Whole-central nervous system functional imaging in larval Drosophila

Lemon, William C.; Pulver, Stefan R.; Höckendorf, Burkhard; McDole, Katie; Branson, Kristin; Freeman, Jeremy; Keller, Philipp J.

doi:10.1038/ncomms8924

Cited by 196 publications

(180 citation statements)

References 51 publications

(94 reference statements)

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“…Recent technological advances in microscopy, combined with better fluorescent probes, have enabled near-brainwide calcium imaging in immobilized worms, flies, and flies, and fish (14,29,30). This was even recently demonstrated in freely behaving embryonic Drosophila (31) and adult C. elegans (11,12).…”

Section: Brainwide Calcium Imaging At Subcellular Resolution In a Frementioning

confidence: 99%

Visualizing Calcium Flux in Freely Moving Nematode Embryos

Ardiel

Kumar

Marbach

et al. 2017

Biophysical Journal

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The lack of physiological recordings from Caenorhabditis elegans embryos stands in stark contrast to the comprehensive anatomical and gene expression datasets already available. Using light-sheet fluorescence microscopy to address the challenges associated with functional imaging at this developmental stage, we recorded calcium dynamics in muscles and neurons and developed analysis strategies to relate activity and movement. In muscles, we found that the initiation of twitching was associated with a spreading calcium wave in a dorsal muscle bundle. Correlated activity in muscle bundles was linked with early twitching and eventual coordinated movement. To identify neuronal correlates of behavior, we monitored brainwide activity with subcellular resolution and identified a particularly active cell associated with muscle contractions. Finally, imaging neurons of a well-defined adult motor circuit, we found that reversals in the eggshell correlated with calcium transients in AVA interneurons.

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Section: Brainwide Calcium Imaging At Subcellular Resolution In a Frementioning

confidence: 99%

Visualizing Calcium Flux in Freely Moving Nematode Embryos

Ardiel

Kumar

Marbach

et al. 2017

Biophysical Journal

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“…Rapid progress is being made toward this goal, especially using animal models with relatively simple brains. Large quantities of neural activity data have been acquired simultaneously with behavioral data in larval zebrafish Danio rerio (Dunn et al 2016), the nematode Caenorhabditis elegans (Nguyen et al 2016, Venkatachalam et al 2016, and the fruit fly Drosophila melanogaster (Harris et al 2015, Lemon et al 2015, Seelig and Jayaraman 2015. These organisms are also the focus of past (White et al 1986) or ongoing (Takemura et al 2013) connectomic efforts to map the synapse-level connectivity between all neurons in the brain.…”

Section: Introductionmentioning

confidence: 99%

Systematic exploration of unsupervised methods for mapping behavior

Todd

Kain²,

Bivort

2017

Phys. Biol.

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To fully understand the mechanisms giving rise to behavior, we need to be able to precisely measure it. When coupled with large behavioral data sets, unsupervised clustering methods offer the potential of unbiased mapping of behavioral spaces. However, unsupervised techniques to map behavioral spaces are in their infancy, and there have been few systematic considerations of all the methodological options. We compared the performance of seven distinct mapping methods in clustering a wavelettransformed data set consisting of the x-and y-positions of the six legs of individual flies. Legs were automatically tracked by small pieces of fluorescent dye, while the fly was tethered and walking on an air-suspended ball. We find that there is considerable variation in the performance of these mapping methods, and that better performance is attained when clustering is done in higher dimensional spaces (which are otherwise less preferable because they are hard to visualize). High dimensionality means that some algorithms, including the non-parametric watershed cluster assignment algorithm, cannot be used. We developed an alternative watershed algorithm which can be used in high-dimensional spaces when a probability density estimate can be computed directly. With these tools in hand, we examined the behavioral space of fly leg postural dynamics and locomotion. We find a striking division of behavior into modes involving the fore legs and modes involving the hind legs, with few direct transitions between them. By computing behavioral clusters using the data from all flies simultaneously, we show that this division appears to be common to all flies. We also identify individual-to-individual differences in behavior and behavioral transitions. Lastly, we suggest a computational pipeline that can achieve satisfactory levels of performance without the taxing computational demands of a systematic combinatorial approach.

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“…Such systemlevel cell-lineage reconstructions provide important insights into the stereotypy of developmental processes, link developmental history to cell function in the developmental building plan of an animal, aid in dissecting the role of differential gene expression in directing cell-fate decisions, and facilitate experimental validation of mechanistic models of development [24][25][26][27][28][29][30][31][32][33] . In neuroscience, light-sheet microscopy has made it possible to perform functional imaging of large neuronal populations, entire brains 5,34 and even the entire CNS 35 . Such experiments have the potential to illuminate how large neural networks perform complex computations and generate behavior at the single-cell level 22,36 .…”

Section: Introductionmentioning

confidence: 99%

Efficient processing and analysis of large-scale light-sheet microscopy data

et al. 2015

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Light-sheet microscopy is a powerful method for imaging the development and function of complex biological systems at high spatiotemporal resolution and over long time scales. Such experiments typically generate terabytes of multidimensional image data, and thus they demand efficient computational solutions for data management, processing and analysis. We present protocols and software to tackle these steps, focusing on the imaging-based study of animal development. