Complementary control of sensory adaptation by two types of cortical interneurons

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.

Multiple Mechanistically Distinct Timescales of Neocortical Plasticity Occur During Habituation

Recognizing familiar but innocuous stimuli and suppressing behavioral response to those stimuli are critical steps in dedicating cognitive resources to significant elements of the environment. Recent work in the visual system has uncovered key neocortical mechanisms of this familiarity that emerges over days. Specifically, exposure to phase-reversing gratings of a specific orientation causes long-lasting stimulus-selective response potentiation (SRP) in layer 4 of mouse primary visual cortex (V1) as the animal's behavioral responses are reduced through habituation. This plasticity and concomitant learning require the NMDA receptor and the activity of parvalbumin-expressing (PV+) inhibitory neurons. Changes over the course of seconds and minutes have been less well studied in this paradigm, so we have here characterized cortical plasticity occurring over seconds and minutes, as well as days, to identify separable forms of plasticity accompanying familiarity. In addition, we show evidence of interactions between plasticity over these different timescales and reveal key mechanistic differences. Layer 4 visual-evoked potentials (VEPs) are potentiated over days, and they are depressed over minutes, even though both forms of plasticity coincide with significant reductions in behavioral response. Adaptation, classically described as a progressive reduction in synaptic or neural activity, also occurs over the course of seconds, but appears mechanistically separable over a second as compared to tens of seconds. Interestingly, these short-term forms of adaptation are modulated by long-term familiarity, such that they occur for novel but not highly familiar stimuli. Genetic knock-down of NMDA receptors within V1 prevents all forms of plasticity while, importantly, the modulation of short-term adaptation by long-term familiarity is gated by PV+ interneurons. Our findings demonstrate that different timescales of adaptation/habituation have divergent but overlapping mechanisms, providing new insight into how the brain is modified by experience to encode familiarity.

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.

Contributions of Distinct Auditory Cortical Inhibitory Neuron Types to the Detection of Sounds in Background Noise

The ability to separate background noise from relevant acoustic signals is essential for appropriate sound-driven behavior in natural environments. Examples of this separation are apparent in the auditory system, where neural responses to behaviorally relevant stimuli become increasingly noise invariant along the ascending auditory pathway. However, the mechanisms that underlie this reduction in responses to background noise are not well understood. To address this gap in knowledge, we first evaluated the effects of auditory cortical inactivation on mice of both sexes trained to perform a simple auditory signal-in-noise detection task and found that outputs from the auditory cortex are important for the detection of auditory stimuli in noisy environments. Next, we evaluated the contributions of the two most common cortical inhibitory cell types, parvalbumin-expressing (PV+) and somatostatin-expressing (SOM+) interneurons, to the perception of masked auditory stimuli. We found that inactivation of either PV+ or SOM+ cells resulted in a reduction in the ability of mice to determine the presence of auditory stimuli masked by noise. These results indicate that a disruption of auditory cortical network dynamics by either of these two types of inhibitory cells is sufficient to impair the ability to separate acoustic signals from noise.

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

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

Neural Substrates and Models of Omission Responses and Predictive Processes

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

Novel stimuli evoke excess activity in the mouse primary visual cortex

Rapid detection and processing of stimulus novelty are key elements of adaptive behavior. Predictive coding theories postulate that novel stimuli should be encoded differently from familiar stimuli. Here, we show that the majority of neurons in layer 2/3 of the mouse primary visual cortex exhibit a significant excess response to novel visual stimuli. The distinction between novel and familiar images developed rapidly, requiring only a few repeated presentations. We show that this phenomenon can be described by a model of cascading adaptation. This ubiquitous mechanism makes it likely that similar computations could be carried out in many brain areas.

To explore how neural circuits represent novel versus familiar inputs, we presented mice with repeated sets of images with novel images sparsely substituted. Using two-photon calcium imaging to record from layer 2/3 neurons in the mouse primary visual cortex, we found that novel images evoked excess activity in the majority of neurons. This novelty response rapidly emerged, arising with a time constant of 2.6 ± 0.9 s. When a new image set was repeatedly presented, a majority of neurons had similarly elevated activity for the first few presentations, which decayed to steady state with a time constant of 1.4 ± 0.4 s. When we increased the number of images in the set, the novelty response’s amplitude decreased, defining a capacity to store ∼15 familiar images under our conditions. These results could be explained quantitatively using an adaptive subunit model in which presynaptic neurons have individual tuning and gain control. This result shows that local neural circuits can create different representations for novel versus familiar inputs using generic, widely available mechanisms.

Task-induced modulations of neuronal activity along the auditory pathway

Sensory processing varies depending on behavioral context. Here, we ask how task engagement modulates neurons in the auditory system. We train mice in a simple tone-detection task and compare their neuronal activity during passive hearing and active listening. Electrophysiological extracellular recordings in the inferior colliculus, medial geniculate body, primary auditory cortex, and anterior auditory field reveal widespread modulations across all regions and cortical layers and in both putative regular- and fast-spiking cortical neurons. Clustering analysis unveils ten distinct modulation patterns that can either enhance or suppress neuronal activity. Task engagement changes the tone-onset response in most neurons. Such modulations first emerge in subcortical areas, ruling out cortical feedback as the only mechanism underlying subcortical modulations. Half the neurons additionally display late modulations associated with licking, arousal, or reward. Our results reveal the presence of functionally distinct subclasses of neurons, differentially sensitive to specific task-related variables but anatomically distributed along the auditory pathway.

