Intracellular correlates of stimulus-specific adaptation

Detection of a temporal salient object benefits from visual stimulus-specific adaptation in avian midbrain inhibitory nucleus

Food and predators are the most noteworthy objects for the basic survival of wild animals, and both are often deviant in both spatial and temporal domains and quickly attract an animal's attention. Although stimulus-specific adaptation (SSA) is considered a potential neural basis of salient sound detection in the temporal domain, related research on visual SSA is limited and its relationship with temporal saliency is uncertain. The avian nucleus isthmi pars magnocellularis (Imc), which is central to midbrain selective attention network, is an ideal site to investigate the neural correlate of visual SSA and detection of a salient object in the time domain. Here, the constant order paradigm was applied to explore the visual SSA in the Imc of pigeons. The results showed that the firing rates of Imc neurons gradually decrease with repetitions of motion in the same direction, but recover when a motion in a deviant direction is presented, implying visual SSA to the direction of a moving object. Furthermore, enhanced response for an object moving in other directions that were not presented ever in the paradigm is also observed. To verify the neural mechanism underlying these phenomena, we introduced a neural computation model involving a recoverable synaptic change with a "center-surround" pattern to reproduce the visual SSA and temporal saliency for the moving object. These results suggest that the Imc produces visual SSA to motion direction, allowing temporal salient object detection, which may facilitate the detection of the sudden appearance of a predator.

Sequential maturation of stimulus-specific adaptation in the mouse lemniscal auditory system

Stimulus-specific adaptation (SSA), the reduction of neural activity to a common stimulus that does not generalize to other, rare stimuli, is an essential property of our brain. Although well characterized in adults, it is still unknown how it develops during adolescence and what neuronal circuits are involved. Using in vivo electrophysiology and optogenetics in the lemniscal pathway of the mouse auditory system, we observed SSA to be stable from postnatal day 20 (P20) in the inferior colliculus, to develop until P30 in the auditory thalamus and even later in the primary auditory cortex (A1). We found this maturation process to be experience-dependent in A1 but not in thalamus and to be related to alterations in deep but not input layers of A1. We also identified corticothalamic projections to be implicated in thalamic SSA development. Together, our results reveal different circuits underlying the sequential SSA maturation and provide a unique perspective to understand predictive coding and surprise across sensory systems.

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.

Perspectives on adaptive dynamical systems

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

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.

Context-Dependent Inhibitory Control of Stimulus-Specific Adaptation

Stimulus-specific adaptation (SSA) is the reduction in responses to frequent stimuli (standards) that does not generalize to rare stimuli (deviants). We investigated the contribution of inhibition in auditory cortex to SSA using two-photon targeted cell-attached recordings and optogenetic manipulations in male mice. We characterized the responses of parvalbumin (PV)-, somatostatin (SST)-, and vasoactive intestinal polypeptide (VIP)-expressing interneurons of layer 2/3, and of serotonin receptor 5HT3a-expressing interneurons of layer 1. All populations showed early-onset SSA. Unexpectedly, the PV, SST, and VIP populations exhibited a substantial late component of evoked activity, often stronger for standard than for deviant stimuli. Optogenetic suppression of PV neurons facilitated pyramidal neuron responses substantially more (approximately ×10) for deviants than for standards. VIP suppression decreased responses of putative PV neurons, specifically for standard but not for deviant stimuli. Thus, the inhibitory network does not generate cortical SSA, but powerfully controls its expression by differentially affecting the responses to deviants and to standards.SIGNIFICANCE STATEMENT Stimulus-specific adaptation (SSA) reflects the growing complexity of auditory processing along the ascending auditory system. In the presence of SSA, neuronal responses depend not only on the stimulus itself but also on the history of stimulation. Strong SSA in the fast, ascending auditory pathway first occurs in cortex. Here we studied the role of the cortical inhibitory network in shaping SSA, showing that while cortical inhibition does not generate SSA, it powerfully controls its expression. We deduce that the cortical network contributes in crucial ways to the properties of SSA.

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

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

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.

