Self-supervised learning for interventional image analytics: toward robust device trackers

Purpose

The accurate detection and tracking of devices, such as guiding catheters in live X-ray image acquisitions, are essential prerequisites for endovascular cardiac interventions. This information is leveraged for procedural guidance, e.g., directing stent placements. To ensure procedural safety and efficacy, there is a need for high robustness/no failures during tracking. To achieve this, one needs to efficiently tackle challenges, such as device obscuration by the contrast agent or other external devices or wires and changes in the field-of-view or acquisition angle, as well as the continuous movement due to cardiac and respiratory motion.

Approach

To overcome the aforementioned challenges, we propose an approach to learn spatio-temporal features from a very large data cohort of over 16 million interventional X-ray frames using self-supervision for image sequence data. Our approach is based on a masked image modeling technique that leverages frame interpolation-based reconstruction to learn fine inter-frame temporal correspondences. The features encoded in the resulting model are fine-tuned downstream in a light-weight model.

Results

Our approach achieves state-of-the-art performance, in particular for robustness, compared to ultra optimized reference solutions (that use multi-stage feature fusion or multi-task and flow regularization). The experiments show that our method achieves a 66.31% reduction in the maximum tracking error against the reference solutions (23.20% when flow regularization is used), achieving a success score of 97.95% at a 3 × faster inference speed of 42 frames-per-second (on GPU). In addition, we achieve a 20% reduction in the standard deviation of errors, which indicates a much more stable tracking performance.

Conclusions

The proposed data-driven approach achieves superior performance, particularly in robustness and speed compared with the frequently used multi-modular approaches for device tracking. The results encourage the use of our approach in various other tasks within interventional image analytics that require effective understanding of spatio-temporal semantics.

Distinct information conveyed to the olfactory bulb by feedforward input from the nose and feedback from the cortex

Sensory systems are organized hierarchically, but feedback projections frequently disrupt this order. In the olfactory bulb (OB), cortical feedback projections numerically match sensory inputs. To unravel information carried by these two streams, we imaged the activity of olfactory sensory neurons (OSNs) and cortical axons in the mouse OB using calcium indicators, multiphoton microscopy, and diverse olfactory stimuli. Here, we show that odorant mixtures of increasing complexity evoke progressively denser OSN activity, yet cortical feedback activity is of similar sparsity for all stimuli. Also, representations of complex mixtures are similar in OSNs but are decorrelated in cortical axons. While OSN responses to increasing odorant concentrations exhibit a sigmoidal relationship, cortical axonal responses are complex and nonmonotonic, which can be explained by a model with activity-dependent feedback inhibition in the cortex. Our study indicates that early-stage olfactory circuits have access to local feedforward signals and global, efficiently formatted information about odor scenes through cortical feedback.

Interpretable deep learning for deconvolutional analysis of neural signals

The widespread adoption of deep learning to build models that capture the dynamics of neural populations is typically based on "black-box" approaches that lack an interpretable link between neural activity and function. Here, we propose to apply algorithm unrolling, a method for interpretable deep learning, to design the architecture of sparse deconvolutional neural networks and obtain a direct interpretation of network weights in relation to stimulus-driven single-neuron activity through a generative model. We characterize our method, referred to as deconvolutional unrolled neural learning (DUNL), and show its versatility by applying it to deconvolve single-trial local signals across multiple brain areas and recording modalities. To exemplify use cases of our decomposition method, we uncover multiplexed salience and reward prediction error signals from midbrain dopamine neurons in an unbiased manner, perform simultaneous event detection and characterization in somatosensory thalamus recordings, and characterize the responses of neurons in the piriform cortex. Our work leverages the advances in interpretable deep learning to gain a mechanistic understanding of neural dynamics.

Adaptive algorithms for shaping behavior

Dogs and laboratory mice are commonly trained to perform complex tasks by guiding them through a curriculum of simpler tasks ('shaping'). What are the principles behind effective shaping strategies? Here, we propose a machine learning framework for shaping animal behavior, where an autonomous teacher agent decides its student's task based on the student's transcript of successes and failures on previously assigned tasks. Using autonomous teachers that plan a curriculum in a common sequence learning task, we show that near-optimal shaping algorithms adaptively alternate between simpler and harder tasks to carefully balance reinforcement and extinction. Based on this intuition, we derive an adaptive shaping heuristic with minimal parameters, which we show is near-optimal on the sequence learning task and robustly trains deep reinforcement learning agents on navigation tasks that involve sparse, delayed rewards. Extensions to continuous curricula are explored. Our work provides a starting point towards a general computational framework for shaping animal behavior.

Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb

Within a single sniff, the mammalian olfactory system can decode the identity and concentration of odorants wafted on turbulent plumes of air. Yet, it must do so given access only to the noisy, dimensionally-reduced representation of the odor world provided by olfactory receptor neurons. As a result, the olfactory system must solve a compressed sensing problem, relying on the fact that only a handful of the millions of possible odorants are present in a given scene. Inspired by this principle, past works have proposed normative compressed sensing models for olfactory decoding. However, these models have not captured the unique anatomy and physiology of the olfactory bulb, nor have they shown that sensing can be achieved within the 100-millisecond timescale of a single sniff. Here, we propose a rate-based Poisson compressed sensing circuit model for the olfactory bulb. This model maps onto the neuron classes of the olfactory bulb, and recapitulates salient features of their connectivity and physiology. For circuit sizes comparable to the human olfactory bulb, we show that this model can accurately detect tens of odors within the timescale of a single sniff. We also show that this model can perform Bayesian posterior sampling for accurate uncertainty estimation. Fast inference is possible only if the geometry of the neural code is chosen to match receptor properties, yielding a distributed neural code that is not axis-aligned to individual odor identities. Our results illustrate how normative modeling can help us map function onto specific neural circuits to generate new hypotheses.