Inhibition in the auditory cortex

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

Altered Response Dynamics and Increased Population Correlation to Tonal Stimuli Embedded in Noise in Aging Auditory Cortex

Age-related hearing loss (presbycusis) is a chronic health condition that affects one-third of the world population. One hallmark of presbycusis is a difficulty hearing in noisy environments. Presbycusis can be separated into two components: alterations of peripheral mechanotransduction of sound in the cochlea and central alterations of auditory processing areas of the brain. Although the effects of the aging cochlea in hearing loss have been well studied, the role of the aging brain in hearing loss is less well understood. Therefore, to examine how age-related central processing changes affect hearing in noisy environments, we used a mouse model (Thy1-GCaMP6s X CBA) that has excellent peripheral hearing in old age. We used in vivo two-photon Ca2+ imaging to measure the responses of neuronal populations in auditory cortex (ACtx) of adult (2-6 months, nine male, six female, 4180 neurons) and aging mice (15-17 months, six male, three female, 1055 neurons) while listening to tones in noisy backgrounds. We found that ACtx neurons in aging mice showed larger responses to tones and have less suppressed responses consistent with reduced inhibition. Aging neurons also showed less sensitivity to temporal changes. Population analysis showed that neurons in aging mice showed higher pairwise activity correlations and showed a reduced diversity in responses to sound stimuli. Using neural decoding techniques, we show a loss of information in neuronal populations in the aging brain. Thus, aging not only affects the responses of single neurons but also affects how these neurons jointly represent stimuli.SIGNIFICANCE STATEMENT Aging results in hearing deficits particularly under challenging listening conditions. We show that auditory cortex contains distinct subpopulations of excitatory neurons that preferentially encode different stimulus features and that aging selectively reduces certain subpopulations. We also show that aging increases correlated activity between neurons and thereby reduces the response diversity in auditory cortex. The loss of population response diversity leads to a decrease of stimulus information and deficits in sound encoding, especially in noisy backgrounds. Future work determining the identities of circuits affected by aging could provide new targets for therapeutic strategies.

Sensory processing dysregulations as reliable translational biomarkers in SYNGAP1 haploinsufficiency

Amongst the numerous genes associated with intellectual disability, SYNGAP1 stands out for its frequency and penetrance of loss-of-function variants found in patients, as well as the wide range of co-morbid disorders associated with its mutation. Most studies exploring the pathophysiological alterations caused by Syngap1 haploinsufficiency in mouse models have focused on cognitive problems and epilepsy, however whether and to what extent sensory perception and processing are altered by Syngap1 haploinsufficiency is less clear. By performing EEG recordings in awake mice, we identified specific alterations in multiple aspects of auditory and visual processing, including increased baseline gamma oscillation power, increased theta/gamma phase amplitude coupling following stimulus presentation and abnormal neural entrainment in response to different sensory modality-specific frequencies. We also report lack of habituation to repetitive auditory stimuli and abnormal deviant sound detection. Interestingly, we found that most of these alterations are present in human patients as well, thus making them strong candidates as translational biomarkers of sensory-processing alterations associated with SYNGAP1/Syngap1 haploinsufficiency.

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.

Contribution of Interneuron Subtype-Specific GABAergic Signaling to Emergent Sensory Processing in Mouse Somatosensory Whisker Barrel Cortex

Mammalian neocortex is important for conscious processing of sensory information with balanced glutamatergic and GABAergic signaling fundamental to this function. Yet little is known about how this interaction arises despite increasing insight into early GABAergic interneuron (IN) circuits. To study this, we assessed the contribution of specific INs to the development of sensory processing in the mouse whisker barrel cortex, specifically the role of INs in early speed coding and sensory adaptation. In wild-type animals, both speed processing and adaptation were present as early as the layer 4 critical period of plasticity and showed refinement over the period leading to active whisking onset. To test the contribution of IN subtypes, we conditionally silenced action-potential-dependent GABA release in either somatostatin (SST) or vasoactive intestinal peptide (VIP) INs. These genetic manipulations influenced both spontaneous and sensory-evoked cortical activity in an age- and layer-dependent manner. Silencing SST + INs reduced early spontaneous activity and abolished facilitation in sensory adaptation observed in control pups. In contrast, VIP + IN silencing had an effect towards the onset of active whisking. Silencing either IN subtype had no effect on speed coding. Our results show that these IN subtypes contribute to early sensory processing over the first few postnatal weeks.

Shorter Contextual Timescale Rather Than Memory Deficit in Aging

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

Cholinergic modulation of sensory processing in awake mouse cortex

Cholinergic modulation of brain activity is fundamental for awareness and conscious sensorimotor behaviours, but deciphering the timing and significance of acetylcholine actions for these behaviours is challenging. The widespread nature of cholinergic projections to the cortex means that new insights require access to specific neuronal populations, and on a time-scale that matches behaviourally relevant cholinergic actions. Here, we use fast, voltage imaging of L2/3 cortical pyramidal neurons exclusively expressing the genetically-encoded voltage indicator Butterfly 1.2, in awake, head-fixed mice, receiving sensory stimulation, whilst manipulating the cholinergic system. Altering muscarinic acetylcholine function re-shaped sensory-evoked fast depolarisation and subsequent slow hyperpolarisation of L2/3 pyramidal neurons. A consequence of this re-shaping was disrupted adaptation of the sensory-evoked responses, suggesting a critical role for acetylcholine during sensory discrimination behaviour. Our findings provide new insights into how the cortex processes sensory information and how loss of acetylcholine, for example in Alzheimer's Disease, disrupts sensory behaviours.

