Subcortical origin of nonlinear sound encoding in auditory cortex.

A major challenge in neuroscience is to understand how neural representations of sensory information are transformed by the network of ascending and descending connections in each sensory system. By recording from neurons at several levels of the auditory pathway, we show that much of the nonlinear encoding of complex sounds in auditory cortex can be explained by transformations in the midbrain and thalamus. Modeling cortical neurons in terms of their inputs across these subcortical populations enables their responses to be predicted with unprecedented accuracy. By contrast, subcortical responses cannot be predicted from descending cortical inputs, indicating that ascending transformations are irreversible, resulting in increasingly lossy, higher-order representations across the auditory pathway. Rather, auditory cortex selectively modulates the nonlinear aspects of thalamic auditory responses and the functional coupling between subcortical neurons without affecting the linear encoding of sound. These findings reveal the fundamental role of subcortical transformations in shaping cortical responses.

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

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

Mixed Representations of Sound and Action in the Auditory Midbrain.

Linking sensory input and its consequences is a fundamental brain operation. During behavior, the neural activity of neocortical and limbic systems often reflects dynamic combinations of sensory and task-dependent variables, and these "mixed representations" are suggested to be important for perception, learning, and plasticity. However, the extent to which such integrative computations might occur outside of the forebrain is less clear. Here, we conduct cellular-resolution two-photon Ca2+ imaging in the superficial "shell" layers of the inferior colliculus (IC), as head-fixed mice of either sex perform a reward-based psychometric auditory task. We find that the activity of individual shell IC neurons jointly reflects auditory cues, mice's actions, and behavioral trial outcomes, such that trajectories of neural population activity diverge depending on mice's behavioral choice. Consequently, simple classifier models trained on shell IC neuron activity can predict trial-by-trial outcomes, even when training data are restricted to neural activity occurring prior to mice's instrumental actions. Thus, in behaving mice, auditory midbrain neurons transmit a population code that reflects a joint representation of sound, actions, and task-dependent variables.

The role of midbrain dopamine cells projecting to the insular cortex in mediated performance: Implications for animal models of reality testing.

A growing body of literature indicates that mediated learning techniques have specific utility for tapping into reality testing in animal models of neuropsychiatric illness. In particular, recent work has shown that animal models that recapitulate various endophenotypes of schizophrenia are particularly vulnerable to impairments in reality testing when undergoing mediated learning. Multiple studies have indicated that these effects are dopamine receptor 2-dependent and correlated with aberrant insular cortex (IC) activity. However, until now, the connection between dopamine and the IC had not been investigated. Here, we utilized a novel intersectional approach to label mesencephalic dopamine cells that specifically project to the insular cortex in both wild-type controls and transgenic mice expressing the dominant-negative form of the Disrupted-in-Schizophrenia-1 (DISC-1) gene. Using these techniques, we identified a population of cells that project from the ventral tegmental area (VTA) to the IC. Afterward, we conducted multiple studies to test the necessity of this circuit in behaviors ranging from gustatory detection to the maintenance of effort and, finally, mediated performance. Our results indicate that perturbations of the DISC-1 genetic locus lead to a reduction in the number of cells in the VTA → IC circuit. Behaviorally, VTA → IC circuitry does not influence gustatory detection or motivation to acquire sucrose reward; however, inactivation of this circuit differentially suppresses Pavlovian approach behavior in wild-type and DISC-1 transgenic mice during mediated performance testing. Moreover, under these testing conditions, inactivation of this circuit predisposes wild-type (but not DISC-1) mice to display impaired reality testing. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Cognitive representations of intracranial self-stimulation of midbrain dopamine neurons depend on stimulation frequency.

Dopamine neurons in the ventral tegmental area support intracranial self-stimulation (ICSS), yet the cognitive representations underlying this phenomenon remain unclear. Here, 20-Hz stimulation of dopamine neurons, which approximates a physiologically relevant prediction error, was not sufficient to support ICSS beyond a continuously reinforced schedule and did not endow cues with a general or specific value. However, 50-Hz stimulation of dopamine neurons was sufficient to drive robust ICSS and was represented as a specific reward to motivate behavior. The frequency dependence of this effect is due to the rate (not the number) of action potentials produced by dopamine neurons, which differently modulates dopamine release downstream.

