Representational maps in the brain: concepts, approaches, and applications.

Neural systems have evolved to process sensory stimuli in a way that allows for efficient and adaptive behavior in a complex environment. Recent technological advances enable us to investigate sensory processing in animal models by simultaneously recording the activity of large populations of neurons with single-cell resolution, yielding high-dimensional datasets. In this review, we discuss concepts and approaches for assessing the population-level representation of sensory stimuli in the form of a representational map. In such a map, not only are the identities of stimuli distinctly represented, but their relational similarity is also mapped onto the space of neuronal activity. We highlight example studies in which the structure of representational maps in the brain are estimated from recordings in humans as well as animals and compare their methodological approaches. Finally, we integrate these aspects and provide an outlook for how the concept of representational maps could be applied to various fields in basic and clinical neuroscience.

Sound elicits stereotyped facial movements that provide a sensitive index of hearing abilities in mice.

Sound elicits rapid movements of muscles in the face, ears, and eyes that protect the body from injury and trigger brain-wide internal state changes. Here, we performed quantitative facial videography from mice resting atop a piezoelectric force plate and observed that broadband sounds elicited rapid and stereotyped facial twitches. Facial motion energy (FME) adjacent to the whisker array was 30 dB more sensitive than the acoustic startle reflex and offered greater inter-trial and inter-animal reliability than sound-evoked pupil dilations or movement of other facial and body regions. FME tracked the low-frequency envelope of broadband sounds, providing a means to study behavioral discrimination of complex auditory stimuli, such as speech phonemes in noise. Approximately 25% of layer 5-6 units in the auditory cortex (ACtx) exhibited firing rate changes during facial movements. However, FME facilitation during ACtx photoinhibition indicated that sound-evoked facial movements were mediated by a midbrain pathway and modulated by descending corticofugal input. FME and auditory brainstem response (ABR) thresholds were closely aligned after noise-induced sensorineural hearing loss, yet FME growth slopes were disproportionately steep at spared frequencies, reflecting a central plasticity that matched commensurate changes in ABR wave 4. Sound-evoked facial movements were also hypersensitive in Ptchd1 knockout mice, highlighting the use of FME for identifying sensory hyper-reactivity phenotypes after adult-onset hyperacusis and inherited deficiencies in autism risk genes. These findings present a sensitive and integrative measure of hearing while also highlighting that even low-intensity broadband sounds can elicit a complex mixture of auditory, motor, and reafferent somatosensory neural activity.

A stable sensory map emerges from a dynamic equilibrium of neurons with unstable tuning properties.

Recent long-term measurements of neuronal activity have revealed that, despite stability in large-scale topographic maps, the tuning properties of individual cortical neurons can undergo substantial reformatting over days. To shed light on this apparent contradiction, we captured the sound response dynamics of auditory cortical neurons using repeated 2-photon calcium imaging in awake mice. We measured sound-evoked responses to a set of pure tone and complex sound stimuli in more than 20,000 auditory cortex neurons over several days. We found that a substantial fraction of neurons dropped in and out of the population response. We modeled these dynamics as a simple discrete-time Markov chain, capturing the continuous changes in responsiveness observed during stable behavioral and environmental conditions. Although only a minority of neurons were driven by the sound stimuli at a given time point, the model predicts that most cells would at least transiently become responsive within 100 days. We observe that, despite single-neuron volatility, the population-level representation of sound frequency was stably maintained, demonstrating the dynamic equilibrium underlying the tonotopic map. Our results show that sensory maps are maintained by shifting subpopulations of neurons "sharing" the job of creating a sensory representation.

Cell-type-specific silence in thalamocortical circuits precedes hippocampal sharp-wave ripples.