Nonequilibrium sensing of volatile compounds using active and passive analyte delivery

Although sensor technologies have allowed us to outperform the human senses of sight, hearing, and touch, the development of artificial noses is significantly behind their biological counterparts. This largely stems from the sophistication of natural olfaction, which relies on both fluid dynamics within the nasal anatomy and the response patterns of hundreds to thousands of unique molecular-scale receptors. We designed a sensing approach to identify volatiles inspired by the fluid dynamics of the nose, allowing us to extract information from a single sensor (here, the reflectance spectra from a mesoporous one-dimensional photonic crystal) rather than relying on a large sensor array. By accentuating differences in the nonequilibrium mass-transport dynamics of vapors and training a machine learning algorithm on the sensor output, we clearly identified polar and nonpolar volatile compounds, determined the mixing ratios of binary mixtures, and accurately predicted the boiling point, flash point, vapor pressure, and viscosity of a number of volatile liquids, including several that had not been used for training the model. We further implemented a bioinspired active sniffing approach, in which the analyte delivery was performed in well-controlled 'inhale-exhale' sequences, enabling an additional modality of differentiation and reducing the duration of data collection and analysis to seconds. Our results outline a strategy to build accurate and rapid artificial noses for volatile compounds that can provide useful information such as the composition and physical properties of chemicals, and can be applied in a variety of fields, including disease diagnosis, hazardous waste management, and healthy building monitoring.

Experience-dependent evolution of odor mixture representations in piriform cortex

Rodents can learn from exposure to rewarding odors to make better and quicker decisions. The piriform cortex is thought to be important for learning complex odor associations; however, it is not understood exactly how it learns to remember discriminations between many, sometimes overlapping, odor mixtures. We investigated how odor mixtures are represented in the posterior piriform cortex (pPC) of mice while they learn to discriminate a unique target odor mixture against hundreds of nontarget mixtures. We find that a significant proportion of pPC neurons discriminate between the target and all other nontarget odor mixtures. Neurons that prefer the target odor mixture tend to respond with brief increases in firing rate at odor onset compared to other neurons, which exhibit sustained and/or decreased firing. We allowed mice to continue training after they had reached high levels of performance and find that pPC neurons become more selective for target odor mixtures as well as for randomly chosen repeated nontarget odor mixtures that mice did not have to discriminate from other nontargets. These single unit changes during overtraining are accompanied by better categorization decoding at the population level, even though behavioral metrics of mice such as reward rate and latency to respond do not change. However, when difficult ambiguous trial types are introduced, the robustness of the target selectivity is correlated with better performance on the difficult trials. Taken together, these data reveal pPC as a dynamic and robust system that can optimize for both current and possible future task demands at once.

Distinct representation of cue-outcome association by D1 and D2 neurons in the ventral striatum's olfactory tubercle

Positive and negative associations acquired through olfactory experience are thought to be especially strong and long-lasting. The conserved direct olfactory sensory input to the ventral striatal olfactory tubercle (OT) and its convergence with dense dopaminergic input to the OT could underlie this privileged form of associative memory, but how this process occurs is not well understood. We imaged the activity of the two canonical types of striatal neurons, expressing D1- or D2-type dopamine receptors, in the OT at cellular resolution while mice learned odor-outcome associations ranging from aversive to rewarding. D1 and D2 neurons both responded to rewarding and aversive odors. D1 neurons in the OT robustly and bidirectionally represented odor valence, responding similarly to odors predicting similar outcomes regardless of odor identity. This valence representation persisted even in the absence of a licking response to the odors and in the absence of the outcomes, indicating a true transformation of odor sensory information by D1 OT neurons. In contrast, D2 neuronal representation of the odor-outcome associations was weaker, contingent on a licking response by the mouse, and D2 neurons were more selective for odor identity than valence. Stimulus valence coding in the OT was modality-sensitive, with separate sets of D1 neurons responding to odors and sounds predicting the same outcomes, suggesting that integration of multimodal valence information happens downstream of the OT. Our results point to distinct representation of identity and valence of odor stimuli by D1 and D2 neurons in the OT.

Multi-animal pose estimation, identification and tracking with DeepLabCut

Estimating the pose of multiple animals is a challenging computer vision problem: frequent interactions cause occlusions and complicate the association of detected keypoints to the correct individuals, as well as having highly similar looking animals that interact more closely than in typical multi-human scenarios. To take up this challenge, we build on DeepLabCut, an open-source pose estimation toolbox, and provide high-performance animal assembly and tracking-features required for multi-animal scenarios. Furthermore, we integrate the ability to predict an animal's identity to assist tracking (in case of occlusions). We illustrate the power of this framework with four datasets varying in complexity, which we release to serve as a benchmark for future algorithm development.