Mesostriatal dopamine is sensitive to changes in specific cue-reward contingencies.

Learning causal relationships relies on understanding how often one event precedes another. To investigate how dopamine neuron activity and neurotransmitter release change when a retrospective relationship is degraded for a specific pair of events, we used outcome-selective Pavlovian contingency degradation in rats. Conditioned responding was attenuated for the cue-reward contingency that was degraded, as was dopamine neuron activity in the midbrain and dopamine release in the ventral striatum in response to the cue and subsequent reward. Contingency degradation also abolished the trial-by-trial history dependence of the dopamine responses at the time of trial outcome. This profile of changes in cue- and reward-evoked responding is not easily explained by a standard reinforcement learning model. An alternative model based on learning causal relationships was better able to capture dopamine responses during contingency degradation, as well as conditioned behavior following optogenetic manipulations of dopamine during noncontingent rewards. Our results suggest that mesostriatal dopamine encodes the contingencies between meaningful events during learning.

Distributional coding of associative learning in discrete populations of midbrain dopamine neurons.

Midbrain dopamine neurons are thought to play key roles in learning by conveying the difference between expected and actual outcomes. Recent evidence suggests diversity in dopamine signaling, yet it remains poorly understood how heterogeneous signals might be organized to facilitate the role of downstream circuits mediating distinct aspects of behavior. Here, we investigated the organizational logic of dopaminergic signaling by recording and labeling individual midbrain dopamine neurons during associative behavior. Our findings show that reward information and behavioral parameters are not only heterogeneously encoded but also differentially distributed across populations of dopamine neurons. Retrograde tracing and fiber photometry suggest that populations of dopamine neurons projecting to different striatal regions convey distinct signals. These data, supported by computational modeling, indicate that such distributional coding can maximize dynamic range and tailor dopamine signals to facilitate specialized roles of different striatal regions.

Decoding Typical Flight States Based on Neural Signals from the Midbrain Motor Nuclei of Pigeons.

BACKGROUND: Exploring the neural encoding mechanism and decoding of motion state switching during flight can advance our knowledge of avian behavior control and contribute to the development of avian robots. However, limited acquisition equipment and neural signal quality have posed challenges, thus we understand little about the neural mechanisms of avian flight. METHODS: We used chronically implanted micro-electrode arrays to record the local field potentials (LFPs) in the formation reticularis medialis mesencephali (FRM) of pigeons during various motion states in their natural outdoor flight. Subsequently, coherence-based functional connectivity networks under different bands were constructed and the topological features were extracted. Finally, we used a support vector machine model to decode different flight states. RESULTS: Our findings indicate that the gamma band (80-150 Hz) in the FRM exhibits significant power for identifying different states in pigeons. Specifically, the avian brain transmitted flight related information more efficiently during the accelerated take-off or decelerated landing states, compared with the uniform flight and baseline states. Finally, we achieved a best average accuracy of 0.86 using the connectivity features in the 80-150 Hz band and 0.89 using the fused features for state decoding. CONCLUSIONS: Our results open up possibilities for further research into the neural mechanism of avian flight and contribute to the understanding of flight behavior control in birds.

Auditory Competition and Coding of Relative Stimulus Strength across Midbrain Space Maps of Barn Owls.

The natural environment challenges the brain to prioritize the processing of salient stimuli. The barn owl, a sound localization specialist, exhibits a circuit called the midbrain stimulus selection network, dedicated to representing locations of the most salient stimulus in circumstances of concurrent stimuli. Previous competition studies using unimodal (visual) and bimodal (visual and auditory) stimuli have shown that relative strength is encoded in spike response rates. However, open questions remain concerning auditory-auditory competition on coding. To this end, we present diverse auditory competitors (concurrent flat noise and amplitude-modulated noise) and record neural responses of awake barn owls of both sexes in subsequent midbrain space maps, the external nucleus of the inferior colliculus (ICx) and optic tectum (OT). While both ICx and OT exhibit a topographic map of auditory space, OT also integrates visual input and is part of the global-inhibitory midbrain stimulus selection network. Through comparative investigation of these regions, we show that while increasing strength of a competitor sound decreases spike response rates of spatially distant neurons in both regions, relative strength determines spike train synchrony of nearby units only in the OT. Furthermore, changes in synchrony by sound competition in the OT are correlated to gamma range oscillations of local field potentials associated with input from the midbrain stimulus selection network. The results of this investigation suggest that modulations in spiking synchrony between units by gamma oscillations are an emergent coding scheme representing relative strength of concurrent stimuli, which may have relevant implications for downstream readout.