Development, Diversity, and Death of MGE-Derived Cortical Interneurons

In the mammalian brain, cortical interneurons (INs) are a highly diverse group of cells. A key neurophysiological question concerns how each class of INs contributes to cortical circuit function and whether specific roles can be attributed to a selective cell type. To address this question, researchers are integrating knowledge derived from transcriptomic, histological, electrophysiological, developmental, and functional experiments to extensively characterise the different classes of INs. Our hope is that such knowledge permits the selective targeting of cell types for therapeutic endeavours. This review will focus on two of the main types of INs, namely the parvalbumin (PV⁺) or somatostatin (SOM⁺)-containing cells, and summarise the research to date on these classes.

Differential Excitability of PV and SST Neurons Results in Distinct Functional Roles in Inhibition Stabilization of Up States

Up states are the best studied example of an emergent neural dynamic regime. Computational models based on a single class of inhibitory neurons indicate that Up states reflect bistable dynamic systems in which positive feedback is stabilized by strong inhibition and predict a paradoxical effect in which increased drive to inhibitory neurons results in decreased inhibitory activity. To date, however, computational models have not incorporated empirically defined properties of parvalbumin (PV) and somatostatin (SST) neurons. Here we first experimentally characterized the frequency-current (F-I) curves of pyramidal (Pyr), PV, and SST neurons from mice of either sex, and confirmed a sharp difference between the threshold and slopes of PV and SST neurons. The empirically defined F-I curves were incorporated into a three-population computational model that simulated the empirically derived firing rates of pyramidal, PV, and SST neurons. Simulations revealed that the intrinsic properties were sufficient to predict that PV neurons are primarily responsible for generating the nontrivial fixed points representing Up states. Simulations and analytical methods demonstrated that while the paradoxical effect is not obligatory in a model with two classes of inhibitory neurons, it is present in most regimes. Finally, experimental tests validated predictions of the model that the Pyr ↔ PV inhibitory loop is stronger than the Pyr ↔ SST loop.SIGNIFICANCE STATEMENT Many cortical computations, such as working memory, rely on the local recurrent excitatory connections that define cortical circuit motifs. Up states are among the best studied examples of neural dynamic regimes that rely on recurrent excitatory excitation. However, this positive feedback must be held in check by inhibition. To address the relative contribution of PV and SST neurons, we characterized the intrinsic input-output differences between these classes of inhibitory neurons and, using experimental and theoretical methods, show that the higher threshold and gain of PV leads to a dominant role in network stabilization.

A Role for Somatostatin-Positive Interneurons in Neuro-Oscillatory and Information Processing Deficits in Schizophrenia

Alterations in neocortical GABAergic interneurons (INs) have been affiliated with neuropsychiatric diseases, including schizophrenia (SZ). Significant progress has been made linking the function of a specific subtype of GABAergic cells, parvalbumin (PV) positive INs, to altered gamma-band oscillations, which, in turn, underlie perceptual and feedforward information processing in cortical circuits. Here, we review a smaller but growing volume of literature focusing on a separate subtype of neocortical GABAergic INs, somatostatin (SST) positive INs. Despite sharing similar neurodevelopmental origins, SSTs exhibit distinct morphology and physiology from PVs. Like PVs, SSTs are altered in postmortem brain samples from multiple neocortical regions in SZ, although basic and translational research into consequences of SST dysfunction has been relatively sparse. We highlight a growing body of work in rodents, which now indicates that SSTs may also underlie specific aspects of cortical circuit function, namely low-frequency oscillations, disinhibition, and mediation of cortico-cortical feedback. SSTs may thereby support the coordination of local cortical information processing with more global spatial, temporal, and behavioral context, including predictive coding and working memory. These functions are notably deficient in some cases of SZ, as well as other neuropsychiatric disorders, emphasizing the importance of focusing on SSTs in future translational studies. Finally, we highlight the challenges that remain, including subtypes within the SST class.

Hearing loss and brain plasticity: the hyperactivity phenomenon

Many aging adults experience some form of hearing problems that may arise from auditory peripheral damage. However, it has been increasingly acknowledged that hearing loss is not only a dysfunction of the auditory periphery but also results from changes within the entire auditory system, from periphery to cortex. Damage to the auditory periphery is associated with an increase in neural activity at various stages throughout the auditory pathway. Here, we review neurophysiological evidence of hyperactivity, auditory perceptual difficulties that may result from hyperactivity, and outline open conceptual and methodological questions related to the study of hyperactivity. We suggest that hyperactivity alters all aspects of hearing-including spectral, temporal, spatial hearing-and, in turn, impairs speech comprehension when background sound is present. By focusing on the perceptual consequences of hyperactivity and the potential challenges of investigating hyperactivity in humans, we hope to bring animal and human electrophysiologists closer together to better understand hearing problems in older adulthood.

Evaluating the evidence for expectation suppression in the visual system

Reports of expectation suppression have shaped the development of influential predictive coding-based theories of visual perception. However recent work has highlighted confounding factors that may mimic or inflate expectation suppression effects. In this review, we describe four confounds that are prevalent across experiments that tested for expectation suppression: effects of surprise, attention, stimulus repetition and adaptation, and stimulus novelty. With these confounds in mind we then critically review the evidence for expectation suppression across probabilistic cueing, statistical learning, oddball, action-outcome learning and apparent motion designs. We found evidence for expectation suppression within a specific subset of statistical learning designs that involved weeks of sequence learning prior to neural activity measurement. Across other experimental contexts, whereby stimulus appearance probabilities were learned within one or two testing sessions, there was inconsistent evidence for genuine expectation suppression. We discuss how an absence of expectation suppression could inform models of predictive processing, repetition suppression and perceptual decision-making. We also provide suggestions for designing experiments that may better test for expectation suppression in future work.