Natural gradient enables fast sampling in spiking neural networks

For animals to navigate an uncertain world, their brains need to estimate uncertainty at the timescales of sensations and actions. Sampling-based algorithms afford a theoretically-grounded framework for probabilistic inference in neural circuits, but it remains unknown how one can implement fast sampling algorithms in biologically-plausible spiking networks. Here, we propose to leverage the population geometry, controlled by the neural code and the neural dynamics, to implement fast samplers in spiking neural networks. We first show that two classes of spiking samplers-efficient balanced spiking networks that simulate Langevin sampling, and networks with probabilistic spike rules that implement Metropolis-Hastings sampling-can be unified within a common framework. We then show that careful choice of population geometry, corresponding to the natural space of parameters, enables rapid inference of parameters drawn from strongly-correlated high-dimensional distributions in both networks. Our results suggest design principles for algorithms for sampling-based probabilistic inference in spiking neural networks, yielding potential inspiration for neuromorphic computing and testable predictions for neurobiology.

Dynamics of cooperative excavation in ant and robot collectives

The solution of complex problems by the collective action of simple agents in both biologically evolved and synthetically engineered systems involves cooperative action. Understanding the resulting emergent solutions requires integrating across the organismal behavior of many individuals. Here, we investigate an ecologically relevant collective task in black carpenter ants Camponotus pennsylvanicus: excavation of a soft, erodible confining corral. These ants show a transition from individual exploratory excavation at random locations to spatially localized collective exploitative excavation and escape from the corral. Agent-based simulations and a minimal continuum theory that coarse-grains over individual actions and considers their integrated influence on the environment leads to the emergence of an effective phase space of behaviors, characterized in terms of excavation strength and cooperation intensity. To test the theory over the range of both observed and predicted behaviors, we use custom-built robots (RAnts) that respond to stimuli to characterize the phase space of emergence (and failure) of cooperative excavation. Tuning the amount of cooperation between RAnts, allows us to vary the efficiency of excavation and synthetically generate the entire range of macroscopic phases predicted by our theory. Overall, our approach shows how the cooperative completion of tasks can arise from simple rules that involve the interaction of agents with a dynamically changing environment that serves as both an enabler and a modulator of behavior.

Deletion of TrkB in parvalbumin interneurons alters cortical neural dynamics

Signaling by neurotrophins such as the brain‐derived neurotrophic factor (BDNF) is known to modulate development of interneurons, but the circuit effects of this modulation remain unclear. Here, we examined the impact of deleting TrkB, a BDNF receptor, in parvalbumin‐expressing (PV) interneurons on the balance of excitation and inhibition (E‐I) in cortical circuits. In the mouse olfactory cortex, TrkB deletion impairs multiple aspects of PV neuronal function including synaptic excitation, intrinsic excitability, and the innervation pattern of principal neurons. Impaired PV cell function resulted in aberrant spiking patterns in principal neurons in response to stimulation of sensory inputs. Surprisingly, dampened PV neuronal function leads to a paradoxical decrease in overall excitability in cortical circuits. Our study demonstrates that, by modulating PV circuit plasticity and development, TrkB plays a critical role in shaping the evoked pattern of activity in a cortical network.

Antagonistic odor interactions in olfactory sensory neurons are widespread in freely breathing mice

Odor landscapes contain complex blends of molecules that each activate unique, overlapping populations of olfactory sensory neurons (OSNs). Despite the presence of hundreds of OSN subtypes in many animals, the overlapping nature of odor inputs may lead to saturation of neural responses at the early stages of stimulus encoding. Information loss due to saturation could be mitigated by normalizing mechanisms such as antagonism at the level of receptor-ligand interactions, whose existence and prevalence remains uncertain. By imaging OSN axon terminals in olfactory bulb glomeruli as well as OSN cell bodies within the olfactory epithelium in freely breathing mice, we find widespread antagonistic interactions in binary odor mixtures. In complex mixtures of up to 12 odorants, antagonistic interactions are stronger and more prevalent with increasing mixture complexity. Therefore, antagonism is a common feature of odor mixture encoding in OSNs and helps in normalizing activity to reduce saturation and increase information transfer.

Microglial depletion disrupts normal functional development of adult-born neurons in the olfactory bulb

Microglia play key roles in regulating synapse development and refinement in the developing brain, but it is unknown whether they are similarly involved during adult neurogenesis. By transiently depleting microglia from the healthy adult mouse brain, we show that microglia are necessary for the normal functional development of adult-born granule cells (abGCs) in the olfactory bulb. Microglial depletion reduces the odor responses of developing, but not preexisting GCs in vivo in both awake and anesthetized mice. Microglia preferentially target their motile processes to interact with mushroom spines on abGCs, and when microglia are absent, abGCs develop smaller spines and receive weaker excitatory synaptic inputs. These results suggest that microglia promote the development of excitatory synapses onto developing abGCs, which may impact the function of these cells in the olfactory circuit.

