The natverse, a versatile toolbox for combining and analysing neuroanatomical data

eLife, Год журнала: 2020, Номер 9

Опубликована: Апрель 14, 2020

To analyse neuron data at scale, neuroscientists expend substantial effort reading documentation, installing dependencies and moving between analysis visualisation environments. facilitate this, we have developed a suite of interoperable open-source R packages called the natverse. The natverse allows users to read local remote data, perform popular analyses including clustering graph-theoretic neuronal branching. Unlike most tools, enables comparison across many neurons morphology connectivity after imaging or co-registration within common template space. also transformations different spaces modalities. We demonstrate tools that integrate vast majority

Язык: Английский

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Drosophila mushroom bodies integrate hunger and satiety signals to control innate food-seeking behavior

eLife, Год журнала: 2018, Номер 7

Опубликована: Март 16, 2018

The fruit fly can evaluate its energy state and decide whether to pursue food-related cues. Here, we reveal that the mushroom body (MB) integrates hunger satiety signals control food-seeking behavior. We have discovered five pathways in MB essential for hungry flies locate approach food. Blocking MB-intrinsic Kenyon cells (KCs) output neurons (MBONs) these impairs Starvation bi-directionally modulates MBON responses a food odor, suggesting controls occur at KC-to-MBON synapses. These are mediated by six types of dopaminergic (DANs). By manipulating DANs, could inhibit behavior or promote seeking fed flies. Finally, show DANs potentially receive multiple inputs signals. This work demonstrates an information-rich central circuit brain hunger-driven

Язык: Английский

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The Drosophila Mushroom Body: From Architecture to Algorithm in a Learning Circuit

Annual Review of Neuroscience, Год журнала: 2020, Номер 43(1), С. 465 - 484

Опубликована: Апрель 14, 2020

The Drosophila brain contains a relatively simple circuit for forming Pavlovian associations, yet it achieves many operations common across memory systems. Recent advances have established clear framework learning and revealed the following key operations: a) pattern separation, whereby dense combinatorial representations of odors are preprocessed to generate highly specific, nonoverlapping odor patterns used learning; b) convergence, in which sensory information is funneled small set output neurons that guide behavioral actions; c) plasticity, where changing mapping input requires strong reinforcement signal, also modulated by internal state environmental context; d) modularization, consists multiple parallel traces, distinct stability flexibility exist anatomically well-defined modules within network. Cross-module interactions allow higher-order effects past experience influences future learning. Many these parallels with processes formation action selection more complex brains.

Язык: Английский

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Neurogenetic dissection of the Drosophila lateral horn reveals major outputs, diverse behavioural functions, and interactions with the mushroom body

eLife, Год журнала: 2019, Номер 8

Опубликована: Май 21, 2019

Animals exhibit innate behaviours to a variety of sensory stimuli including olfactory cues. In Drosophila, one higher centre, the lateral horn (LH), is implicated in behaviour. However, our structural and functional understanding LH scant, large part due lack sparse neurogenetic tools for this region. We generate collection split-GAL4 driver lines providing genetic access 82 cell types. use these create an anatomical neurotransmitter map link EM connectomics data. find ~30% projections converge with outputs from mushroom body, site learning memory. Using optogenetic activation, we identify types that drive changes valence behavior or specific locomotor programs. summary, have generated resource manipulating mapping neurons, new insights into circuit basis learned behavior.