Evidence suggests that the hippocampus conveys memory-related neural patterns across distributed cortical circuits during high-frequency oscillations called sharp-wave ripples (SWRs). We investigate how circuit activity in the retrosplenial cortex (RSC), a primary hippocampal target, could aid in processing SWR-related input. Using patch-clamp recordings from awake mice, we find that SWR-aligned membrane potential modulation is widespread but weak, and that spiking responses are sparse. However, using cell-type-specific two-photon Ca2+ imaging and optogenetics, we show that, 1-2 s before SWRs, superficial inhibition and thalamocortical input in RSC is reduced. We propose that pyramidal dendrites experience decreased local inhibition and subcortical interference in a seconds-long time window preceding SWRs. This may aid communication of weak and sparse SWR-aligned excitation between the hippocampus and neocortex and promote the strengthening of memory-related connections.

Learning-induced biases in the ongoing dynamics of sensory representations predict stimulus generalization.

Sensory stimuli have long been thought to be represented in the brain as activity patterns of specific neuronal assemblies. However, we still know relatively little about the long-term dynamics of sensory representations. Using chronic in vivo calcium imaging in the mouse auditory cortex, we find that sensory representations undergo continuous recombination, even under behaviorally stable conditions. Auditory cued fear conditioning introduces a bias into these ongoing dynamics, resulting in a long-lasting increase in the number of stimuli activating the same subset of neurons. This plasticity is specific for stimuli sharing representational similarity to the conditioned sound prior to conditioning and predicts behaviorally observed stimulus generalization. Our findings demonstrate that learning-induced plasticity leading to a representational linkage between the conditioned stimulus and non-conditioned stimuli weaves into ongoing dynamics of the brain rather than acting on an otherwise static substrate.

Mapping vestibular and visual contributions to angular head velocity tuning in the cortex.

Neurons that signal the angular velocity of head movements (AHV cells) are important for processing visual and spatial information. However, it has been challenging to isolate the sensory modality that drives them and to map their cortical distribution. To address this, we develop a method that enables rotating awake, head-fixed mice under a two-photon microscope in a visual environment. Starting in layer 2/3 of the retrosplenial cortex, a key area for vision and navigation, we find that 10% of neurons report angular head velocity (AHV). Their tuning properties depend on vestibular input with a smaller contribution of vision at lower speeds. Mapping the spatial extent, we find AHV cells in all cortical areas that we explored, including motor, somatosensory, visual, and posterior parietal cortex. Notably, the vestibular and visual contributions to AHV are area dependent. Thus, many cortical circuits have access to AHV, enabling a diverse integration with sensorimotor and cognitive information.

RippleNet: a Recurrent Neural Network for Sharp Wave Ripple (SPW-R) Detection.

Hippocampal sharp wave ripples (SPW-R) have been identified as key bio-markers of important brain functions such as memory consolidation and decision making. Understanding their underlying mechanisms in healthy and pathological brain function and behaviour rely on accurate SPW-R detection. In this multidisciplinary study, we propose a novel, self-improving artificial intelligence (AI) detection method in the form of deep Recurrent Neural Networks (RNN) with Long Short-Term memory (LSTM) layers that can learn features of SPW-R events from raw, labeled input data. The approach contrasts conventional routines that typically relies on hand-crafted, heuristic feature extraction and often laborious manual curation. The algorithm is trained using supervised learning on hand-curated data sets with SPW-R events obtained under controlled conditions. The input to the algorithm is the local field potential (LFP), the low-frequency part of extracellularly recorded electric potentials from the CA1 region of the hippocampus. Its output predictions can be interpreted as time-varying probabilities of SPW-R events for the duration of the inputs. A simple thresholding applied to the output probabilities is found to identify times of SPW-R events with high precision. The non-causal, or bidirectional variant of the proposed algorithm demonstrates consistently better accuracy compared to the causal, or unidirectional counterpart. Reference implementations of the algorithm, named 'RippleNet', are open source, freely available, and implemented using a common open-source framework for neural networks (tensorflow.keras) and can be easily incorporated into existing data analysis workflows for processing experimental data.

Astrocytic Ca2+ signaling is reduced during sleep and is involved in the regulation of slow wave sleep.