A robust model of Stimulus-Specific Adaptation validated on neuromorphic hardware

Stimulus-Specific Adaptation (SSA) to repetitive stimulation is a phenomenon that has been observed across many different species and in several brain sensory areas. It has been proposed as a computational mechanism, responsible for separating behaviorally relevant information from the continuous stream of sensory information. Although SSA can be induced and measured reliably in a wide variety of conditions, the network details and intracellular mechanisms giving rise to SSA still remain unclear. Recent computational studies proposed that SSA could be associated with a fast and synchronous neuronal firing phenomenon called Population Spikes (PS). Here, we test this hypothesis using a mean-field rate model and corroborate it using a neuromorphic hardware. As the neuromorphic circuits used in this study operate in real-time with biologically realistic time constants, they can reproduce the same dynamics observed in biological systems, together with the exploration of different connectivity schemes, with complete control of the system parameter settings. Besides, the hardware permits the iteration of multiple experiments over many trials, for extended amounts of time and without losing the networks and individual neural processes being studied. Following this "neuromorphic engineering" approach, we therefore study the PS hypothesis in a biophysically inspired recurrent networks of spiking neurons and evaluate the role of different linear and non-linear dynamic computational primitives such as spike-frequency adaptation or short-term depression (STD). We compare both the theoretical mean-field model of SSA and PS to previously obtained experimental results in the area of novelty detection and observe its behavior on its neuromorphic physical equivalent model. We show how the approach proposed can be extended to other computational neuroscience modelling efforts for understanding high-level phenomena in mechanistic models.

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.

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.

Statistical learning of transition patterns in the songbird auditory forebrain

Statistical learning of transition patterns between sounds—a striking capability of the auditory system—plays an essential role in animals’ survival (e.g., detect deviant sounds that signal danger). However, the neural mechanisms underlying this capability are still not fully understood. We recorded extracellular multi-unit and single-unit activity in the auditory forebrain of awake male zebra finches while presenting rare repetitions of a single sound in a long sequence of sounds (canary and zebra finch song syllables) patterned in either an alternating or random order at different inter-stimulus intervals (ISI). When preceding stimuli were regularly alternating (alternating condition), a repeated stimulus violated the preceding transition pattern and was a deviant. When preceding stimuli were in random order (control condition), a repeated stimulus did not violate any regularities and was not a deviant. At all ISIs tested (1 s, 3 s, or jittered at 0.8–1.2 s), deviant repetition enhanced neural responses in the alternating condition in a secondary auditory area (caudomedial nidopallium, NCM) but not in the primary auditory area (Field L2); in contrast, repetition suppressed responses in the control condition in both Field L2 and NCM. When stimuli were presented in the classical oddball paradigm at jittered ISI (0.8–1.2 s), neural responses in both NCM and Field L2 were stronger when a stimulus occurred as deviant with low probability than when the same stimulus occurred as standard with high probability. Together, these results demonstrate: (1) classical oddball effect exists even when ISI is jittered and the onset of a stimulus is not fully predictable; (2) neurons in NCM can learn transition patterns between sounds at multiple ISIs and detect violation of these transition patterns; (3) sensitivity to deviant sounds increases from Field L2 to NCM in the songbird auditory forebrain. Further studies using the current paradigms may help us understand the neural substrate of statistical learning and even speech comprehension.

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

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

Stimulus-specific adaptation to behaviorally-relevant sounds in awake rats

Stimulus-specific adaptation (SSA) is the reduction in responses to a common stimulus that does not generalize, or only partially generalizes, to other stimuli. SSA has been studied mainly with sounds that bear no behavioral meaning. We hypothesized that the acquisition of behavioral meaning by a sound should modify the amount of SSA evoked by that sound. To test this hypothesis, we used fear conditioning in rats, using two word-like stimuli, derived from the English words "danger" and "safety", as well as pure tones. One stimulus (CS+) was associated with a foot shock whereas the other stimulus (CS-) was presented without a concomitant foot shock. We recorded neural responses to the auditory stimuli telemetrically, using chronically implanted multi-electrode arrays in freely moving animals before and after conditioning. Consistent with our hypothesis, SSA changed in a way that depended on the behavioral role of the sound: the contrast between standard and deviant responses remained the same or decreased for CS+ stimuli but increased for CS- stimuli, showing that SSA is shaped by experience. In most cases the sensory responses underlying these changes in SSA increased following conditioning. Unexpectedly, the responses to CS+ word-like stimuli showed a specific, large decrease, which we interpret as evidence for substantial inhibitory plasticity.

Synaptic Recruitment Enhances Gap Termination Responses in Auditory Cortex

The ability to detect short gaps in noise is an important tool for assessing the temporal resolution in the auditory cortex. However, the mere existence of responses to temporal gaps bounded by two short broadband markers is surprising, because of the expected short-term suppression that is prevalent in auditory cortex. Here, we used in-vivo intracellular recordings in anesthetized rats to dissect the synaptic mechanisms that underlie gap-related responses. When a gap is bounded by two short markers, a gap termination response was evoked by the onset of the second marker with minimal contribution from the offset of the first marker. Importantly, we show that the gap termination response was driven by a different (potentially partially overlapping) synaptic population than that underlying the onset response to the first marker. This recruitment of additional synaptic resources is a novel mechanism contributing to the important perceptual task of gap detection.