Cortical ensembles selective for context

Neural processing of sensory information is strongly influenced by context. For instance, cortical responses are reduced to predictable stimuli, while responses are increased to novel stimuli that deviate from contextual regularities. Such bidirectional modulation based on preceding sensory context is likely a critical component or manifestation of attention, learning, and behavior, yet how it arises in cortical circuits remains unclear. Using volumetric two-photon calcium imaging and local field potentials in primary visual cortex (V1) from awake mice presented with visual "oddball" paradigms, we identify both reductions and augmentations of stimulus-evoked responses depending, on whether the stimulus was redundant or deviant, respectively. Interestingly, deviance-augmented responses were limited to a specific subset of neurons mostly in supragranular layers. These deviance-detecting cells were spatially intermixed with other visually responsive neurons and were functionally correlated, forming a neuronal ensemble. Optogenetic suppression of prefrontal inputs to V1 reduced the contextual selectivity of deviance-detecting ensembles, demonstrating a causal role for top-down inputs. The presence of specialized context-selective ensembles in primary sensory cortex, modulated by higher cortical areas, provides a circuit substrate for the brain's construction and selection of prediction errors, computations which are key for survival and deficient in many psychiatric disorders.

Cochlear neural degeneration disrupts hearing in background noise by increasing auditory cortex internal noise

Correlational evidence in humans suggests that selective difficulties hearing in noisy, social settings may reflect premature auditory nerve degeneration. Here, we induced primary cochlear neural degeneration (CND) in adult mice and found direct behavioral evidence for selective detection deficits in background noise. To identify central determinants for this perceptual disorder, we tracked daily changes in ensembles of layer 2/3 auditory cortex parvalbumin-expressing inhibitory neurons and excitatory pyramidal neurons with chronic two-photon calcium imaging. CND induced distinct forms of plasticity in cortical excitatory and inhibitory neurons that culminated in net hyperactivity, increased neural gain, and reduced adaptation to background noise. Ensemble activity measured while mice detected targets in noise could accurately decode whether individual behavioral trials were hits or misses. After CND, random surges of hypercorrelated cortical activity occurring just before target onset reliably predicted impending detection failures, revealing a source of internal cortical noise underlying perceptual difficulties in external noise.

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

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

Diversity of Receptive Fields and Sideband Inhibition with Complex Thalamocortical and Intracortical Origin in L2/3 of Mouse Primary Auditory Cortex

Receptive fields of primary auditory cortex (A1) neurons show excitatory neuronal frequency preference and diverse inhibitory sidebands. While the frequency preferences of excitatory neurons in local A1 areas can be heterogeneous, those of inhibitory neurons are more homogeneous. To date, the diversity and the origin of inhibitory sidebands in local neuronal populations and the relation between local cellular frequency preference and inhibitory sidebands are unknown. To reveal both excitatory and inhibitory subfields, we presented two-tone and pure tone stimuli while imaging excitatory neurons (Thy1) and two types of inhibitory neurons (parvalbumin and somatostatin) in L2/3 of mice A1. We classified neurons into six classes based on frequency response area (FRA) shapes and sideband inhibition depended both on FRA shapes and cell types. Sideband inhibition showed higher local heterogeneity than frequency tuning, suggesting that sideband inhibition originates from diverse sources of local and distant neurons. Two-tone interactions depended on neuron subclasses with excitatory neurons showing the most nonlinearity. Onset and offset neurons showed dissimilar spectral integration, suggesting differing circuits processing sound onset and offset. These results suggest that excitatory neurons integrate complex and nonuniform inhibitory input. Thalamocortical terminals also exhibited sideband inhibition, but with different properties from those of cortical neurons. Thus, some components of sideband inhibition are inherited from thalamocortical inputs and are further modified by converging intracortical circuits. The combined heterogeneity of frequency tuning and diverse sideband inhibition facilitates complex spectral shape encoding and allows for rapid and extensive plasticity.SIGNIFICANCE STATEMENT Sensory systems recognize and differentiate between different stimuli through selectivity for different features. Sideband inhibition serves as an important mechanism to sharpen stimulus selectivity, but its cortical mechanisms are not entirely resolved. We imaged pyramidal neurons and two common classes of interneurons suggested to mediate sideband inhibition (parvalbumin and somatostatin positive) in the auditory cortex and inferred their inhibitory sidebands. We observed a higher degree of variability in the inhibitory sideband than in the local frequency tuning, which cannot be predicted from the relative high homogeneity of responses by inhibitory interneurons. This suggests that cortical sideband inhibition is nonuniform and likely results from a complex interplay between existing functional inhibition in the feedforward input and cortical refinement.

Complementary Effects of Adaptation and Gain Control on Sound Encoding in Primary Auditory Cortex

An important step toward understanding how the brain represents complex natural sounds is to develop accurate models of auditory coding by single neurons. A commonly used model is the linear-nonlinear spectro-temporal receptive field (STRF; LN model). The LN model accounts for many features of auditory tuning, but it cannot account for long-lasting effects of sensory context on sound-evoked activity. Two mechanisms that may support these contextual effects are short-term plasticity (STP) and contrast-dependent gain control (GC), which have inspired expanded versions of the LN model. Both models improve performance over the LN model, but they have never been compared directly. Thus, it is unclear whether they account for distinct processes or describe one phenomenon in different ways. To address this question, we recorded activity of neurons in primary auditory cortex (A1) of awake ferrets during presentation of natural sounds. We then fit models incorporating one nonlinear mechanism (GC or STP) or both (GC+STP) using this single dataset, and measured the correlation between the models' predictions and the recorded neural activity. Both the STP and GC models performed significantly better than the LN model, but the GC+STP model outperformed both individual models. We also quantified the equivalence of STP and GC model predictions and found only modest similarity. Consistent results were observed for a dataset collected in clean and noisy acoustic contexts. These results establish general methods for evaluating the equivalence of arbitrarily complex encoding models and suggest that the STP and GC models describe complementary processes in the auditory system.