Astrocytic Ca2+ signaling has been intensively studied in health and disease but has not been quantified during natural sleep. Here, we employ an activity-based algorithm to assess astrocytic Ca2+ signals in the neocortex of awake and naturally sleeping mice while monitoring neuronal Ca2+ activity, brain rhythms and behavior. We show that astrocytic Ca2+ signals exhibit distinct features across the sleep-wake cycle and are reduced during sleep compared to wakefulness. Moreover, an increase in astrocytic Ca2+ signaling precedes transitions from slow wave sleep to wakefulness, with a peak upon awakening exceeding the levels during whisking and locomotion. Finally, genetic ablation of an important astrocytic Ca2+ signaling pathway impairs slow wave sleep and results in an increased number of microarousals, abnormal brain rhythms, and an increased frequency of slow wave sleep state transitions and sleep spindles. Our findings demonstrate an essential role for astrocytic Ca2+ signaling in regulating slow wave sleep.

Pharmacological modulation of Kv3.1 mitigates auditory midbrain temporal processing deficits following auditory nerve damage.

Higher stages of central auditory processing compensate for a loss of cochlear nerve synapses by increasing the gain on remaining afferent inputs, thereby restoring firing rate codes for rudimentary sound features. The benefits of this compensatory plasticity are limited, as the recovery of precise temporal coding is comparatively modest. We reasoned that persistent temporal coding deficits could be ameliorated through modulation of voltage-gated potassium (Kv) channels that regulate temporal firing patterns. Here, we characterize AUT00063, a pharmacological compound that modulates Kv3.1, a high-threshold channel expressed in fast-spiking neurons throughout the central auditory pathway. Patch clamp recordings from auditory brainstem neurons and in silico modeling revealed that application of AUT00063 reduced action potential timing variability and improved temporal coding precision. Systemic injections of AUT00063 in vivo improved auditory synchronization and supported more accurate decoding of temporal sound features in the inferior colliculus and auditory cortex in adult mice with a near-complete loss of auditory nerve afferent synapses in the contralateral ear. These findings suggest modulating Kv3.1 in central neurons could be a promising therapeutic approach to mitigate temporal processing deficits that commonly accompany aging, tinnitus, ototoxic drug exposure or noise damage.

A stable brain from unstable components: Emerging concepts and implications for neural computation.

Neuroscientists have often described the adult brain in similar terms to an electronic circuit board- dependent on fixed, precise connectivity. However, with the advent of technologies allowing chronic measurements of neural structure and function, the emerging picture is that neural networks undergo significant remodeling over multiple timescales, even in the absence of experimenter-induced learning or sensory perturbation. Here, we attempt to reconcile the parallel observations that critical brain functions are stably maintained, while synapse- and single-cell properties appear to be reformatted regularly throughout adult life. In this review, we discuss experimental evidence at multiple levels ranging from synapses to neuronal ensembles, suggesting that many parameters are maintained in a dynamic equilibrium. We highlight emerging hypotheses that could explain how stable brain functions may be generated from dynamic elements. Furthermore, we discuss the impact of dynamic circuit elements on neural computations, and how they could provide living neural circuits with computational abilities a fixed structure cannot offer. Taken together, recent evidence indicates that continuous dynamics are a fundamental property of neural circuits compatible with macroscopically stable behaviors. In addition, they may be a unique advantage imparting robustness and flexibility throughout life.

Persistent Thalamic Sound Processing Despite Profound Cochlear Denervation.