Mismatch-negativity (MMN) in animal models: Homology of human MMN?

Mismatch negativity (MMN) has long been considered to be one of the deviance-detecting neural characteristics. Animal models exhibit similar neural activities, called MMN-like responses; however, there has been considerable debate on whether MMN-like responses are homologous to MMN in humans. Herein, we reviewed several studies that compared the electrophysiological, pharmacological, and functional properties of MMN-like responses and adaptation-exhibiting middle-latency responses (MLRs) in animals with those in humans. Accumulating evidence suggests that there are clear differences between MMN-like responses and MLRs, in particular that MMN-like responses can be distinguished from mere effects of adaptation, i.e., stimulus-specific adaptation. Finally, we discuss a new direction for research on MMN-like responses by introducing our recent work, which demonstrated that MMN-like responses represent empirical salience of deviant stimuli, suggesting a new functional role of MMN beyond simple deviance detection.

Responses of neurons in the rat's inferior colliculus to a sound are affected by another sound in a space-dependent manner

The perception of a sound can be influenced by another sound in a space-dependent manner. An understanding of this perceptual phenomenon depends on knowledge about how the spatial relationship between two sounds affects neural responses to the sounds. We used the rat as a model system and equal-probability two-tone sequences as stimuli to evaluate how spatial separation between two asynchronously recurring sounds affected responses to the sounds in midbrain auditory neurons. We found that responses elicited by two tone bursts when they were colocalized at the ear contralateral to the neuron were different from the responses elicited by the same sounds when they were separated with one at the contralateral ear while the other at another location. For neurons with transient sound-driven firing and not responsive to stimulation presented at the ipsilateral ear, the response to a sound with a fixed location at the contralateral ear was enhanced when the second sound was separated. These neurons were likely important for detecting a sound in the presence of a spatially separated competing sound. Our results suggest that mechanisms underlying effects of spatial separation on neural responses to sounds may include adaptation and long-lasting binaural excitatory/inhibitory interaction.

Neural adaptation and cognitive inflexibility in repeated problem-solving behaviors

Repeated stimulus processing is often associated with a reduction in neural activity, known as neural adaptation. Therefore, people are more sensitive to novelty detection but likely lose flexibility in subsequent novelty processing after detection. To demonstrate the dynamic changes in neural adaption in repeated problem-solving behaviors and test its negative influence on subsequent nonrepetitive problem-solving behaviors, we adopted a Chinese character decomposition task in this fMRI study. Participants were asked to repeatedly perform 3-5 practice problems that could be solved by the same loose chunk decomposition (LCD) solution followed by a test problem that could be solved by a tight chunk decomposition (TCD) solution in the enhanced-set condition. The practice problem gradually elicited lower percent signal changes within the cuneus, superior parietal lobule (SPL), inferior frontal gyrus (IFG) and medial prefrontal cortex (mPFC) in serial positions -1, -2 and -3 of a set, implying that neural adaptation occurred in repeated practice. Both the test problem and the practice problem that following it recruited greater activation of the SPL and IFG in the enhanced-set condition than in the base-set condition when the practice problem and test problem alternately appeared, implying that the task switching cost from a more dominant task to a less dominant task and vice versa was increased after neural adaptation occurred. In other words, repeatedly solving a set of similar problems with the same solution likely leads to neural adaptation and cognitive inflexibility, which in turn have an undifferentiated impact on task switching. This finding expands existing knowledge about the neurocognitive mechanism underlying the formation of the mental set and sheds light on the influence of neural adaptation on subsequent processing.

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.

Neural Correlate of Transition Violation and Deviance Detection in the Songbird Auditory Forebrain

Deviants are stimuli that violate one's prediction about the incoming stimuli. Studying deviance detection helps us understand how nervous system learns temporal patterns between stimuli and forms prediction about the future. Detecting deviant stimuli is also critical for animals' survival in the natural environment filled with complex sounds and patterns. Using natural songbird vocalizations as stimuli, we recorded multi-unit and single-unit activity from the zebra finch auditory forebrain while presenting rare repeated stimuli after regular alternating stimuli (alternating oddball experiment) or rare deviant among multiple different common stimuli (context oddball experiment). The alternating oddball experiment showed that neurons were sensitive to rare repetitions in regular alternations. In the absence of expectation, repetition suppresses neural responses to the 2nd stimulus in the repetition. When repetition violates expectation, neural responses to the 2nd stimulus in the repetition were stronger than expected. The context oddball experiment showed that a stimulus elicits stronger neural responses when it is presented infrequently as a deviant among multiple common stimuli. As the acoustic differences between deviant and common stimuli increase, the response enhancement also increases. These results together showed that neural encoding of a stimulus depends not only on the acoustic features of the stimulus but also on the preceding stimuli and the transition patterns between them. These results also imply that the classical oddball effect may result from a combination of repetition suppression and deviance enhancement. Classification analyses showed that the difficulties in decoding the stimulus responsible for the neural responses differed for deviants in different experimental conditions. These findings suggest that learning transition patterns and detecting deviants in natural sequences may depend on a hierarchy of neural mechanisms, which may be involved in more complex forms of auditory processing that depend on the transition patterns between stimuli, such as speech processing.