Within- and between-hemifield generalization of repetition suppression in inferior temporal cortex

The decrease in response with stimulus repetition is a common property observed in many sensory brain areas. This repetition suppression (RS) is ubiquitous in neurons of macaque inferior temporal (IT) cortex, the end-stage of the ventral visual pathway. The neural mechanisms of RS in IT are still unclear, and one possibility is that it is inherited from areas upstream to IT that show also RS. Since neurons in IT have larger receptive fields compared with earlier visual areas, we examined the inheritance hypothesis by presenting adapter and test stimuli at widely different spatial locations along both vertical and horizontal meridians and across hemifields. RS was present for distances between adapter and test stimuli up to 22° and when the two stimuli were presented in different hemifields. Also, we examined the position tolerance of the stimulus selectivity of adaptation by comparing the responses to a test stimulus following the same (repetition trial) or a different (alternation trial) adapter at a position different from the test stimulus. Stimulus-selective adaptation was still present and consistently stronger in the later phase of the response for distances up to 18°. Finally, we observed stimulus-selective adaptation in repetition trials even without a measurable excitatory response to the adapter stimulus. To accommodate these and previous data, we propose that at least part of the stimulus-selective adaptation in IT is based on short-term plasticity mechanisms within IT and/or reflects top-down activity from areas downstream to IT.NEW & NOTEWORTHY Neurons in inferior temporal cortex reduce their response when stimuli are repeated. To assess whether this repetition suppression is inherited from upstream visual areas, we examined the extent of its spatial generalization. We observed stimulus-selective adaptation when adapter and test stimuli were presented at widely different spatial positions and in different hemifields. These data suggest that at least part of the repetition suppression originates within inferior temporal cortex and/or reflects feedback from downstream areas.

Differential Short-Term Plasticity of PV and SST Neurons Accounts for Adaptation and Facilitation of Cortical Neurons to Auditory Tones

Cortical responses to sensory stimuli are strongly modulated by temporal context. One of the best studied examples of such modulation is sensory adaptation. We first show that in response to repeated tones pyramidal (Pyr) neurons in male mouse auditory cortex (A1) exhibit facilitating and stable responses, in addition to adapting responses. To examine the potential mechanisms underlying these distinct temporal profiles, we developed a reduced spiking model of sensory cortical circuits that incorporated the signature short-term synaptic plasticity (STP) profiles of the inhibitory parvalbumin (PV) and somatostatin (SST) interneurons. The model accounted for all three temporal response profiles as the result of dynamic changes in excitatory/inhibitory balance produced by STP, primarily through shifts in the relative latency of Pyr and inhibitory neurons. Transition between the three response profiles was possible by changing the strength of the inhibitory PV→Pyr and SST→Pyr synapses. The model predicted that a unit's latency would be related to its temporal profile. Consistent with this prediction, the latency of stable units was significantly shorter than that of adapting and facilitating units. Furthermore, because of the history-dependence of STP the model generated a paradoxical prediction: that inactivation of inhibitory neurons during one tone would decrease the response of A1 neurons to a subsequent tone. Indeed, we observed that optogenetic inactivation of PV neurons during one tone counterintuitively decreased the spiking of Pyr neurons to a subsequent tone 400 ms later. These results provide evidence that STP is critical to temporal context-dependent responses in the sensory cortex.SIGNIFICANCE STATEMENT Our perception of speech and music depends strongly on temporal context, i.e., the significance of a stimulus depends on the preceding stimuli. Complementary neural mechanisms are needed to sometimes ignore repetitive stimuli (e.g., the tic of a clock) or detect meaningful repetition (e.g., consecutive tones in Morse code). We modeled a neural circuit that accounts for diverse experimentally-observed response profiles in auditory cortex (A1) neurons, based on known forms of short-term synaptic plasticity (STP). Whether the simulated circuit reduced, maintained, or enhanced its response to repeated tones depended on the relative dominance of two different types of inhibitory cells. The model made novel predictions that were experimentally validated. Results define an important role for STP in temporal context-dependent perception.

Inhibitory plasticity in layer 1 - dynamic gatekeeper of neocortical associations

Neocortical layer 1 is a major site of convergence for a variety of brain wide afferents carrying experience-dependent top-down information, which are integrated and processed in the apical tuft dendrites of pyramidal cells. Two types of local inhibitory interneurons, Martinotti cells and layer 1 interneurons, dominantly shape dendritic integration, and work from recent years has significantly advanced our understanding of the role of these interneurons in circuit plasticity and learning. Both cell types instruct plasticity in local pyramidal cells, and are themselves subject to robust plastic changes. Despite these similarities, the emerging hypothesis is that they fulfill different, and potentially opposite roles, as they receive different inputs, employ distinct inhibitory dynamics and are implicated in different behavioral contexts.

