictable, decoding performance was substantially greater for the high (relative to low) visual load conditions. Our results provide support for shared attentional resources between visual and auditory modalities that substantially influence the early sensory encoding of speech signals in a context-dependent manner.

Tone-Evoked Acoustic Change Complex (ACC) Recorded in a Sedated Animal Model

The acoustic change complex (ACC) is a scalp-recorded cortical evoked potential complex generated in response to changes (e.g., frequency, amplitude) in an auditory stimulus. The ACC has been well studied in humans, but to our knowledge, no animal model has been evaluated. In particular, it was not known whether the ACC could be recorded under the conditions of sedation that likely would be necessary for recordings from animals. For that reason, we tested the feasibility of recording ACC from sedated cats in response to changes of frequency and amplitude of pure-tone stimuli. Cats were sedated with ketamine and acepromazine, and subdermal needle electrodes were used to record electroencephalographic (EEG) activity. Tones were presented from a small loudspeaker located near the right ear. Continuous tones alternated at 500-ms intervals between two frequencies or two levels. Neurometric functions were created by recording neural response amplitudes while systematically varying the magnitude of steps in frequency centered in octave frequency around 2, 4, 8, and 16 kHz, all at 75 dB SPL, or in decibel level around 75 dB SPL tested at 4 and 8 kHz. The ACC could be recorded readily under this ketamine/azepromazine sedation. In contrast, ACC could not be recorded reliably under any level of isoflurane anesthesia that was tested. The minimum frequency (expressed as Weber fractions (df/f)) or level steps (expressed in dB) needed to elicit ACC fell in the range of previous thresholds reported in animal psychophysical tests of discrimination. The success in recording ACC in sedated animals suggests that the ACC will be a useful tool for evaluation of other aspects of auditory acuity in normal hearing and, presumably, in electrical cochlear stimulation, especially for novel stimulation modes that are not yet feasible in humans.

Deviant Processing in the Primary Somatosensory Cortex

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

WITHDRAWN: Auditory Surprise Model Based on Pattern Retrieval from the Past Observation

This article has been withdrawn: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy). This article has been withdrawn at the request of the authors. The authors regrets that the reason for withdrawal is due to an disagreement in authorship and in scope of data disclosure. The authors apologize to the readers for this unfortunate error.