Mosaic representations of odors in the input and output layers of the mouse olfactory bulb

The elementary stimulus features encoded by the olfactory system remain poorly understood. We examined the relationship between 1,666 physical-chemical descriptors of odors and the activity of olfactory bulb inputs and outputs in awake mice. Glomerular and mitral and tufted cell responses were sparse and locally heterogeneous, with only a weak dependence of their positions on physical-chemical properties. Odor features represented by ensembles of mitral and tufted cells were overlapping but distinct from those represented in glomeruli, which is consistent with an extensive interplay between feedforward and feedback inputs to the bulb. This reformatting was well described as a rotation in odor space. The physical-chemical descriptors accounted for a small fraction in response variance, and the similarity of odors in the physical-chemical space was a poor predictor of similarity in neuronal representations. Our results suggest that commonly used physical-chemical properties are not systematically represented in bulbar activity and encourage further searches for better descriptors of odor space.

Neuronal integration in the adult mouse olfactory bulb is a non-selective addition process

Adult neurogenesis in the olfactory bulb (OB) is considered as a competition in which neurons scramble during a critical selection period for integration and survival. Moreover, newborn neurons are thought to replace pre-existing ones that die. Despite indirect evidence supporting this model, systematic in vivo observations are still scarce. We used two-photon in vivo imaging to study neuronal integration and survival. We show that loss of new neurons in the OB after arrival at terminal positions occurs only at low levels. Moreover, long-term observations showed that no substantial cell death occurred at later stages. Neuronal death was induced by standard doses of thymidine analogs, but disappeared when low doses were used. Finally, we demonstrate that the OB grows throughout life. This shows that neuronal selection during OB-neurogenesis does not occur after neurons reached stable positions. Moreover, this suggests that OB neurogenesis does not represent neuronal turnover but lifelong neuronal addition.

Carpenter ants use diverse antennae sampling strategies to track odor trails

Directed and meaningful animal behavior depends on the ability to sense key features in the environment. Among the different environmental signals, olfactory cues are critically important for foraging, navigation and social communication in many species, including ants. Ants use their two antennae to explore the olfactory world, but how they do so remains largely unknown. In this study, we used high-resolution videography to characterize the antennae dynamics of carpenter ants (Camponotus pennsylvanicus). Antennae are highly active during both odor tracking and exploratory behavior. When tracking, ants used several distinct behavioral strategies with stereotyped antennae sampling patterns (which we call 'sinusoidal', 'probing' and 'trail following'). In all behaviors, left and right antennae movements were anti-correlated, and tracking ants exhibited biases in the use of left versus right antenna to sample the odor trail. These results suggest non-redundant roles for the two antennae. In one of the behavioral modules (trail following), ants used both antennae to detect trail edges and direct subsequent turns, suggesting a specialized form of tropotaxis. Lastly, removal of an antenna resulted not only in less accurate tracking but also in changes in the sampling pattern of the remaining antenna. Our quantitative characterization of odor trail tracking lays a foundation to build better models of olfactory sensory processing and sensorimotor behavior in terrestrial insects.

Calcium-activated chloride channels clamp odor-evoked spike activity in olfactory receptor neurons

The calcium-activated chloride channel anoctamin-2 (Ano2) is thought to amplify transduction currents in olfactory receptor neurons (ORNs), a hypothesis supported by previous studies in dissociated neurons from Ano2^−/− mice. Paradoxically, despite a reduction in transduction currents in Ano2^−/− ORNs, their spike output for odor stimuli may be higher. We examined the role of Ano2 in ORNs in their native environment in freely breathing mice by imaging activity in ORN axons as they arrive in the olfactory bulb glomeruli. Odor-evoked responses in ORN axons of Ano2^−/− animals were consistently larger for a variety of odorants and concentrations. In an open arena, Ano2^−/− animals took longer to approach a localized odor source than Ano2^+/+ animals, revealing clear olfactory behavioral deficits. Our studies provide the first in vivo evidence toward an alternative or additional role for Ano2 in the olfactory transduction cascade, where it may serve as a feedback mechanism to clamp ORN spike output.

How to monitor breathing in laboratory rodents: a review of the current methods

Accurately measuring respiration in laboratory rodents is essential for many fields of research, including olfactory neuroscience, social behavior, learning and memory, and respiratory physiology. However, choosing the right technique to monitor respiration can be tricky, given the many criteria to take into account: reliability, precision, and invasiveness, to name a few. This review aims to assist experimenters in choosing the technique that will best fit their needs, by surveying the available tools, discussing their strengths and weaknesses, and offering suggestions for future improvements.

Antagonism in olfactory receptor neurons and its implications for the perception of odor mixtures

Natural environments feature mixtures of odorants of diverse quantities, qualities and complexities. Olfactory receptor neurons (ORNs) are the first layer in the sensory pathway and transmit the olfactory signal to higher regions of the brain. Yet, the response of ORNs to mixtures is strongly non-additive, and exhibits antagonistic interactions among odorants. Here, we model the processing of mixtures by mammalian ORNs, focusing on the role of inhibitory mechanisms. We show how antagonism leads to an effective ‘normalization’ of the ensemble ORN response, that is, the distribution of responses of the ORN population induced by any mixture is largely independent of the number of components in the mixture. This property arises from a novel mechanism involving the distinct statistical properties of receptor binding and activation, without any recurrent neuronal circuitry. Normalization allows our encoding model to outperform non-interacting models in odor discrimination tasks, leads to experimentally testable predictions and explains several psychophysical experiments in humans.