Neurons at higher stages of sensory processing can partially compensate for a sudden drop in peripheral input through a homeostatic plasticity process that increases the gain on weak afferent inputs. Even after a profound unilateral auditory neuropathy where >95% of afferent synapses between auditory nerve fibers and inner hair cells have been eliminated with ouabain, central gain can restore cortical processing and perceptual detection of basic sounds delivered to the denervated ear. In this model of profound auditory neuropathy, auditory cortex (ACtx) processing and perception recover despite the absence of an auditory brainstem response (ABR) or brainstem acoustic reflexes, and only a partial recovery of sound processing at the level of the inferior colliculus (IC), an auditory midbrain nucleus. In this study, we induced a profound cochlear neuropathy with ouabain and asked whether central gain enabled a compensatory plasticity in the auditory thalamus comparable to the full recovery of function previously observed in the ACtx, the partial recovery observed in the IC, or something different entirely. Unilateral ouabain treatment in adult mice effectively eliminated the ABR, yet robust sound-evoked activity persisted in a minority of units recorded from the contralateral medial geniculate body (MGB) of awake mice. Sound driven MGB units could decode moderate and high-intensity sounds with accuracies comparable to sham-treated control mice, but low-intensity classification was near chance. Pure tone receptive fields and synchronization to broadband pulse trains also persisted, albeit with significantly reduced quality and precision, respectively. MGB decoding of temporally modulated pulse trains and speech tokens were both greatly impaired in ouabain-treated mice. Taken together, the absence of an ABR belied a persistent auditory processing at the level of the MGB that was likely enabled through increased central gain. Compensatory plasticity at the level of the auditory thalamus was less robust overall than previous observations in cortex or midbrain. Hierarchical differences in compensatory plasticity following sensorineural hearing loss may reflect differences in GABA circuit organization within the MGB, as compared to the ACtx or IC.

Interactions across Multiple Stimulus Dimensions in Primary Auditory Cortex.

Although sensory cortex is thought to be important for the perception of complex objects, its specific role in representing complex stimuli remains unknown. Complex objects are rich in information along multiple stimulus dimensions. The position of cortex in the sensory hierarchy suggests that cortical neurons may integrate across these dimensions to form a more gestalt representation of auditory objects. Yet, studies of cortical neurons typically explore single or few dimensions due to the difficulty of determining optimal stimuli in a high dimensional stimulus space. Evolutionary algorithms (EAs) provide a potentially powerful approach for exploring multidimensional stimulus spaces based on real-time spike feedback, but two important issues arise in their application. First, it is unclear whether it is necessary to characterize cortical responses to multidimensional stimuli or whether it suffices to characterize cortical responses to a single dimension at a time. Second, quantitative methods for analyzing complex multidimensional data from an EA are lacking. Here, we apply a statistical method for nonlinear regression, the generalized additive model (GAM), to address these issues. The GAM quantitatively describes the dependence between neural response and all stimulus dimensions. We find that auditory cortical neurons in mice are sensitive to interactions across dimensions. These interactions are diverse across the population, indicating significant integration across stimulus dimensions in auditory cortex. This result strongly motivates using multidimensional stimuli in auditory cortex. Together, the EA and the GAM provide a novel quantitative paradigm for investigating neural coding of complex multidimensional stimuli in auditory and other sensory cortices.

Central Gain Restores Auditory Processing following Near-Complete Cochlear Denervation.

Sensory organ damage induces a host of cellular and physiological changes in the periphery and the brain. Here, we show that some aspects of auditory processing recover after profound cochlear denervation due to a progressive, compensatory plasticity at higher stages of the central auditory pathway. Lesioning >95% of cochlear nerve afferent synapses, while sparing hair cells, in adult mice virtually eliminated the auditory brainstem response and acoustic startle reflex, yet tone detection behavior was nearly normal. As sound-evoked responses from the auditory nerve grew progressively weaker following denervation, sound-evoked activity in the cortex-and, to a lesser extent, the midbrain-rebounded or surpassed control levels. Increased central gain supported the recovery of rudimentary sound features encoded by firing rate, but not features encoded by precise spike timing such as modulated noise or speech. These findings underscore the importance of central plasticity in the perceptual sequelae of cochlear hearing impairment.

Online stimulus optimization rapidly reveals multidimensional selectivity in auditory cortical neurons.