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.

Striatal action-value neurons reconsidered

It is generally believed that during economic decisions, striatal neurons represent the values associated with different actions. This hypothesis is based on studies, in which the activity of striatal neurons was measured while the subject was learning to prefer the more rewarding action. Here we show that these publications are subject to at least one of two critical confounds. First, we show that even weak temporal correlations in the neuronal data may result in an erroneous identification of action-value representations. Second, we show that experiments and analyses designed to dissociate action-value representation from the representation of other decision variables cannot do so. We suggest solutions to identifying action-value representation that are not subject to these confounds. Applying one solution to previously identified action-value neurons in the basal ganglia we fail to detect action-value representations. We conclude that the claim that striatal neurons encode action-values must await new experiments and analyses.

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.

Familiar But Unexpected: Effects of Sound Context Statistics on Auditory Responses in the Songbird Forebrain

Rapid discrimination of salient acoustic signals in the noisy natural environment may depend, not only on specific stimulus features, but also on previous experience that generates expectations about upcoming events. We studied the neural correlates of expectation in the songbird forebrain by using natural vocalizations as stimuli and manipulating the category and familiarity of context sounds. In our paradigm, we recorded bilaterally from auditory neurons in awake adult male zebra finches with multiple microelectrodes during repeated playback of a conspecific song, followed by further playback of this test song in different interleaved sequences with other conspecific or heterospecific songs. Significant enhancement in the auditory response to the test song was seen when its acoustic features differed from the statistical distribution of context song features, but not when it shared the same distribution. Enhancement was also seen when the time of occurrence of the test song was uncertain. These results show that auditory forebrain responses in awake animals in the passive hearing state are modulated dynamically by previous auditory experience and imply that the auditory system can identify the category of a sound based on the global features of the acoustic context. Furthermore, this probability-dependent enhancement in responses to surprising stimuli is independent of stimulus-specific adaptation, which tracks familiarity, suggesting that the two processes could coexist in auditory processing. These findings establish the songbird as a model system for studying these phenomena and contribute to our understanding of statistical learning and the origin of human ERP phenomena to unexpected stimuli.SIGNIFICANCE STATEMENT Traditional auditory neurophysiology has mapped acoustic features of sounds to the response properties of neurons; however, growing evidence suggests that neurons can also encode the probability of sounds. We recorded responses of songbird auditory neurons in a novel paradigm that presented a familiar test stimulus in a sequence with similar or dissimilar sounds. The responses encode, not only stimulus familiarity, but also the expectation for a class of sounds based on the recent statistics of varying sounds in the acoustic context. Our approach thus provides a model system that uses a controlled stimulus paradigm to understand the mechanisms by which top-down processes (expectation and memory) and bottom-up processes (based on stimulus features) interact in sensory coding.

Detection of Tones Masked by Fluctuating Noise in Rat Auditory Cortex

Sounds in natural settings always appear over a noisy background. The masked threshold of a pure tone in white noise (the lowest sound level at which the tone can be detected in the presence of masking noise) is largely determined by energy masking in the peripheral auditory system: when the signal-to-noise ratio within a frequency band centered at the target tone frequency is large enough, the tone can be detected. However, when additional information is supplied to the auditory system, for example in the presence of slow and coherent modulations of a broadband masker (often found in natural sounds), masked thresholds can be reduced substantially below the values expected from pure energy masking. Here, we used intracellular recordings in vivo in rat auditory cortex in order to study neuronal responses to pure tones masked by broadband maskers and amplitude-modulated broadband maskers. When tones were embedded in amplitude-modulated noise, detection thresholds were substantially lower than when embedded in unmodulated noise. The main cue for tone detection in modulated noise consisted of the suppression of the locking of the neuronal responses to the amplitude modulation of the noise by low-level tones.