When ordering in a coffee shop, you probably recognize and enjoy the aroma of freshly roasted coffee beans. But as well as coffee, you can also smell the croissants behind the counter and maybe even the perfume or cologne of the person next to you. Each of these scents consists of a collection of chemicals, or odorants. To distinguish between the aroma of coffee and that of croissants, your brain must group the odorants appropriately and then keep the groups separate from each other.

This is not a trivial task. Odorants bind to proteins called odorant receptors found on the surface of cells in the nose called olfactory receptor neurons. But each odorant does not have its own dedicated receptor. Instead, a single odorant will bind to multiple types of odorant receptors, and thus, each olfactory receptor neuron may respond to multiple odorants. So how does the brain encode mixtures of odorants in a way that allows us to distinguish one aroma from another?

Reddy, Zak et al. have developed a computational model to explain how this process works. The model assumes that an odorant triggers a response in an olfactory receptor neuron via two steps. First, the odorant binds to an odorant receptor. Second, the bound odorant activates the receptor. But the odorant that binds most strongly to a receptor will not necessarily be the odorant that is best at activating that receptor.

This allows a phenomenon called competitive antagonism to occur. This is when one odorant in a mixture binds more strongly to a receptor than the other odorants, but only weakly activates that receptor. In so doing, the strongly bound odorant prevents the other odorants from binding to and activating the receptor. This helps tame the dominating influence of background odors, which might otherwise saturate the responses of individual olfactory receptor neurons.

Reddy, Zak et al. show that processes such as competitive antagonism enable olfactory receptor neurons to encode all of the odors within a mixture. The model can explain various phenomena observed in experiments and it adds to our understanding of how the brain generates our sense of smell. The model may also be relevant to other biological systems that must filter weak signals from a dominant background. These include the immune system, which must distinguish a small set of foreign proteins from the much larger number of proteins that make up our bodies.

Embryonic and postnatal neurogenesis produce functionally distinct subclasses of dopaminergic neuron

Most neurogenesis in the mammalian brain is completed embryonically, but in certain areas the production of neurons continues throughout postnatal life. The functional properties of mature postnatally generated neurons often match those of their embryonically produced counterparts. However, we show here that in the olfactory bulb (OB), embryonic and postnatal neurogenesis produce functionally distinct subpopulations of dopaminergic (DA) neurons. We define two subclasses of OB DA neuron by the presence or absence of a key subcellular specialisation: the axon initial segment (AIS). Large AIS-positive axon-bearing DA neurons are exclusively produced during early embryonic stages, leaving small anaxonic AIS-negative cells as the only DA subtype generated via adult neurogenesis. These populations are functionally distinct: large DA cells are more excitable, yet display weaker and - for certain long-latency or inhibitory events - more broadly tuned responses to odorant stimuli. Embryonic and postnatal neurogenesis can therefore generate distinct neuronal subclasses, placing important constraints on the functional roles of adult-born neurons in sensory processing.

Developmentally primed cortical neurons maintain fidelity of differentiation and establish appropriate functional connectivity after transplantation

Repair of complex CNS circuitry requires newly incorporated neurons to become appropriately, functionally integrated. One approach is to direct differentiation of endogenous progenitors in situ, or ex vivo followed by transplantation. Prior studies find that newly incorporated neurons can establish long-distance axon projections, form synapses and functionally integrate in evolutionarily old hypothalamic energy-balance circuitry. We now demonstrate that postnatal neocortical connectivity can be reconstituted with point-to-point precision, including cellular integration of specific, molecularly identified projection neuron subtypes into correct positions, combined with development of appropriate long-distance projections and synapses. Using optogenetics-based electrophysiology, experiments demonstrate functional afferent and efferent integration of transplanted neurons into transcallosal projection neuron circuitry. Results further indicate that 'primed' early postmitotic neurons, including already fate-restricted deep-layer projection neurons and/or plastic postmitotic neuroblasts with partially fate-restricted potential, account for the predominant population of neurons capable of achieving this optimal level of integration.

Development and Refinement of Functional Properties of Adult-Born Neurons

New neurons appear only in a few regions of the adult mammalian brain and become integrated into existing circuits. Little is known about the functional development of individual neurons in vivo. We examined the functional life history of adult-born granule cells (abGCs) in the olfactory bulb using multiphoton imaging in awake and anesthetized mice. We found that abGCs can become responsive to odorants soon after they arrive in the olfactory bulb. Tracking identified abGCs over weeks revealed that the robust and broadly tuned responses of most newly arrived abGCs gradually become more selective over a period of ∼3 weeks, but a small fraction achieves broader tuning with maturation. Enriching the olfactory environment of mice prolonged the period over which abGCs were strongly and broadly responsive to odorants. Our data offer direct support for rapid integration of adult-born neurons into existing circuits, followed by experience-dependent refinement of their functional connectivity.

