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.

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.

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.

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.

Brainstem neural mechanisms controlling locomotion with special reference to basal vertebrates.

Over the last 60 years, the basic neural circuitry responsible for the supraspinal control of locomotion has progressively been uncovered. Initially, significant progress was made in identifying the different supraspinal structures controlling locomotion in mammals as well as some of the underlying mechanisms. It became clear, however, that the complexity of the mammalian central nervous system (CNS) prevented researchers from characterizing the detailed cellular mechanisms involved and that animal models with a simpler nervous system were needed. Basal vertebrate species such as lampreys, xenopus embryos, and zebrafish became models of choice. More recently, optogenetic approaches have considerably revived interest in mammalian models. The mesencephalic locomotor region (MLR) is an important brainstem region known to control locomotion in all vertebrate species examined to date. It controls locomotion through intermediary cells in the hindbrain, the reticulospinal neurons (RSNs). The MLR comprises populations of cholinergic and glutamatergic neurons and their specific contribution to the control of locomotion is not fully resolved yet. Moreover, the downward projections from the MLR to RSNs is still not fully understood. Reporting on discoveries made in different animal models, this review article focuses on the MLR, its projections to RSNs, and the contribution of these neural elements to the control of locomotion. Excellent and detailed reviews on the brainstem control of locomotion have been recently published with emphasis on mammalian species. The present review article focuses on findings made in basal vertebrates such as the lamprey, to help direct new research in mammals, including humans.

Interhemispheric competition during sleep.

Our understanding of the functions and mechanisms of sleep remains incomplete, reflecting their increasingly evident complexity1-3. Likewise, studies of interhemispheric coordination during sleep4-6 are often hard to connect precisely to known sleep circuits and mechanisms. Here, by recording from the claustra of sleeping bearded dragons (Pogona vitticeps), we show that, although the onsets and offsets of Pogona rapid-eye-movement (REMP) and slow-wave sleep are coordinated bilaterally, these two sleep states differ markedly in their inter-claustral coordination. During slow-wave sleep, the claustra produce sharp-wave ripples independently of one another, showing no coordination. By contrast, during REMP sleep, the potentials produced by the two claustra are precisely coordinated in amplitude and time. These signals, however, are not synchronous: one side leads the other by about 20 ms, with the leading side switching typically once per REMP episode or in between successive episodes. The leading claustrum expresses the stronger activity, suggesting bilateral competition. This competition does not occur directly between the two claustra or telencephalic hemispheres. Rather, it occurs in the midbrain and depends on the integrity of a GABAergic (γ-aminobutyric-acid-producing) nucleus of the isthmic complex, which exists in all vertebrates and is known in birds to underlie bottom-up attention and gaze control. These results reveal that a winner-take-all-type competition exists between the two sides of the brain of Pogona, which originates in the midbrain and has precise consequences for claustrum activity and coordination during REMP sleep.

Mesencephalic locomotor region stimulation-cuneiform or pedunculopontine?

Roussel et al.1 provide new insight into mecencephalic locomotor region (MLR) stimulation to treat spinal cord injury in mice. Previously, it was unclear which part of the MLR to target. Now, evidence converges on cuneiform nucleus activation.

Functional contribution of mesencephalic locomotor region nuclei to locomotor recovery after spinal cord injury.

Spinal cord injury (SCI) results in a disruption of information between the brain and the spinal circuit. Electrical stimulation of the mesencephalic locomotor region (MLR) can promote locomotor recovery in acute and chronic SCI rodent models. Although clinical trials are currently under way, there is still debate about the organization of this supraspinal center and which anatomic correlate of the MLR should be targeted to promote recovery. Combining kinematics, electromyographic recordings, anatomic analysis, and mouse genetics, our study reveals that glutamatergic neurons of the cuneiform nucleus contribute to locomotor recovery by enhancing motor efficacy in hindlimb muscles, and by increasing locomotor rhythm and speed on a treadmill, over ground, and during swimming in chronic SCI mice. In contrast, glutamatergic neurons of the pedunculopontine nucleus slow down locomotion. Therefore, our study identifies the cuneiform nucleus and its glutamatergic neurons as a therapeutical target to improve locomotor recovery in patients living with SCI.

Multi-timescale analysis of midbrain dopamine neuronal firing activities.

Midbrain dopamine (DA) neurons exhibit spiking and bursting patterns under physiological conditions. Based on the data on electrophysiological recordings, Yu et al. developed a 13-dimensional mathematical model to capture the detailed characteristics of the DA neuronal firing activities. We use the fitting method to simplify the original model into a 4-dimensional model. Then, the spiking-to-bursting transition is detected from a simple and robust mathematical condition. Physiologically, this condition is a balance of the restorative and the regenerative ion channels at resting potential. Geometrically, this condition imposes a transcritical bifurcation. Moreover, we combine singularity theory and singular perturbation methods to capture the geometry of three-timescale firing attractors in a universal unfolding of a cusp singularity. In particular, the planar description of the corresponding firing patterns can generate the corresponding firing attractors. This analysis provides a new idea for understanding the firing activities of the DA neuron and the specific mechanisms for the switching and dynamic regulation among different patterns.

Diversity of temporal response patterns in midbrain auditory neurons of frogs Batrachyla and its relevance for male vocal responses.

We investigated response selectivities of single auditory neurons in the torus semicircularis of male frogs Batrachyla leptopus (72 neurons) and B. taeniata (57 neurons) to synthetic stimuli of different temporal structures. Series of stimuli in which note and pulse rate, note and pulse structure and call duration varied systematically were presented. Neuronal responses quantified in terms of proportions of units displaying diverse temporal transfer functions are related in different modes with patterns of evoked vocal responses studied previously in these frogs. Correspondences and mismatches occurred between the auditory and vocal domains. The analysis of this evidence together with corresponding information from previous neuronal and behavioral studies in the third species of this genus, B. antartandica, indicates that different modes of preferences for acoustic communication signals can coexist within this anuran group.