Midbrain signaling of identity prediction errors depends on orbitofrontal cortex networks.

Outcome-guided behavior requires knowledge about the identity of future rewards. Previous work across species has shown that the dopaminergic midbrain responds to violations in expected reward identity and that the lateral orbitofrontal cortex (OFC) represents reward identity expectations. Here we used network-targeted transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) during a trans-reinforcer reversal learning task to test the hypothesis that outcome expectations in the lateral OFC contribute to the computation of identity prediction errors (iPE) in the midbrain. Network-targeted TMS aiming at lateral OFC reduced the global connectedness of the lateral OFC and impaired reward identity learning in the first block of trials. Critically, TMS disrupted neural representations of expected reward identity in the OFC and modulated iPE responses in the midbrain. These results support the idea that iPE signals in the dopaminergic midbrain are computed based on outcome expectations represented in the lateral OFC.

Heterogeneity of mesencephalic dopaminergic neurons: From molecular classifications, electrophysiological properties to functional connectivity.

The mesencephalic dopamine (DA) system is composed of neuronal subtypes that are molecularly and functionally distinct, are responsible for specific behaviors, and are closely associated with numerous brain disorders. Existing research has made significant advances in identifying the heterogeneity of mesencephalic DA neurons, which is necessary for understanding their diverse physiological functions and disease susceptibility. Moreover, there is a conflict regarding the electrophysiological properties of the distinct subsets of midbrain DA neurons. This review aimed to elucidate recent developments in the heterogeneity of midbrain DA neurons, including subpopulation categorization, electrophysiological characteristics, and functional connectivity to provide new strategies for accurately identifying distinct subtypes of midbrain DA neurons and investigating the underlying mechanisms of these neurons in various diseases.

Dissociable Roles of the Auditory Midbrain and Cortex in Processing the Statistical Features of Natural Sound Textures.

Sound texture perception takes advantage of a hierarchy of time-averaged statistical features of acoustic stimuli, but much remains unclear about how these statistical features are processed along the auditory pathway. Here, we compared the neural representation of sound textures in the inferior colliculus (IC) and auditory cortex (AC) of anesthetized female rats. We recorded responses to texture morph stimuli that gradually add statistical features of increasingly higher complexity. For each texture, several different exemplars were synthesized using different random seeds. An analysis of transient and ongoing multiunit responses showed that the IC units were sensitive to every type of statistical feature, albeit to a varying extent. In contrast, only a small proportion of AC units were overtly sensitive to any statistical features. Differences in texture types explained more of the variance of IC neural responses than did differences in exemplars, indicating a degree of "texture type tuning" in the IC, but the same was, perhaps surprisingly, not the case for AC responses. We also evaluated the accuracy of texture type classification from single-trial population activity and found that IC responses became more informative as more summary statistics were included in the texture morphs, while for AC population responses, classification performance remained consistently very low. These results argue against the idea that AC neurons encode sound type via an overt sensitivity in neural firing rate to fine-grain spectral and temporal statistical features.

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

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

The ultrastructure of macaque mesencephalic trigeminal nucleus neurons.

Primary afferents originating from the mesencephalic trigeminal nucleus provide the main source of proprioceptive information guiding mastication, and thus represent an important component of this critical function. Unlike those of other primary afferents, their cell bodies lie within the central nervous system. It is believed that this unusual central location allows them to be regulated by synaptic input. In this study, we explored the ultrastructure of macaque mesencephalic trigeminal nucleus neurons to determine the presence and nature of this synaptic input in a primate. We first confirmed the location of macaque mesencephalic trigeminal neurons by retrograde labeling from the masticatory muscles. Since the labeled neurons were by far the largest cells located at the edge of the periaqueductal gray, we could undertake sampling for electron microscopy based on soma size. Ultrastructurally, mesencephalic trigeminal neurons had very large somata with euchromatic nuclei that sometimes displayed deeply indented nuclear membranes. Terminal profiles with varied vesicle characteristics and synaptic density thicknesses were found in contact with either their somatic plasma membranes or somatic spines. However, in contradistinction to other, much smaller, somata in the region, the plasma membranes of the mesencephalic trigeminal somata had only a few synaptic contacts. They did extend numerous somatic spines of various lengths into the neuropil, but most of these also lacked synaptic contact. The observed ultrastructural organization indicates that macaque trigeminal mesencephalic neurons do receive synaptic contacts, but despite their central location, they only avail themselves of very limited input.