Stimulus-specific adaptation in a recurrent network model of primary auditory cortex

Stimulus-specific adaptation (SSA) occurs when neurons decrease their responses to frequently-presented (standard) stimuli but not, or not as much, to other, rare (deviant) stimuli. SSA is present in all mammalian species in which it has been tested as well as in birds. SSA confers short-term memory to neuronal responses, and may lie upstream of the generation of mismatch negativity (MMN), an important human event-related potential. Previously published models of SSA mostly rely on synaptic depression of the feedforward, thalamocortical input. Here we study SSA in a recurrent neural network model of primary auditory cortex. When the recurrent, intracortical synapses display synaptic depression, the network generates population spikes (PSs). SSA occurs in this network when deviants elicit a PS but standards do not, and we demarcate the regions in parameter space that allow SSA. While SSA based on PSs does not require feedforward depression, we identify feedforward depression as a mechanism for expanding the range of parameters that support SSA. We provide predictions for experiments that could help differentiate between SSA due to synaptic depression of feedforward connections and SSA due to synaptic depression of recurrent connections. Similar to experimental data, the magnitude of SSA in the model depends on the frequency difference between deviant and standard, probability of the deviant, inter-stimulus interval and input amplitude. In contrast to models based on feedforward depression, our model shows true deviance sensitivity as found in experiments.

Stimulus Phase Locking of Cortical Oscillations for Rhythmic Tone Sequences in Rats

Humans can rapidly detect regular patterns (i.e., within few cycles) without any special attention to the acoustic environment. This suggests that human sensory systems are equipped with a powerful mechanism for automatically predicting forthcoming stimuli to detect regularity. It has recently been hypothesized that the neural basis of sensory predictions exists for not only what happens (predictive coding) but also when a particular stimulus occurs (predictive timing). Here, we hypothesize that the phases of neural oscillations are critical in predictive timing, and these oscillations are modulated in a band-specific manner when acoustic patterns become predictable, i.e., regular. A high-density microelectrode array (10 × 10 within 4 × 4 mm²) was used to characterize spatial patterns of band-specific oscillations when a random-tone sequence was switched to a regular-tone sequence. Increasing the regularity of the tone sequence enhanced phase locking in a band-specific manner, notwithstanding the type of the regular sound pattern. Gamma-band phase locking increased immediately after the transition from random to regular sequences, while beta-band phase locking gradually evolved with time after the transition. The amplitude of the tone-evoked response, in contrast, increased with frequency separation with respect to the prior tone, suggesting that the evoked-response amplitude encodes sequence information on a local scale, i.e., the local order of tones. The phase locking modulation spread widely over the auditory cortex, while the amplitude modulation was confined around the activation foci. Thus, our data suggest that oscillatory phase plays a more important role than amplitude in the neuronal detection of tone sequence regularity, which is closely related to predictive timing. Furthermore, band-specific contributions may support recent theories that gamma oscillations encode bottom-up prediction errors, whereas beta oscillations are involved in top-down prediction.

Rapid Sensory Adaptation Redux: A Circuit Perspective

Adaptation is fundamental to life. All organisms adapt over timescales that span from evolution to generations and lifetimes to moment-by-moment interactions. The nervous system is particularly adept at rapidly adapting to change, and this in fact may be one of its fundamental principles of organization and function. Rapid forms of sensory adaptation have been well documented across all sensory modalities in a wide range of organisms, yet we do not have a comprehensive understanding of the adaptive cellular mechanisms that ultimately give rise to the corresponding percepts, due in part to the complexity of the circuitry. In this Perspective, we aim to build links between adaptation at multiple scales of neural circuitry by investigating the differential adaptation across brain regions and sub-regions and across specific cell types, for which the explosion of modern tools has just begun to enable. This investigation points to a set of challenges for the field to link functional observations to adaptive properties of the neural circuit that ultimately underlie percepts.

Distinct Spatiotemporal Response Properties of Excitatory Versus Inhibitory Neurons in the Mouse Auditory Cortex

In the auditory system, early neural stations such as brain stem are characterized by strict tonotopy, which is used to deconstruct sounds to their basic frequencies. But higher along the auditory hierarchy, as early as primary auditory cortex (A1), tonotopy starts breaking down at local circuits. Here, we studied the response properties of both excitatory and inhibitory neurons in the auditory cortex of anesthetized mice. We used in vivo two photon-targeted cell-attached recordings from identified parvalbumin-positive neurons (PVNs) and their excitatory pyramidal neighbors (PyrNs). We show that PyrNs are locally heterogeneous as characterized by diverse best frequencies, pairwise signal correlations, and response timing. In marked contrast, neighboring PVNs exhibited homogenous response properties in pairwise signal correlations and temporal responses. The distinct physiological microarchitecture of different cell types is maintained qualitatively in response to natural sounds. Excitatory heterogeneity and inhibitory homogeneity within the same circuit suggest different roles for each population in coding natural stimuli.