Neuronal Representation of Social Information in the Medial Amygdala of Awake Behaving Mice

The medial amygdala (MeA) plays a critical role in processing species- and sex-specific signals that trigger social and defensive behaviors. However, the principles by which this deep brain structure encodes social information is poorly understood. We used a miniature microscope to image the Ca²⁺ dynamics of large neural ensembles in awake behaving mice and tracked the responses of MeA neurons over several months. These recordings revealed spatially intermingled subsets of MeA neurons with distinct temporal dynamics. The encoding of social information in the MeA differed between males and females and relied on information from both individual cells and neuronal populations. By performing long-term Ca²⁺ imaging across different social contexts, we found that sexual experience triggers lasting and sex-specific changes in MeA activity, which, in males, involve signaling by oxytocin. These findings reveal basic principles underlying the brain's representation of social information and its modulation by intrinsic and extrinsic factors.

Distinct projection patterns of different classes of layer 2 principal neurons in the olfactory cortex

The broadly-distributed, non-topographic projections to and from the olfactory cortex may suggest a flat, non-hierarchical organization in odor information processing. Layer 2 principal neurons in the anterior piriform cortex (APC) can be divided into 2 subtypes: semilunar (SL) and superficial pyramidal (SP) cells. Although it is known that SL and SP cells receive differential inputs from the olfactory bulb (OB), little is known about their projections to other olfactory regions. Here, we examined axonal projections of SL and SP cells using a combination of mouse genetics and retrograde labeling. Retrograde tracing from the OB or posterior piriform cortex (PPC) showed that the APC projects to these brain regions mainly through layer 2b cells, and dual-labeling revealed many cells extending collaterals to both target regions. Furthermore, a transgenic mouse line specifically labeling SL cells showed that they send profuse axonal projections to olfactory cortical areas, but not to the OB. These findings support a model in which information flow from SL to SP cells and back to the OB is mediated by a hierarchical feedback circuit, whereas both SL and SP cells broadcast information to higher olfactory areas in a parallel manner.

Reading Out Olfactory Receptors: Feedforward Circuits Detect Odors in Mixtures without Demixing

The olfactory system, like other sensory systems, can detect specific stimuli of interest amidst complex, varying backgrounds. To gain insight into the neural mechanisms underlying this ability, we imaged responses of mouse olfactory bulb glomeruli to mixtures. We used this data to build a model of mixture responses that incorporated nonlinear interactions and trial-to-trial variability and explored potential decoding mechanisms that can mimic mouse performance when given glomerular responses as input. We find that a linear decoder with sparse weights could match mouse performance using just a small subset of the glomeruli (∼15). However, when such a decoder is trained only with single odors, it generalizes poorly to mixture stimuli due to nonlinear mixture responses. We show that mice similarly fail to generalize, suggesting that they learn this segregation task discriminatively by adjusting task-specific decision boundaries without taking advantage of a demixed representation of odors.

Population imaging at subcellular resolution supports specific and local inhibition by granule cells in the olfactory bulb

Information processing in early sensory regions is modulated by a diverse range of inhibitory interneurons. We sought to elucidate the role of olfactory bulb interneurons called granule cells (GCs) in odor processing by imaging the activity of hundreds of these cells simultaneously in mice. Odor responses in GCs were temporally diverse and spatially disperse, with some degree of non-random, modular organization. The overall sparseness of activation of GCs was highly correlated with the extent of glomerular activation by odor stimuli. Increasing concentrations of single odorants led to proportionately larger population activity, but some individual GCs had non-monotonic relations to concentration due to local inhibitory interactions. Individual dendritic segments could sometimes respond independently to odors, revealing their capacity for compartmentalized signaling in vivo. Collectively, the response properties of GCs point to their role in specific and local processing, rather than global operations such as response normalization proposed for other interneurons.

Mice Develop Efficient Strategies for Foraging and Navigation Using Complex Natural Stimuli

The ability to shift between multiple decision-making strategies during natural behavior allows animals to strike a balance between flexibility and efficiency. We investigated odor-guided navigation by mice to understand how decision-making strategies are balanced during a complex natural behavior. Mice navigated to odor sources in an open arena using naturally fluctuating airborne odor cues as their positions were recorded precisely in real time. When mice had limited prior experience of source locations, their search behavior was consistent with a gradient ascent algorithm that utilized directional cues in the plume to navigate to the odor source. Gradient climbing was effective because the arena size allowed animals to conduct their search mainly within the odor plume, with frequent odor contacts. With increased experience, mice shifted their strategy from this flexible, sensory-driven search behavior to a more efficient and stereotyped foraging approach that varied little in response to odor plumes. This study demonstrates that mice use prior knowledge to adaptively balance flexibility and efficiency during complex behavior guided by dynamic natural stimuli.

Analysis and synthesis in olfaction

Natural environments contain numerous volatile compounds emanating from a large number of sources, and the survival of many animals depends on their ability to segregate odors of interest within complex odorous scenes. In a recent paper, we described how the ability of mice to detect odors within mixtures depends on the chemical structure and neural representation of the target and background odorants.

All-optical electrophysiology in mammalian neurons using engineered microbial rhodopsins

All-optical electrophysiology—spatially resolved simultaneous optical perturbation and measurement of membrane voltage—would open new vistas in neuroscience research. We evolved two archaerhodopsin-based voltage indicators, QuasAr1 and 2, which show improved brightness and voltage sensitivity, microsecond response times, and produce no photocurrent. We engineered a novel channelrhodopsin actuator, CheRiff, which shows improved light sensitivity and kinetics, and spectral orthogonality to the QuasArs. A co-expression vector, Optopatch, enabled crosstalk-free genetically targeted all-optical electrophysiology. In cultured neurons, we combined Optopatch with patterned optical excitation to probe back-propagating action potentials in dendritic spines, synaptic transmission, sub-cellular microsecond-timescale details of action potential propagation, and simultaneous firing of many neurons in a network. Optopatch measurements revealed homeostatic tuning of intrinsic excitability in human stem cell-derived neurons. In brain slice, Optopatch induced and reported action potentials and subthreshold events, with high signal-to-noise ratios. The Optopatch platform enables high-throughput, spatially resolved electrophysiology without use of conventional electrodes.