The effect of NMDA-R antagonist, MK-801, on neuronal mismatch along the rat auditory thalamocortical pathway

Efficient sensory processing requires that the brain maximize its response to unexpected stimuli, while suppressing responsivity to expected events. Mismatch negativity (MMN) is an auditory event-related potential that occurs when a regular pattern is interrupted by an event that violates the expected properties of the pattern. According to the predictive coding framework there are two mechanisms underlying the MMN: repetition suppression and prediction error. MMN has been found to be reduced in individuals with schizophrenia, an effect believed to be underpinned by glutamate N-methyl-d-aspartate receptor (NMDA-R) dysfunction. In the current study, we aimed to test how the NMDA-R antagonist, MK-801 in the anaesthetized rat, affected repetition suppression and prediction error processes along the auditory thalamocortical pathway. We found that low-dose systemic administration of MK-801 differentially affect thalamocortical responses, namely, increasing thalamic repetition suppression and cortical prediction error. Results demonstrate an enhancement of neuronal mismatch, also confirmed by large scale-responses. Furthermore, MK-801 produces faster and stronger dynamics of adaptation along the thalamocortical hierarchy. Clearly more research is required to understand how NMDA-R antagonism and dosage affects processes contributing to MMN. Nonetheless, because a low dose of an NMDA-R antagonist increased neuronal mismatch, the outcome has implications for schizophrenia treatment.

Interneuron Types as Attractors and Controllers

Cortical interneurons display striking differences in shape, physiology, and other attributes, challenging us to appropriately classify them. We previously suggested that interneuron types should be defined by their role in cortical processing. Here, we revisit the question of how to codify their diversity based upon their division of labor and function as controllers of cortical information flow. We suggest that developmental trajectories provide a guide for appreciating interneuron diversity and argue that subtype identity is generated using a configurational (rather than combinatorial) code of transcription factors that produce attractor states in the underlying gene regulatory network. We present our updated three-stage model for interneuron specification: an initial cardinal step, allocating interneurons into a few major classes, followed by definitive refinement, creating subclasses upon settling within the cortex, and lastly, state determination, reflecting the incorporation of interneurons into functional circuit ensembles. We close by discussing findings indicating that major interneuron classes are both evolutionarily ancient and conserved. We propose that the complexity of cortical circuits is generated by phylogenetically old interneuron types, complemented by an evolutionary increase in principal neuron diversity. This suggests that a natural neurobiological definition of interneuron types might be derived from a match between their developmental origin and computational function.

A circuit model of auditory cortex

The mammalian sensory cortex is composed of multiple types of inhibitory and excitatory neurons, which form sophisticated microcircuits for processing and transmitting sensory information. Despite rapid progress in understanding the function of distinct neuronal populations, the parameters of connectivity that are required for the function of these microcircuits remain unknown. Recent studies found that two most common inhibitory interneurons, parvalbumin- (PV) and somatostatin-(SST) positive interneurons control sound-evoked responses, temporal adaptation and network dynamics in the auditory cortex (AC). These studies can inform our understanding of parameters for the connectivity of excitatory-inhibitory cortical circuits. Specifically, we asked whether a common microcircuit can account for the disparate effects found in studies by different groups. By starting with a cortical rate model, we find that a simple current-compensating mechanism accounts for the experimental findings from multiple groups. They key mechanisms are two-fold. First, PVs compensate for reduced SST activity when thalamic inputs are strong with less compensation when thalamic inputs are weak. Second, SSTs are generally disinhibited by reduced PV activity regardless of thalamic input strength. These roles are augmented by plastic synapses. These roles reproduce the differential effects of PVs and SSTs in stimulus-specific adaptation, forward suppression and tuning-curve adaptation, as well as the influence of PVs on feedforward functional connectivity in the circuit. This circuit exhibits a balance of inhibitory and excitatory currents that persists on stimulation. This approach brings together multiple findings from different laboratories and identifies a circuit that can be used in future studies of upstream and downstream sensory processing.

Neural Responses and Perceptual Sensitivity to Sound Depend on Sound-Level Statistics

Sensitivity to sound-level statistics is crucial for optimal perception, but research has focused mostly on neurophysiological recordings, whereas behavioral evidence is sparse. We use electroencephalography (EEG) and behavioral methods to investigate how sound-level statistics affect neural activity and the detection of near-threshold changes in sound amplitude. We presented noise bursts with sound levels drawn from distributions with either a low or a high modal sound level. One participant group listened to the stimulation while EEG was recorded (Experiment I). A second group performed a behavioral amplitude-modulation detection task (Experiment II). Neural activity depended on sound-level statistical context in two different ways. Consistent with an account positing that the sensitivity of neurons to sound intensity adapts to ambient sound level, responses for higher-intensity bursts were larger in low-mode than high-mode contexts, whereas responses for lower-intensity bursts did not differ between contexts. In contrast, a concurrent slow neural response indicated prediction-error processing: The response was larger for bursts at intensities that deviated from the predicted statistical context compared to those not deviating. Behavioral responses were consistent with prediction-error processing, but not with neural adaptation. Hence, neural activity adapts to sound-level statistics, but fine-tuning of perceptual sensitivity appears to involve neural prediction-error responses.

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

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

Distinct subtypes of inhibitory interneurons differentially promote the propagation of rate and temporal codes in the feedforward neural network

Sensory information is believed to be encoded in neuronal spikes using two different neural codes, the rate code (spike firing rate) and the temporal code (precisely-timed spikes). Since the sensory cortex has a highly hierarchical feedforward structure, sensory information-carrying neural codes should reliably propagate across the feedforward network (FFN) of the cortex. Experimental evidence suggests that inhibitory interneurons, such as the parvalbumin-positive (PV) and somatostatin-positive (SST) interneurons, that have distinctively different electrophysiological and synaptic properties, modulate the neural codes during sensory information processing in the cortex. However, how PV and SST interneurons impact on the neural code propagation in the cortical FFN is unknown. We address this question by building a five-layer FFN model consisting of a physiologically realistic Hodgkin-Huxley-type models of excitatory neurons and PV/SST interneurons at different ratios. In response to different firing rate inputs (20-80 Hz), a higher ratio of PV over SST interneurons promoted a reliable propagation of all ranges of firing rate inputs. In contrast, in response to a range of precisely-timed spikes in the form of pulse-packets [with a different number of spikes (α, 40-400 spikes) and degree of dispersion (σ, 0-20 ms)], a higher ratio of SST over PV interneurons promoted a reliable propagation of pulse-packets. Our simulation results show that PV and SST interneurons differentially promote a reliable propagation of the rate and temporal codes, respectively, indicating that the dynamic recruitment of PV and SST interneurons may play critical roles in a reliable propagation of sensory information-carrying neural codes in the cortical FFN.