The Representation of Prediction Error in Auditory Cortex

To survive, organisms must extract information from the past that is relevant for their future. How this process is expressed at the neural level remains unclear. We address this problem by developing a novel approach from first principles. We show here how to generate low-complexity representations of the past that produce optimal predictions of future events. We then illustrate this framework by studying the coding of ‘oddball’ sequences in auditory cortex. We find that for many neurons in primary auditory cortex, trial-by-trial fluctuations of neuronal responses correlate with the theoretical prediction error calculated from the short-term past of the stimulation sequence, under constraints on the complexity of the representation of this past sequence. In some neurons, the effect of prediction error accounted for more than 50% of response variability. Reliable predictions often depended on a representation of the sequence of the last ten or more stimuli, although the representation kept only few details of that sequence.

A crucial aspect of all life is the ability to use past events in order to guide future behavior. To do that, creatures need the ability to predict future events. Indeed, predictability has been shown to affect neuronal responses in many animals and under many conditions. Clearly, the quality of predictions should depend on the amount and detail of the past information used to generate them. Here, by using a basic principle from information theory, we show how to derive explicitly the tradeoff between quality of prediction and complexity of the representation of past information. We then apply these ideas to a concrete case–neuronal responses recorded in auditory cortex during the presentation of oddball sequences, consisting of two tones with varying probabilities. We show that the neuronal responses fit quantitatively the prediction errors of optimal predictors derived from our theory, and use that result in order to deduce the properties of the representations of the past in the auditory system. We conclude that these memory representations have surprisingly long duration (10 stimuli back or more), but keep relatively little detail about this past. Our theory can be applied widely to other sensory systems.

Neurons in the inferior colliculus of the rat show stimulus-specific adaptation for frequency, but not for intensity

Electrophysiological and psychophysical responses to a low-intensity probe sound tend to be suppressed by a preceding high-intensity adaptor sound. Nevertheless, rare low-intensity deviant sounds presented among frequent high-intensity standard sounds in an intensity oddball paradigm can elicit an electroencephalographic mismatch negativity (MMN) response. This has been taken to suggest that the MMN is a correlate of true change or “deviance” detection. A key question is where in the ascending auditory pathway true deviance sensitivity first emerges. Here, we addressed this question by measuring low-intensity deviant responses from single units in the inferior colliculus (IC) of anesthetized rats. If the IC exhibits true deviance sensitivity to intensity, IC neurons should show enhanced responses to low-intensity deviant sounds presented among high-intensity standards. Contrary to this prediction, deviant responses were only enhanced when the standards and deviants differed in frequency. The results could be explained with a model assuming that IC neurons integrate over multiple frequency-tuned channels and that adaptation occurs within each channel independently. We used an adaptation paradigm with multiple repeated adaptors to measure the tuning widths of these adaption channels in relation to the neurons’ overall tuning widths.

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

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

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

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

Specific Early and Late Oddball-Evoked Responses in Excitatory and Inhibitory Neurons of Mouse Auditory Cortex

A major challenge for sensory processing in the brain is considering stimulus context, such as stimulus probability, which may be relevant for survival. Excitatory neurons in auditory cortex, for example, adapt to repetitive tones in a stimulus-specific manner without fully generalizing to a low-probability deviant tone ("oddball") that breaks the preceding regularity. Whether such stimulus-specific adaptation (SSA) also prevails in inhibitory neurons and how it might relate to deviance detection remains elusive. We obtained whole-cell recordings from excitatory neurons and somatostatin- and parvalbumin-positive GABAergic interneurons in layer 2/3 of mouse auditory cortex and measured tone-evoked membrane potential responses. All cell types displayed SSA of fast ("early") subthreshold and suprathreshold responses with oddball tones of a deviant frequency eliciting enlarged responses compared with adapted standards. SSA was especially strong when oddball frequency matched neuronal preference. In addition, we identified a slower "late" response component (200-400 ms after tone onset), most clearly in excitatory and parvalbumin-positive neurons, which also displayed SSA. For excitatory neurons, this late component reflected genuine deviance detection. Moreover, intracellular blockade of NMDA receptors reduced early and late responses in excitatory but not parvalbumin-positive neurons. The late component in excitatory neurons thus shares time course, deviance detection, and pharmacological features with the deviant-evoked event-related potential known as mismatch negativity (MMN) and provides a potential link between neuronal SSA and MMN. In summary, our results suggest a two-phase cortical activation upon oddball stimulation, with oddball tones first reactivating the adapted auditory cortex circuitry and subsequently triggering delayed reverberating network activity. Significance statement: Understanding how the brain encodes sensory context in addition to stimulus feature has been a main focus in neuroscience. Using in vivo targeted whole-cell recordings from excitatory and inhibitory neurons of mouse primary auditory cortex, we report two temporally distinct components of membrane potential responses encoding oddball tones that break stimulus regularity. Both components display stimulus-specific adaptation upon oddball paradigm stimulation in the three recorded cell types. The late response component, in particular, carries signatures of genuine deviance detection. In excitatory but not parvalbumin-positive inhibitory neurons, both early and late components depend on NMDA receptor-signaling. Our work proposes a potential neuronal substrate of a known deviant-evoked event-related potential, which is of fundamental significance in basic and clinical neuroscience.