Distinct spatiotemporal activity in principal neurons of the mouse olfactory bulb in anesthetized and awake states

The acquisition of olfactory information and its early processing in mammals are modulated by brain states through sniffing behavior and neural feedback. We imaged the spatiotemporal pattern of odor-evoked activity in a population of output neurons (mitral/tufted cells, MTCs) in the olfactory bulb (OB) of head-restrained mice expressing a genetically-encoded calcium indicator. The temporal dynamics of MTC population activity were relatively simple in anesthetized animals, but were highly variable in awake animals. However, the apparently irregular activity in awake animals could be predicted well using sniff timing measured externally, or inferred through fluctuations in the global responses of MTC population even without explicit knowledge of sniff times. The overall spatial pattern of activity was conserved across states, but odor responses had a diffuse spatial component in anesthetized mice that was less prominent during wakefulness. Multi-photon microscopy indicated that MTC lateral dendrites were the likely source of spatially disperse responses in the anesthetized animal. Our data demonstrate that the temporal and spatial dynamics of MTCs can be significantly modulated by behavioral state, and that the ensemble activity of MTCs can provide information about sniff timing to downstream circuits to help decode odor responses.

Optophysiological analysis of associational circuits in the olfactory cortex

Primary olfactory cortical areas receive direct input from the olfactory bulb, but also have extensive associational connections that have been mainly studied with classical anatomical methods. Here, we shed light on the functional properties of associational connections in the anterior and posterior piriform cortices (aPC and pPC) using optophysiological methods. We found that the aPC receives dense functional connections from the anterior olfactory nucleus (AON), a major hub in olfactory cortical circuits. The local recurrent connectivity within the aPC, long invoked in cortical autoassociative models, is sparse and weak. By contrast, the pPC receives negligible input from the AON, but has dense connections from the aPC as well as more local recurrent connections than the aPC. Finally, there are negligible functional connections from the pPC to aPC. Our study provides a circuit basis for a more sensory role for the aPC in odor processing and an associative role for the pPC.

Role of astrocytes in neurovascular coupling

Neural activity is intimately tied to blood flow in the brain. This coupling is specific enough in space and time that modern imaging methods use local hemodynamics as a measure of brain activity. In this review, we discuss recent evidence indicating that neuronal activity is coupled to local blood flow changes through an intermediary, the astrocyte. We highlight unresolved issues regarding the role of astrocytes and propose ways to address them using novel techniques. Our focus is on cellular level analysis in vivo, but we also relate mechanistic insights gained from ex vivo experiments to native tissue. We also review some strategies to harness advances in optical and genetic methods to study neurovascular coupling in the intact brain.

Olfactory maps in the brain

The responses of neural elements in many sensory areas of the brain vary systematically with their physical position, leading to a topographic representation of the outside world. Sensory representation in the olfactory system has been harder to decipher, in part because it is difficult to find appropriate metrics to characterize odor space and to sample this space densely. Recent experiments have shown that the arrangement of glomeruli, the elementary units of processing, is relatively invariant across individuals in a species, yet it is flexible enough to accommodate new sensors that might be added. Evidence supports the existence of coarse spatial domains carved out on a genetic or functional basis, but a systematic organization of odor responses or neural circuits on a local scale is not evident. Experiments and theory that relate the properties of odorant receptors to the detailed wiring diagram of the downstream olfactory circuits and to behaviors they trigger may reveal the design principles that have emerged during evolution.

Molecular organization of vomeronasal chemoreception

The vomeronasal organ (VNO) has a key role in mediating the social and defensive responses of many terrestrial vertebrates to species- and sex-specific chemosignals. More than 250 putative pheromone receptors have been identified in the mouse VNO, but the nature of the signals detected by individual VNO receptors has not yet been elucidated. To gain insight into the molecular logic of VNO detection leading to mating, aggression or defensive responses, we sought to uncover the response profiles of individual vomeronasal receptors to a wide range of animal cues. Here we describe the repertoire of behaviourally and physiologically relevant stimuli detected by a large number of individual vomeronasal receptors in mice, and define a global map of vomeronasal signal detection. We demonstrate that the two classes (V1R and V2R) of vomeronasal receptors use fundamentally different strategies to encode chemosensory information, and that distinct receptor subfamilies have evolved towards the specific recognition of certain animal groups or chemical structures. The association of large subsets of vomeronasal receptors with cognate, ethologically and physiologically relevant stimuli establishes the molecular foundation of vomeronasal information coding, and opens new avenues for further investigating the neural mechanisms underlying behaviour specificity.