Somatostatin-Expressing Interneurons in the Auditory Cortex Mediate Sustained Suppression by Spectral Surround

Sensory systems integrate multiple stimulus features to generate coherent percepts. Spectral surround suppression, the phenomenon by which sound-evoked responses of auditory neurons are suppressed by stimuli outside their receptive field, is an example of this integration taking place in the auditory system. While this form of global integration is commonly observed in auditory cortical neurons, and potentially used by the nervous system to separate signals from noise, the mechanisms that underlie this suppression of activity are not well understood. We evaluated the contributions to spectral surround suppression of the two most common inhibitory cell types in the cortex, parvalbumin-expressing (PV+) and somatostatin-expressing (SOM+) interneurons, in mice of both sexes. We found that inactivating SOM+ cells, but not PV+ cells, significantly reduces sustained spectral surround suppression in excitatory cells, indicating a dominant causal role for SOM+ cells in the integration of information across multiple frequencies. The similarity of these results to those from other sensory cortices provides evidence of common mechanisms across the cerebral cortex for generating global percepts from separate features.SIGNIFICANCE STATEMENT To generate coherent percepts, sensory systems integrate simultaneously occurring features of a stimulus, yet the mechanisms by which this integration occurs are not fully understood. Our results show that neurochemically distinct neuronal subtypes in the primary auditory cortex have different contributions to the integration of different frequency components of an acoustic stimulus. Together with findings from other sensory cortices, our results provide evidence of a common mechanism for cortical computations used for global integration of stimulus features.

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

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

Contrast gain control occurs independently of both parvalbumin-positive interneuron activity and shunting inhibition in auditory cortex

Contrast gain control is the systematic adjustment of neuronal gain in response to the contrast of sensory input. It is widely observed in sensory cortical areas and has been proposed to be a canonical neuronal computation. Here, we investigated whether shunting inhibition from parvalbumin-positive interneurons-a mechanism involved in gain control in visual cortex-also underlies contrast gain control in auditory cortex. First, we performed extracellular recordings in the auditory cortex of anesthetized male mice and optogenetically manipulated the activity of parvalbumin-positive interneurons while varying the contrast of the sensory input. We found that both activation and suppression of parvalbumin interneuron activity altered the overall gain of cortical neurons. However, despite these changes in overall gain, we found that manipulating parvalbumin interneuron activity did not alter the strength of contrast gain control in auditory cortex. Furthermore, parvalbumin-positive interneurons did not show increases in activity in response to high-contrast stimulation, which would be expected if they drive contrast gain control. Finally, we performed in vivo whole-cell recordings in auditory cortical neurons during high- and low-contrast stimulation and found that no increase in membrane conductance was observed during high-contrast stimulation. Taken together, these findings indicate that while parvalbumin-positive interneuron activity modulates the overall gain of auditory cortical responses, other mechanisms are primarily responsible for contrast gain control in this cortical area.NEW & NOTEWORTHY We investigated whether contrast gain control is mediated by shunting inhibition from parvalbumin-positive interneurons in auditory cortex. We performed extracellular and intracellular recordings in mouse auditory cortex while presenting sensory stimuli with varying contrasts and manipulated parvalbumin-positive interneuron activity using optogenetics. We show that while parvalbumin-positive interneuron activity modulates the gain of cortical responses, this activity is not the primary mechanism for contrast gain control in auditory cortex.

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.

Genetic Reduction of Matrix Metalloproteinase-9 Promotes Formation of Perineuronal Nets Around Parvalbumin-Expressing Interneurons and Normalizes Auditory Cortex Responses in Developing Fmr1 Knock-Out Mice

Abnormal sensory responses associated with Fragile X Syndrome (FXS) and autism spectrum disorders include hypersensitivity and impaired habituation to repeated stimuli. Similar sensory deficits are also observed in adult Fmr1 knock-out (KO) mice and are reversed by genetic deletion of Matrix Metalloproteinase-9 (MMP-9) through yet unknown mechanisms. Here we present new evidence that impaired development of parvalbumin (PV)-expressing inhibitory interneurons may underlie hyper-responsiveness in auditory cortex of Fmr1 KO mice via MMP-9-dependent regulation of perineuronal nets (PNNs). First, we found that PV cell development and PNN formation around GABAergic interneurons were impaired in developing auditory cortex of Fmr1 KO mice. Second, MMP-9 levels were elevated in P12-P18 auditory cortex of Fmr1 KO mice and genetic reduction of MMP-9 to WT levels restored the formation of PNNs around PV cells. Third, in vivo single-unit recordings from auditory cortex neurons showed enhanced spontaneous and sound-driven responses in developing Fmr1 KO mice, which were normalized following genetic reduction of MMP-9. These findings indicate that elevated MMP-9 levels contribute to the development of sensory hypersensitivity by influencing formation of PNNs around PV interneurons suggesting MMP-9 as a new therapeutic target to reduce sensory deficits in FXS and potentially other autism spectrum disorders.