In vitro modeling of the human dopaminergic system using spatially arranged ventral midbrain-striatum-cortex assembloids.

Ventral midbrain dopaminergic neurons project to the striatum as well as the cortex and are involved in movement control and reward-related cognition. In Parkinson's disease, nigrostriatal midbrain dopaminergic neurons degenerate and cause typical Parkinson's disease motor-related impairments, while the dysfunction of mesocorticolimbic midbrain dopaminergic neurons is implicated in addiction and neuropsychiatric disorders. Study of the development and selective neurodegeneration of the human dopaminergic system, however, has been limited due to the lack of an appropriate model and access to human material. Here, we have developed a human in vitro model that recapitulates key aspects of dopaminergic innervation of the striatum and cortex. These spatially arranged ventral midbrain-striatum-cortical organoids (MISCOs) can be used to study dopaminergic neuron maturation, innervation and function with implications for cell therapy and addiction research. We detail protocols for growing ventral midbrain, striatal and cortical organoids and describe how they fuse in a linear manner when placed in custom embedding molds. We report the formation of functional long-range dopaminergic connections to striatal and cortical tissues in MISCOs, and show that injected, ventral midbrain-patterned progenitors can mature and innervate the tissue. Using these assembloids, we examine dopaminergic circuit perturbations and show that chronic cocaine treatment causes long-lasting morphological, functional and transcriptional changes that persist upon drug withdrawal. Thus, our method opens new avenues to investigate human dopaminergic cell transplantation and circuitry reconstruction as well as the effect of drugs on the human dopaminergic system.

Brn3b regulates the formation of fear-related midbrain circuits and defensive responses to visual threat.

Defensive responses to visually threatening stimuli represent an essential fear-related survival instinct, widely detected across species. The neural circuitry mediating visually triggered defensive responses has been delineated in the midbrain. However, the molecular mechanisms regulating the development and function of these circuits remain unresolved. Here, we show that midbrain-specific deletion of the transcription factor Brn3b causes a loss of neurons projecting to the lateral posterior nucleus of the thalamus. Brn3b deletion also down-regulates the expression of the neuropeptide tachykinin 2 (Tac2). Furthermore, Brn3b mutant mice display impaired defensive freezing responses to visual threat precipitated by social isolation. This behavioral phenotype could be ameliorated by overexpressing Tac2, suggesting that Tac2 acts downstream of Brn3b in regulating defensive responses to threat. Together, our experiments identify specific genetic components critical for the functional organization of midbrain fear-related visual circuits. Similar mechanisms may contribute to the development and function of additional long-range brain circuits underlying fear-associated behavior.

The mesencephalic locomotor region recruits V2a reticulospinal neurons to drive forward locomotion in larval zebrafish.

The mesencephalic locomotor region (MLR) is a brain stem area whose stimulation triggers graded forward locomotion. How MLR neurons recruit downstream vsx2+ (V2a) reticulospinal neurons (RSNs) is poorly understood. Here, to overcome this challenge, we uncovered the locus of MLR in transparent larval zebrafish and show that the MLR locus is distinct from the nucleus of the medial longitudinal fasciculus. MLR stimulations reliably elicit forward locomotion of controlled duration and frequency. MLR neurons recruit V2a RSNs via projections onto somata in pontine and retropontine areas, and onto dendrites in the medulla. High-speed volumetric imaging of neuronal activity reveals that strongly MLR-coupled RSNs are active for steering or forward swimming, whereas weakly MLR-coupled medullary RSNs encode the duration and frequency of the forward component. Our study demonstrates how MLR neurons recruit specific V2a RSNs to control the kinematics of forward locomotion and suggests conservation of the motor functions of V2a RSNs across vertebrates.

