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2194 Janelia Publications

Showing 91-100 of 2194 results
05/25/22 | Accurate angular integration with only a handful of neurons.
Marcella Noorman , Brad K Hulse , Vivek Jayaraman , Sandro Romani , Ann M Hermundstad
bioRxiv. 2022 May 25:. doi: 10.1101/2022.05.23.493052

To flexibly navigate, many animals rely on internal spatial representations that persist when the animal is standing still in darkness, and update accurately by integrating the animal's movements in the absence of localizing sensory cues. Theories of mammalian head direction cells have proposed that these dynamics can be realized in a special class of networks that maintain a localized bump of activity via structured recurrent connectivity, and that shift this bump of activity via angular velocity input. Although there are many different variants of these so-called ring attractor networks, they all rely on large numbers of neurons to generate representations that persist in the absence of input and accurately integrate angular velocity input. Surprisingly, in the fly, Drosophila melanogaster, a head direction representation is maintained by a much smaller number of neurons whose dynamics and connectivity resemble those of a ring attractor network. These findings challenge our understanding of ring attractors and their putative implementation in neural circuits. Here, we analyzed failures of angular velocity integration that emerge in small attractor networks with only a few computational units. Motivated by the peak performance of the fly head direction system in darkness, we mathematically derived conditions under which small networks, even with as few as 4 neurons, achieve the performance of much larger networks. The resulting description reveals that by appropriately tuning the network connectivity, the network can maintain persistent representations over the continuum of head directions, and it can accurately integrate angular velocity inputs. We then analytically determined how performance degrades as the connectivity deviates from this optimally-tuned setting, and we find a trade-off between network size and the tuning precision needed to achieve persistence and accurate integration. This work shows how even small networks can accurately track an animal's movements to guide navigation, and it informs our understanding of the functional capabilities of discrete systems more broadly.

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05/25/22 | Drosophila gustatory projections are segregated by taste modality and connectivity.
Engert S, Sterne GR, Bock DD, Scott K
eLife. 2022 May 25;11:. doi: 10.7554/eLife.78110

Gustatory sensory neurons detect caloric and harmful compounds in potential food and convey this information to the brain to inform feeding decisions. To examine the signals that gustatory neurons transmit and receive, we reconstructed gustatory axons and their synaptic sites in the adult brain, utilizing a whole-brain electron microscopy volume. We reconstructed 87 gustatory projections from the proboscis labellum in the right hemisphere and 57 from the left, representing the majority of labellar gustatory axons. Gustatory neurons contain a nearly equal number of interspersed pre- and postsynaptic sites, with extensive synaptic connectivity among gustatory axons. Morphology- and connectivity-based clustering revealed six distinct groups, likely representing neurons recognizing different taste modalities. The vast majority of synaptic connections are between neurons of the same group. This study resolves the anatomy of labellar gustatory projections, reveals that gustatory projections are segregated based on taste modality, and uncovers synaptic connections that may alter the transmission of gustatory signals.

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05/25/22 | Expectation-based learning rules underlie dynamic foraging in Drosophila
Adithya E. Rajagopalan , Ran Darshan , James E. Fitzgerald , Glenn C. Turner
bioRxiv. 2022 May 25:. doi: 10.1101/2022.05.24.493252

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.

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05/24/22 | Perceptual decisions exhibit hallmarks of dynamic Bayesian inference
Julie A. Charlton , Wiktor F. Młynarski , Yoon H. Bai , Ann M. Hermundstad , Robbe L. T. Goris
bioRxiv. 2022 May 24:. doi: 10.1101/2022.05.23.493109

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.

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05/23/22 | Hormone-controlled changes in the differentiation state of post-mitotic neurons.
Lai Y, Miyares RL, Liu L, Chu S, Lee T, Yu H
Current Biology. 2022 May 23;32(10):2341-2348. doi: 10.1016/j.cub.2022.04.027

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.

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05/20/22 | Super-resolution visualization of chromatin loop folding in human lymphoblastoid cells using interferometric photoactivated localization microscopy.
Parteka-Tojek Z, Zhu JJ, Lee B, Jodkowska K, Wang P, Aaron J, Chew T, Banecki K, Plewczyński D, Ruan Y
Scientific Reports. 2022 May 20;12(1):8582. doi: 10.1038/s41598-022-12568-9

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.

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05/18/22 | A functionally ordered visual feature map in the Drosophila brain.
Klapoetke NC, Nern A, Rogers EM, Rubin GM, Reiser MB, Card GM
Neuron. 2022 May 18;110(10):1700. doi: 10.1016/j.neuron.2022.02.013

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.

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05/18/22 | Maintaining a stable head direction representation in naturalistic visual environments
Hannah Haberkern , Shivam S Chitnis , Philip M Hubbard , Tobias Goulet , Ann M Hermundstad , Vivek Jayaraman
bioRxiv. 2022 May 18:. doi: 10.1101/2022.05.17.492284

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.

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05/18/22 | Three Mutations Convert the Selectivity of a Protein Sensor From Nicotinic Agonists to S-Methadone For Use in Cells, Organelles, and Biofluids.
Anand K. Muthusamy , Charlene H. Kim , Scott C. Virgil , Hailey J. Knox , Jonathan S. Marvin , Aaron L. Nichols , Bruce N. Cohen , Dennis A. Dougherty , Loren L. Looger , Henry A. Lester
Journal of the American Chemical Society. 2022 May 18;144(19):. doi: 10.1101/2022.02.24.481226

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.

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Looger Lab
05/18/22 | Volume-transmitted GABA waves pace epileptiform rhythms in the hippocampal network
Vincent Magloire , Leonid P. Savtchenko , Sergyi Sylantyev , Thomas P. Jensen , Nicholas Cole , Jonathan S. Marvin , Loren L. Looger , Dimitri M. Kullmann , Matthew C. Walker , Ivan Pavlov , Dmitri A. Rusakov
bioRxiv. 2022 May 18:. doi: 10.1101/2021.03.25.437016

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.

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