Audio-visual experience strengthens multisensory assemblies in adult mouse visual cortex

We experience the world through multiple senses simultaneously. To better understand mechanisms of multisensory processing we ask whether inputs from two senses (auditory and visual) can interact and drive plasticity in neural-circuits of the primary visual cortex (V1). Using genetically-encoded voltage and calcium indicators, we find coincident audio-visual experience modifies both the supra and subthreshold response properties of neurons in L2/3 of mouse V1. Specifically, we find that after audio-visual pairing, a subset of multimodal neurons develops enhanced auditory responses to the paired auditory stimulus. This cross-modal plasticity persists over days and is reflected in the strengthening of small functional networks of L2/3 neurons. We find V1 processes coincident auditory and visual events by strengthening functional associations between feature specific assemblies of multimodal neurons during bouts of sensory driven co-activity, leaving a trace of multisensory experience in the cortical network.

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

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

Rapid and long-lasting improvements in neural discrimination of acoustic signals with passive familiarization

Sensory representations in the adult brain must undergo dynamic changes to adapt to the complexity of the external world. This study investigated how passive exposure to novel sounds modifies neural representations to facilitate recognition and discrimination, using the zebra finch model organism. The neural responses in an auditory structure in the zebra finch brain, Caudal Medial Nidopallium (NCM), undergo a long-term form of adaptation with repeated stimulus presentation, providing an excellent substrate to probe the neural underpinnings of adaptive sensory representations. In Experiment 1, electrophysiological activity in NCM was recorded under passive listening conditions as novel natural vocalizations were familiarized through playback. Neural decoding of stimuli using the temporal profiles of both single-unit and multi-unit responses improved dramatically during the first few stimulus presentations. During subsequent encounters, these signals were recognized after hearing fewer initial acoustic features. Remarkably, the accuracy of neural decoding was higher when different stimuli were heard in separate blocks compared to when they were presented randomly in a shuffled sequence. NCM neurons with narrow spike waveforms generally yielded higher neural decoding accuracy than wide spike neurons, but the rate at which these accuracies improved with passive exposure was comparable between the two neuron types. Experiment 2 supported and extended these findings by showing that the rapid gains in neural decoding of novel vocalizations with passive familiarization were long-lasting, maintained for 20 hours after the initial encounter, in multi-unit responses. Taken together, these findings provide valuable insights into the mechanisms by which the nervous system dynamically modulates sensory representations to improve discrimination of novel complex signals over short and long timescales. Similar mechanisms may also be engaged during processing of human speech signals, and thus may have potential translational relevance for elucidating the neural basis of speech comprehension difficulties.

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.

Coding Principles in Adaptation

Adaptation is a common principle that recurs throughout the nervous system at all stages of processing. This principle manifests in a variety of phenomena, from spike frequency adaptation, to apparent changes in receptive fields with changes in stimulus statistics, to enhanced responses to unexpected stimuli. The ubiquity of adaptation leads naturally to the question: What purpose do these different types of adaptation serve? A diverse set of theories, often highly overlapping, has been proposed to explain the functional role of adaptive phenomena. In this review, we discuss several of these theoretical frameworks, highlighting relationships among them and clarifying distinctions. We summarize observations of the varied manifestations of adaptation, particularly as they relate to these theoretical frameworks, focusing throughout on the visual system and making connections to other sensory systems.

Diversity and Function of Somatostatin-Expressing Interneurons in the Cerebral Cortex

Inhibitory interneurons make up around 10-20% of the total neuron population in the cerebral cortex. A hallmark of inhibitory interneurons is their remarkable diversity in terms of morphology, synaptic connectivity, electrophysiological and neurochemical properties. It is generally understood that there are three distinct and non-overlapping interneuron classes in the mouse neocortex, namely, parvalbumin-expressing, 5-HT3A receptor-expressing and somatostatin-expressing interneuron classes. Each class is, in turn, composed of a multitude of subclasses, resulting in a growing number of interneuron classes and subclasses. In this review, I will focus on the diversity of somatostatin-expressing interneurons (SOM+ INs) in the cerebral cortex and elucidate their function in cortical circuits. I will then discuss pathological consequences of a malfunctioning of SOM+ INs in neurological disorders such as major depressive disorder, and present future avenues in SOM research and brain pathologies.

Phonetic acquisition in cortical dynamics, a computational approach

Many computational theories have been developed to improve artificial phonetic classification performance from linguistic auditory streams. However, less attention has been given to psycholinguistic data and neurophysiological features recently found in cortical tissue. We focus on a context in which basic linguistic units–such as phonemes–are extracted and robustly classified by humans and other animals from complex acoustic streams in speech data. We are especially motivated by the fact that 8-month-old human infants can accomplish segmentation of words from fluent audio streams based exclusively on the statistical relationships between neighboring speech sounds without any kind of supervision. In this paper, we introduce a biologically inspired and fully unsupervised neurocomputational approach that incorporates key neurophysiological and anatomical cortical properties, including columnar organization, spontaneous micro-columnar formation, adaptation to contextual activations and Sparse Distributed Representations (SDRs) produced by means of partial N-Methyl-D-aspartic acid (NMDA) depolarization. Its feature abstraction capabilities show promising phonetic invariance and generalization attributes. Our model improves the performance of a Support Vector Machine (SVM) classifier for monosyllabic, disyllabic and trisyllabic word classification tasks in the presence of environmental disturbances such as white noise, reverberation, and pitch and voice variations. Furthermore, our approach emphasizes potential self-organizing cortical principles achieving improvement without any kind of optimization guidance which could minimize hypothetical loss functions by means of–for example–backpropagation. Thus, our computational model outperforms multiresolution spectro-temporal auditory feature representations using only the statistical sequential structure immerse in the phonotactic rules of the input stream.

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.