Synaptic plasticity as a cortical coding scheme

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

Frequency-specific adaptation and its underlying circuit model in the auditory midbrain

Receptive fields of sensory neurons are considered to be dynamic and depend on the stimulus history. In the auditory system, evidence of dynamic frequency-receptive fields has been found following stimulus-specific adaptation (SSA). However, the underlying mechanism and circuitry of SSA have not been fully elucidated. Here, we studied how frequency-receptive fields of neurons in rat inferior colliculus (IC) changed when exposed to a biased tone sequence. Pure tone with one specific frequency (adaptor) was presented markedly more often than others. The adapted tuning was compared with the original tuning measured with an unbiased sequence. We found inhomogeneous changes in frequency tuning in IC, exhibiting a center-surround pattern with respect to the neuron's best frequency. Central adaptors elicited strong suppressive and repulsive changes while flank adaptors induced facilitative and attractive changes. Moreover, we proposed a two-layer model of the underlying network, which not only reproduced the adaptive changes in the receptive fields but also predicted novelty responses to oddball sequences. These results suggest that frequency-specific adaptation in auditory midbrain can be accounted for by an adapted frequency channel and its lateral spreading of adaptation, which shed light on the organization of the underlying circuitry.

Sensitivity of rat inferior colliculus neurons to frequency distributions

Stimulus-specific adaptation refers to a neural response reduction to a repeated stimulus that does not generalize to other stimuli. However, stimulus-specific adaptation appears to be influenced by additional factors. For example, the statistical distribution of tone frequencies has recently been shown to dynamically alter stimulus-specific adaptation in human auditory cortex. The present study investigated whether statistical stimulus distributions also affect stimulus-specific adaptation at an earlier stage of the auditory hierarchy. Neural spiking activity and local field potentials were recorded from inferior colliculus neurons of rats while tones were presented in oddball sequences that formed two different statistical contexts. Each sequence consisted of a repeatedly presented tone (standard) and three rare deviants of different magnitudes (small, moderate, large spectral change). The critical manipulation was the relative probability with which large spectral changes occurred. In one context the probability was high (relative to all deviants), while it was low in the other context. We observed larger responses for deviants compared with standards, confirming previous reports of increased response adaptation for frequently presented tones. Importantly, the statistical context in which tones were presented strongly modulated stimulus-specific adaptation. Physically and probabilistically identical stimuli (moderate deviants) in the two statistical contexts elicited different response magnitudes consistent with neural gain changes and thus neural sensitivity adjustments induced by the spectral range of a stimulus distribution. The data show that already at the level of the inferior colliculus stimulus-specific adaptation is dynamically altered by the statistical context in which stimuli occur.

The cortical modulation of stimulus-specific adaptation in the auditory midbrain and thalamus: a potential neuronal correlate for predictive coding

To follow an ever-changing auditory scene, the auditory brain is continuously creating a representation of the past to form expectations about the future. Unexpected events will produce an error in the predictions that should “trigger” the network’s response. Indeed, neurons in the auditory midbrain, thalamus and cortex, respond to rarely occurring sounds while adapting to frequently repeated ones, i.e., they exhibit stimulus specific adaptation (SSA). SSA cannot be explained solely by intrinsic membrane properties, but likely involves the participation of the network. Thus, SSA is envisaged as a high order form of adaptation that requires the influence of cortical areas. However, present research supports the hypothesis that SSA, at least in its simplest form (i.e., to frequency deviants), can be transmitted in a bottom-up manner through the auditory pathway. Here, we briefly review the underlying neuroanatomy of the corticofugal projections before discussing state of the art studies which demonstrate that SSA present in the medial geniculate body (MGB) and inferior colliculus (IC) is not inherited from the cortex but can be modulated by the cortex via the corticofugal pathways. By modulating the gain of neurons in the thalamus and midbrain, the auditory cortex (AC) would refine SSA subcortically, preventing irrelevant information from reaching the cortex.