Язык: Английский

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Recurrent architecture for adaptive regulation of learning in the insect brain

Nature Neuroscience, Год журнала: 2020, Номер 23(4), С. 544 - 555

Опубликована: Март 23, 2020

Язык: Английский

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A Connectome of the AdultDrosophilaCentral Brain

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2020, Номер unknown

Опубликована: Янв. 21, 2020

Abstract The neural circuits responsible for behavior remain largely unknown. Previous efforts have reconstructed the complete of small animals, with hundreds neurons, and selected larger animals. Here we (the FlyEM project at Janelia collaborators Google) summarize new methods present circuitry a large fraction brain much more complex animal, fruit fly Drosophila melanogaster . Improved include procedures to prepare, image, align, segment, find synapses, proofread such data sets; that define cell types based on connectivity in addition morphology; simplify access evolving set. From resulting derive better definition computational compartments their connections; an exhaustive atlas examples types, many them novel; detailed most central brain; exploration statistics structure different compartments, as whole. We make public, web site resources specifically designed it easy explore, all levels expertise from expert merely curious. public availability these data, simplified means it, dramatically reduces effort needed answer typical circuit questions, identity upstream downstream partners, regions, link neurons defined by our analysis genetic reagents can be used study functions. Note: In next few weeks, will release series papers involved discussions. One paper detail hemibrain reconstruction extensive interpretation made possible this dense connectome. Another explore complex, region navigation, motor control, sleep. A final insights mushroom body, center multimodal associative learning brain.

Язык: Английский

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An open-access volume electron microscopy atlas of whole cells and tissues

Nature, Год журнала: 2021, Номер 599(7883), С. 147 - 151

Опубликована: Окт. 6, 2021

Язык: Английский

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neuPrint: An open access tool for EM connectomics

Frontiers in Neuroinformatics, Год журнала: 2022, Номер 16

Опубликована: Июль 20, 2022

Due to advances in electron microscopy and deep learning, it is now practical reconstruct a connectome, description of neurons the chemical synapses between them, for significant volumes neural tissue. Smaller past reconstructions were primarily used by domain experts, could be handled downloading data, performance was not serious problem. But new much larger upend these assumptions. These networks contain tens thousands millions connections, with yet pending, are interest large community non-specialists. Allowing other scientists make use this data needs more than publication-it requires tools that publicly available, easy use, efficiently handle data. We introduce neuPrint address analysis challenges. Neuprint contains two major components-a web interface programmer APIs. The designed allow any scientist worldwide, using only browser, quickly ask answer typical biological queries about connectome. APIs computer-savvy complex or higher volume queries. NeuPrint also provides features assessing reconstruction quality. Internally, organizes connectome as graph stored neo4j database. This gives high queries, access though public well documented query language Cypher, will extend future connectomics databases. Our experience an experiment open science. find fraction readers article proceed examine directly. In our case preprints worked exactly intended, inquiries PDF downloads starting immediately after pre-print publication, little affected formal publication later. From we deduce many interested suggesting data-only papers can appreciated release speed up propagation scientific results months. providing, keeping, available online imposes substantial additional costs research.

Язык: Английский

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Whole-brain annotation and multi-connectome cell typing of Drosophila

Nature, Год журнала: 2024, Номер 634(8032), С. 139 - 152

Опубликована: Окт. 2, 2024

Язык: Английский

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Multisensory learning binds neurons into a cross-modal memory engram

Nature, Год журнала: 2023, Номер 617(7962), С. 777 - 784

Опубликована: Апрель 26, 2023

Associating multiple sensory cues with objects and experience is a fundamental brain process that improves object recognition memory performance. However, neural mechanisms bind features during learning augment expression are unknown. Here we demonstrate multisensory appetitive aversive in Drosophila. Combining colours odours improved performance, even when each modality was tested alone. Temporal control of neuronal function revealed visually selective mushroom body Kenyon cells (KCs) to be required for enhancement both visual olfactory after training. Voltage imaging head-fixed flies showed binds activity between streams modality-specific KCs so unimodal input generates multimodal response. Binding occurs regions the KC axons, which receive valence-relevant dopaminergic reinforcement, propagated downstream. Dopamine locally releases GABAergic inhibition permit specific microcircuits within KC-spanning serotonergic neurons as an excitatory bridge previously 'modality-selective' streams. Cross-modal binding thereby expands representing engram into those other. This broadening performance permits single feature retrieve experience.

Язык: Английский

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