Neurons in sensory brain regions shape our perception of the surrounding environment through two parallel operations: decomposition and integration. For example, auditory neurons decompose sounds by separately encoding their frequency, temporal modulation, intensity, and spatial location. Neurons also integrate across these various features to support a unified perceptual gestalt of an auditory object. At higher levels of a sensory pathway, neurons may select for a restricted region of feature space defined by the intersection of multiple, independent stimulus dimensions. To further characterize how auditory cortical neurons decompose and integrate multiple facets of an isolated sound, we developed an automated procedure that manipulated five fundamental acoustic properties in real time based on single-unit feedback in awake mice. Within several minutes, the online approach converged on regions of the multidimensional stimulus manifold that reliably drove neurons at significantly higher rates than predefined stimuli. Optimized stimuli were cross-validated against pure tone receptive fields and spectrotemporal receptive field estimates in the inferior colliculus and primary auditory cortex. We observed, from midbrain to cortex, increases in both level invariance and frequency selectivity, which may underlie equivalent sparseness of responses in the two areas. We found that onset and steady-state spike rates increased proportionately as the stimulus was tailored to the multidimensional receptive field. By separately evaluating the amount of leverage each sound feature exerted on the overall firing rate, these findings reveal interdependencies between stimulus features as well as hierarchical shifts in selectivity and invariance that may go unnoticed with traditional approaches.

Robustness of cortical topography across fields, laminae, anesthetic states, and neurophysiological signal types.

Topographically organized maps of the sensory receptor epithelia are regarded as cornerstones of cortical organization as well as valuable readouts of diverse biological processes ranging from evolution to neural plasticity. However, maps are most often derived from multiunit activity recorded in the thalamic input layers of anesthetized animals using near-threshold stimuli. Less distinct topography has been described by studies that deviated from the formula above, which brings into question the generality of the principle. Here, we explicitly compared the strength of tonotopic organization at various depths within core and belt regions of the auditory cortex using electrophysiological measurements ranging from single units to delta-band local field potentials (LFP) in the awake and anesthetized mouse. Unit recordings in the middle cortical layers revealed a precise tonotopic organization in core, but not belt, regions of auditory cortex that was similarly robust in awake and anesthetized conditions. In core fields, tonotopy was degraded outside the middle layers or when LFP signals were substituted for unit activity, due to an increasing proportion of recording sites with irregular tuning for pure tones. However, restricting our analysis to clearly defined receptive fields revealed an equivalent tonotopic organization in all layers of the cortical column and for LFP activity ranging from gamma to theta bands. Thus, core fields represent a transition between topographically organized simple receptive field arrangements that extend throughout all layers of the cortical column and the emergence of nontonotopic representations outside the input layers that are further elaborated in the belt fields.

Sound-evoked olivocochlear activation in unanesthetized mice.

Genetic tools available for the mouse make it a powerful model to study the modulation of cochlear function by descending control systems. Suppression of distortion product otoacoustic emission (DPOAE) amplitude by contralateral acoustic stimulation (CAS) provides a robust tool for noninvasively monitoring the strength of descending modulation, yet investigations in mice have been performed infrequently and only under anesthesia, a condition likely to reduce olivocochlear activation. Here, we characterize the contralateral olivocochlear reflex in the alert, unanesthetized mouse. Head-fixed mice were restrained between two closed acoustic systems, while an artifact rejection protocol minimized contamination from self-generated sounds and movements. In mice anesthetized with pentobarbital, ketamine or urethane, CAS at 80 dB SPL evoked, on average, a <1-dB change in DPOAE amplitude. In contrast, the mean CAS-induced DPOAE suppression in unanesthetized mice was nearly 8 dB. Experiments in mice with targeted deletion of the α9 subunit of the nicotinic acetylcholine receptor confirmed the contribution of the medial olivocochlear efferents to this phenomenon. These findings demonstrate the utility of the CAS assay in the unanesthetized mouse and highlight the adverse effects of anesthesia when probing the functional status of descending control pathways within the auditory system.