Auditory cortical processing in real-world listening: the auditory system going real

The auditory sense of humans transforms intrinsically senseless pressure waveforms into spectacularly rich perceptual phenomena: the music of Bach or the Beatles, the poetry of Li Bai or Omar Khayyam, or more prosaically the sense of the world filled with objects emitting sounds that is so important for those of us lucky enough to have hearing. Whereas the early representations of sounds in the auditory system are based on their physical structure, higher auditory centers are thought to represent sounds in terms of their perceptual attributes. In this symposium, we will illustrate the current research into this process, using four case studies. We will illustrate how the spectral and temporal properties of sounds are used to bind together, segregate, categorize, and interpret sound patterns on their way to acquire meaning, with important lessons to other sensory systems as well.

Statistical context shapes stimulus-specific adaptation in human auditory cortex

Stimulus-specific adaptation is the phenomenon whereby neural response magnitude decreases with repeated stimulation. Inconsistencies between recent nonhuman animal recordings and computational modeling suggest dynamic influences on stimulus-specific adaptation. The present human electroencephalography (EEG) study investigates the potential role of statistical context in dynamically modulating stimulus-specific adaptation by examining the auditory cortex-generated N1 and P2 components. As in previous studies of stimulus-specific adaptation, listeners were presented with oddball sequences in which the presentation of a repeated tone was infrequently interrupted by rare spectral changes taking on three different magnitudes. Critically, the statistical context varied with respect to the probability of small versus large spectral changes within oddball sequences (half of the time a small change was most probable; in the other half a large change was most probable). We observed larger N1 and P2 amplitudes (i.e., release from adaptation) for all spectral changes in the small-change compared with the large-change statistical context. The increase in response magnitude also held for responses to tones presented with high probability, indicating that statistical adaptation can overrule stimulus probability per se in its influence on neural responses. Computational modeling showed that the degree of coadaptation in auditory cortex changed depending on the statistical context, which in turn affected stimulus-specific adaptation. Thus the present data demonstrate that stimulus-specific adaptation in human auditory cortex critically depends on statistical context. Finally, the present results challenge the implicit assumption of stationarity of neural response magnitudes that governs the practice of isolating established deviant-detection responses such as the mismatch negativity.

Stimulus-specific adaptation at the synapse level in vitro

Stimulus-specific adaptation (SSA) is observed in many brain regions in humans and animals. SSA of cortical neurons has been proposed to accumulate through relays in ascending pathways. Here, we examined SSA at the synapse level using whole-cell patch-clamp recordings of primary cultured cortical neurons of the rat. First, we found that cultured neurons had high firing capability with 100-Hz current injection. However, neuron firing started to adapt to repeated electrically activated synaptic inputs at 10 Hz. Next, to activate different dendritic inputs, electrical stimulations were spatially separated. Cultured neurons showed similar SSA properties in the oddball stimulation paradigm compared to those reported in vivo. Single neurons responded preferentially to a deviant stimulus over repeated, standard stimuli considering both synapse-driven spikes and excitatory postsynaptic currents (EPSCs). Compared with two closely placed stimulating electrodes that activated highly overlapping dendritic fields, two separately placed electrodes that activated less overlapping dendritic fields elicited greater SSA. Finally, we used glutamate puffing to directly activate postsynaptic glutamate receptors. Neurons showed SSA to two separately placed puffs repeated at 10 Hz. Compared with EPSCs, GABAa receptor-mediated inhibitory postsynaptic currents showed weaker SSA. Heterogeneity of the synaptic inputs was critical for producing SSA, with glutamate receptor desensitization participating in the process. Our findings suggest that postsynaptic fatigue contributes largely to SSA at low frequencies.

Neurons in macaque inferior temporal cortex show no surprise response to deviants in visual oddball sequences

Many studies measured neural responses in oddball paradigms, showing a different response to the same stimulus when presented with a low (deviant) compared with a high probability (standard) in a sequence. Such a differential response is manifested in event-related potential studies as the mismatch negativity (MMN) and has been observed in several sensory modalities, including vision. Other studies showed that stimulus repetition suppresses the neural response. It has been suggested that this adaptation effect underlies the smaller responses to the standard compared with the deviant stimulus in oddball sequences. However, the MMN may also reflect the violation of a prediction based on the sequence of standards, i.e., a surprise response. We examined the presence of a surprise response to deviants in visual oddball sequences in macaque (Macaca mulatta) inferior temporal (IT) cortex, a higher-order cortical area. In agreement with visual MMN studies, single-unit IT responses were greater for the deviant than for the standard stimuli. However, single IT neurons showed no greater response to the deviant stimulus in the oddball sequence than to the same stimulus presented with the same probability in a sequence that consisted of many stimuli. LFPs also showed no evidence of a surprise response. These data suggest that stimulus-specific adaptation, without a surprise-related boost of activity to the deviant, underlies the responses in visual oddball sequences even in higher visual cortex. Furthermore, we show that for IT neurons such adaptive mechanisms take into account a relatively short stimulus history, with weaker effects at longer time scales.