Human-Like Modulation Sensitivity Emerging through Optimization to Natural Sound Recognition.

Natural sounds contain rich patterns of amplitude modulation (AM), which is one of the essential sound dimensions for auditory perception. The sensitivity of human hearing to AM measured by psychophysics takes diverse forms depending on the experimental conditions. Here, we address with a single framework the questions of why such patterns of AM sensitivity have emerged in the human auditory system and how they are realized by our neural mechanisms. Assuming that optimization for natural sound recognition has taken place during human evolution and development, we examined its effect on the formation of AM sensitivity by optimizing a computational model, specifically, a multilayer neural network, for natural sound (namely, everyday sounds and speech sounds) recognition and simulating psychophysical experiments in which the AM sensitivity of the model was assessed. Relatively higher layers in the model optimized to sounds with natural AM statistics exhibited AM sensitivity similar to that of humans, although the model was not designed to reproduce human-like AM sensitivity. Moreover, simulated neurophysiological experiments on the model revealed a correspondence between the model layers and the auditory brain regions. The layers in which human-like psychophysical AM sensitivity emerged exhibited substantial neurophysiological similarity with the auditory midbrain and higher regions. These results suggest that human behavioral AM sensitivity has emerged as a result of optimization for natural sound recognition in the course of our evolution and/or development and that it is based on a stimulus representation encoded in the neural firing rates in the auditory midbrain and higher regions.SIGNIFICANCE STATEMENT This study provides a computational paradigm to bridge the gap between the behavioral properties of human sensory systems as measured in psychophysics and neural representations as measured in nonhuman neurophysiology. This was accomplished by combining the knowledge and techniques in psychophysics, neurophysiology, and machine learning. As a specific target modality, we focused on the auditory sensitivity to sound AM. We built an artificial neural network model that performs natural sound recognition and simulated psychophysical and neurophysiological experiments in the model. Quantitative comparison of a machine learning model with human and nonhuman data made it possible to integrate the knowledge of behavioral AM sensitivity and neural AM tunings from the perspective of optimization to natural sound recognition.

Development of frequency tuning shaped by spatial cue reliability in the barn owl's auditory midbrain.

Sensory systems preferentially strengthen responses to stimuli based on their reliability at conveying accurate information. While previous reports demonstrate that the brain reweighs cues based on dynamic changes in reliability, how the brain may learn and maintain neural responses to sensory statistics expected to be stable over time is unknown. The barn owl's midbrain features a map of auditory space where neurons compute horizontal sound location from the interaural time difference (ITD). Frequency tuning of midbrain map neurons correlates with the most reliable frequencies for the neurons' preferred ITD (Cazettes et al., 2014). Removal of the facial ruff led to a specific decrease in the reliability of high frequencies from frontal space. To directly test whether permanent changes in ITD reliability drive frequency tuning, midbrain map neurons were recorded from adult owls, with the facial ruff removed during development, and juvenile owls, before facial ruff development. In both groups, frontally tuned neurons were tuned to frequencies lower than in normal adult owls, consistent with the change in ITD reliability. In addition, juvenile owls exhibited more heterogeneous frequency tuning, suggesting normal developmental processes refine tuning to match ITD reliability. These results indicate causality of long-term statistics of spatial cues in the development of midbrain frequency tuning properties, implementing probabilistic coding for sound localization.

Upregulation of breathing rate during running exercise by central locomotor circuits in mice.

While respiratory adaptation to exercise is compulsory to cope with the increased metabolic demand, the neural signals at stake remain poorly identified. Using neural circuit tracing and activity interference strategies in mice, we uncover here two systems by which the central locomotor network can enable respiratory augmentation in relation to running activity. One originates in the mesencephalic locomotor region (MLR), a conserved locomotor controller. Through direct projections onto the neurons of the preBötzinger complex that generate the inspiratory rhythm, the MLR can trigger a moderate increase of respiratory frequency, prior to, or even in the absence of, locomotion. The other is the lumbar enlargement of the spinal cord containing the hindlimb motor circuits. When activated, and through projections onto the retrotrapezoid nucleus (RTN), it also potently upregulates breathing rate. On top of identifying critical underpinnings for respiratory hyperpnea, these data also expand the functional implication of cell types and pathways that are typically regarded as "locomotor" or "respiratory" related.