Postnatal development of dendrodendritic inhibition in the Mammalian olfactory bulb

The mitral–granule cell (MC–GC) reciprocal synapse is an important source of auto- and lateral-inhibition in the olfactory bulb (OB), and this local inhibition is critical for odor discrimination. We may gain insight into the role of MC autoinhibition in olfaction by correlating the functional development of the autoinhibition with the postnatal development of olfactory function. We have studied the functional development of the MC–GC reciprocal synapse using whole-cell patch-clamp recordings from MCs and GCs in acute OB slices from 3- to 30-day-old rats. The magnitude of dendrodendritic inhibition (DDI) measured by depolarizing a single MC and recording recurrent inhibition in the same cell increased up to the fifteenth day of life (P15), but dropped between P15 and P30. The initial increase and later decrease in DDI was echoed by a similar increase and decrease in the frequency of miniature inhibitory post-synaptic currents, suggesting an accompanying modulation in the number of synapses available to participate in DDI. The late decrease in DDI could also result, in part, from a decrease in GC excitability as well as an increase in relative contribution of N-methyl d-aspartate (NMDA) receptors to γ-amino butyric acid (GABA) release from GC synapses. Changes in release probability of GABAergic synapses are unlikely to account for the late reduction in DDI, although they might contribute to the early increase during development. Our results demonstrate that the functional MC–GC circuit evolves over development in a complex manner that may include both construction and elimination of synapses.

Serotonergic modulation of odor input to the mammalian olfactory bulb

Centrifugal serotonergic fibers innervate the olfactory bulb, but the importance of these projections for olfactory processing is unclear. We examined serotonergic modulation of sensory input to olfactory glomeruli using mice that express synaptopHluorin in olfactory receptor neurons (ORN). Odor-evoked synaptic input to glomeruli was attenuated by increased serotonin signaling through serotonin 2C (5-HT2C) receptors and amplified by decreased serotonergic activity. Intravital multiphoton calcium imaging revealed that 5-HT2C receptor activation amplified odor-evoked activity in a subset of juxtaglomerular cells and attenuated glutamate release from ORN terminals via GABA(B) receptors. Endogenous serotonin released by electrical stimulation of the dorsal raphe nucleus attenuated odor-evoked responses without detectable bias in glomerular position or odor identity. Weaker glomerular responses, however, were less sensitive to raphe stimulation than strong responses. Our data indicate that the serotonergic system regulates odor inputs in the olfactory bulb and suggest that behavioral states may alter odor processing at the earliest stages.

Coupling of neural activity to blood flow in olfactory glomeruli is mediated by astrocytic pathways

Functional neuroimaging uses activity-dependent changes in cerebral blood flow to map brain activity, but the contributions of presynaptic and postsynaptic activity are incompletely understood, as are the underlying cellular pathways. Using intravital multiphoton microscopy, we measured presynaptic activity, postsynaptic neuronal and astrocytic calcium responses, and erythrocyte velocity and flux in olfactory glomeruli during odor stimulation in mice. Odor-evoked functional hyperemia in glomerular capillaries was highly correlated with glutamate release, but did not require local postsynaptic activity. Odor stimulation induced calcium transients in astrocyte endfeet and an associated dilation of upstream arterioles. Calcium elevations in astrocytes and functional hyperemia depended on astrocytic metabotropic glutamate receptor 5 and cyclooxygenase activation. Astrocytic glutamate transporters also contributed to functional hyperemia through mechanisms independent of calcium rises and cyclooxygenase activation. These local pathways initiated by glutamate account for a large part of the coupling between synaptic activity and functional hyperemia in the olfactory bulb.

Studying vesicle cycling in presynaptic terminals using the genetically encoded probe synaptopHluorin

Genetically encoded fluorescent probes have become indispensable tools in the biological sciences. Studies of synaptic vesicle recycling have been facilitated by a group of GFP-derived probes called pHluorins. These probes exploit changes in pH that accompany exocytosis and recapture of synaptic vesicles. Here we describe how these synaptic tracers can be used in rodent hippocampal neurons to monitor the synaptic vesicle cycle in real time and to obtain mechanistic insights about it. Synapses can be observed in living samples using a wide-field fluorescence microscope and a cooled charge-coupled device camera. A simple specimen chamber allows electrical stimulation of synapses to evoke exocytosis in a precisely controlled manner. We present protocols to measure various parameters of the synaptic vesicle cycle. This technique can be easily adapted to study different classes of synapses from wild-type and mutant mice. Once cultured neurons expressing synaptopHluorin are available, the whole procedure should take about 2 h.

Experience-dependent modification of primary sensory synapses in the mammalian olfactory bulb

Experience-dependent changes in neural circuits have traditionally been investigated several synapses downstream of sensory input. Whether experience can alter the strength of primary sensory synapses remains mostly unknown. To address this issue, we investigated the consequences of odor deprivation on synapses made by olfactory sensory axons in the olfactory bulb of rats. Odor deprivation triggered an increase in the probability of glutamate release from olfactory sensory neuron synapses. Deprivation also increased the amplitude of quantal synaptic currents mediated by AMPA- and NMDA-type glutamate receptors, as well as the abundance of these receptors in the glomerular region. Our results demonstrate that sensory experience is capable of modulating synaptic strength at the earliest stages of information transfer between the environment and an organism. Such compensatory experience-dependent changes may represent a mechanism of sensory gain control.