Foraging animals must use decision-making strategies that dynamically account for uncertainty in the world. To cope with this uncertainty, animals have developed strikingly convergent strategies that use information about multiple past choices and reward to learn representations of the current state of the world. However, the underlying learning rules that drive the required learning have remained unclear. Here, working in the relatively simple nervous system of Drosophila, we combine behavioral measurements, mathematical modeling, and neural circuit perturbations to show that dynamic foraging depends on a learning rule incorporating reward expectation. Using a novel olfactory dynamic foraging task, we characterize the behavioral strategies used by individual flies when faced with unpredictable rewards and show, for the first time, that they perform operant matching. We build on past theoretical work and demonstrate that this strategy requires the existence of a covariance-based learning rule in the mushroom body - a hub for learning in the fly. In particular, the behavioral consequences of optogenetic perturbation experiments suggest that this learning rule incorporates reward expectation. Our results identify a key element of the algorithm underlying dynamic foraging in flies and suggest a comprehensive mechanism that could be fundamental to these behaviors across species.

To interpret the sensory environment, the brain combines ambiguous sensory measurements with context-specific prior experience. But environmental contexts can change abruptly and unpredictably, resulting in uncertainty about the current context. Here we address two questions: how should context-specific prior knowledge optimally guide the interpretation of sensory stimuli in changing environments, and do human decision-making strategies resemble this optimum? We probe these questions with a task in which subjects report the orientation of ambiguous visual stimuli that were drawn from three dynamically switching distributions, representing different environmental contexts. We derive predictions for an ideal Bayesian observer that leverages the statistical structure of the task to maximize decision accuracy and show that its decisions are biased by task context. The magnitude of this decision bias is not a fixed property of the sensory measurement but depends on the observer's belief about the current context. The model therefore predicts that decision bias will grow with the reliability of the context cue, the stability of the environment, and with the number of trials since the last context switch. Analysis of human choice data validates all three predictions, providing evidence that the brain continuously updates probabilistic representations of the environment to best interpret an uncertain, ever-changing world.

While we think of neurons as having a fixed identity, many show spectacular plasticity. Metamorphosis drives massive changes in the fly brain; neurons that persist into adulthood often change in response to the steroid hormone ecdysone. Besides driving remodeling, ecdysone signaling can also alter the differentiation status of neurons. The three sequentially born subtypes of mushroom body (MB) Kenyon cells (γ, followed by α'/β', and finally α/β) serve as a model of temporal fating. γ neurons are also used as a model of remodeling during metamorphosis. As γ neurons are the only functional Kenyon cells in the larval brain, they serve the function of all three adult subtypes. Correspondingly, larval γ neurons have a similar morphology to α'/β' and α/β neurons-their axons project dorsally and medially. During metamorphosis, γ neurons remodel to form a single medial projection. Both temporal fate changes and defects in remodeling therefore alter γ-neuron morphology in similar ways. Mamo, a broad-complex, tramtrack, and bric-à-brac/poxvirus and zinc finger (BTB/POZ) transcription factor critical for temporal specification of α'/β' neurons, was recently described as essential for γ remodeling. In a previous study, we noticed a change in the number of adult Kenyon cells expressing γ-specific markers when mamo was manipulated. These data implied a role for Mamo in γ-neuron fate specification, yet mamo is not expressed in γ neurons until pupariation, well past γ specification. This indicates that mamo has a later role in ensuring that γ neurons express the correct Kenyon cell subtype-specific genes in the adult brain.

The three-dimensional (3D) genome structure plays a fundamental role in gene regulation and cellular functions. Recent studies in 3D genomics inferred the very basic functional chromatin folding structures known as chromatin loops, the long-range chromatin interactions that are mediated by protein factors and dynamically extruded by cohesin. We combined the use of FISH staining of a very short (33 kb) chromatin fragment, interferometric photoactivated localization microscopy (iPALM), and traveling salesman problem-based heuristic loop reconstruction algorithm from an image of the one of the strongest CTCF-mediated chromatin loops in human lymphoblastoid cells. In total, we have generated thirteen good quality images of the target chromatin region with 2-22 nm oligo probe localization precision. We visualized the shape of the single chromatin loops with unprecedented genomic resolution which allowed us to study the structural heterogeneity of chromatin looping. We were able to compare the physical distance maps from all reconstructed image-driven computational models with contact frequencies observed by ChIA-PET and Hi-C genomic-driven methods to examine the concordance between single cell imaging and population based genomic data.

Topographic maps, the systematic spatial ordering of neurons by response tuning, are common across species. In Drosophila, the lobula columnar (LC) neuron types project from the optic lobe to the central brain, where each forms a glomerulus in a distinct position. However, the advantages of this glomerular arrangement are unclear. Here, we examine the functional and spatial relationships of 10 glomeruli using single-neuron calcium imaging. We discover novel detectors for objects smaller than the lens resolution (LC18) and for complex line motion (LC25). We find that glomeruli are spatially clustered by selectivity for looming versus drifting object motion and ordered by size tuning to form a topographic visual feature map. Furthermore, connectome analysis shows that downstream neurons integrate from sparse subsets of possible glomeruli combinations, which are biased for glomeruli encoding similar features. LC neurons are thus an explicit example of distinct feature detectors topographically organized to facilitate downstream circuit integration.

Many animals rely on a representation of head direction for flexible, goal-directed navigation. In insects, a compass-like head direction representation is maintained in a conserved brain region called the central complex. This head direction representation is updated by self-motion information and by tethering to sensory cues in the surroundings through a plasticity mechanism. However, under natural settings, some of these sensory cues may temporarily disappear—for example, when clouds hide the sun—and prominent landmarks at different distances from the insect may move across the animal's field of view during translation, creating potential conflicts for a neural compass. We used two-photon calcium imaging in head-fixed Drosophila behaving in virtual reality to monitor the fly's compass during navigation in immersive naturalistic environments with approachable local landmarks. We found that the fly's compass remains stable even in these settings by tethering to available global cues, likely preserving the animal's ability to perform compass-driven behaviors such as maintaining a constant heading.

We report a reagentless, intensity-based S-methadone fluorescent sensor, iS-methadoneSnFR, consisting of a circularly permuted GFP inserted within the sequence of a mutated bacterial periplasmic binding protein (PBP). We used directed evolution to convert a previously reported nicotine-binding PBP to a selective S-methadone-binding sensor, via three mutations in the PBP’s second shell and hinge regions. iS-methadoneSnFR displays sensitivity across the pharmacologically relevant range and selectivity against endogenous analytes and other opioids. Robust iS-methadoneSnFR responses in human sweat and saliva and mouse serum enable diagnostic uses. Genetic encoding and imaging in mammalian demonstrated the acid trapping of S-methadone in the Golgi apparatus where opioid receptors can signal. This work shows a straightforward strategy in adapting existing PBPs to serve real-time applications ranging from subcellular to personal pharmacokinetics.

Mechanisms that entrain and drive rhythmic epileptiform discharges remain debated. Traditionally, this quest has been focusing on interneuronal networks driven by GABAergic connections that activate synaptic or extrasynaptic receptors. However, synchronised interneuronal discharges could also trigger a transient elevation of extracellular GABA across the tissue volume, thus raising tonic GABAA receptor conductance (Gtonic) in multiple cells. Here, we use patch-clamp GABA ‘sniffer’ and optical GABA sensor to show that periodic epileptiform discharges are preceded by region-wide, rising waves of extracellular GABA. Neural network simulations that incorporate volume-transmitted GABA signals point to mechanistic principles underpinning this relationship. We validate this hypothesis using simultaneous patch-clamp recordings from multiple nerve cells, selective optogenetic stimulation of fast-spiking interneurons. Critically, we manipulate GABA uptake to suppress extracellular GABA waves but not synaptic GABAergic transmission, which shows a clear effect on rhythm generation. Our findings thus unveil a key role of extrasynaptic, volume-transmitted GABA actions in pacing regenerative rhythmic activity in brain networks.

The flagella of mammalian sperm display non-planar, asymmetric beating, in contrast to the planar, symmetric beating of flagella from sea urchin sperm and unicellular organisms. The molecular basis of this difference is unclear. Here, we perform in situ cryo-electron tomography of mouse and human sperm axonemes, providing the highest resolution structural information to date. Our subtomogram averages reveal mammalian sperm- specific protein complexes within the outer microtubule doublets, the radial spokes and nexin-dynein regulatory complexes. The locations and structures of these complexes suggest potential roles in enhancing the mechanical strength of mammalian sperm axonemes and regulating dynein-based axonemal bending. Intriguingly, we find that each of the nine outer microtubule doublets is decorated with a distinct combination of sperm- specific complexes. We propose that this asymmetric distribution of proteins differentially regulates the sliding of each microtubule doublet and may underlie the asymmetric beating of mammalian sperm.

While fluorescence microscopy has proven to be an exceedingly useful tool in bioscience, it is difficult to offer simultaneous high resolution, fast speed, large volume, and good biocompatibility in a single imaging technique. Thus, when determining the image data required to quantitatively test a complex biological hypothesis, it often becomes evident that multiple imaging techniques are necessary. Recent years have seen an explosion in development of novel fluorescence microscopy techniques, each of which features a unique suite of capabilities. In this Technical Perspective, we highlight recent studies to illustrate the benefits, and often the necessity, of combining multiple fluorescence microscopy modalities. We provide guidance in choosing optimal technique combinations to effectively address a biological question. Ultimately, we aim to promote a more well-rounded approach in designing fluorescence microscopy experiments, leading to more robust quantitative insight.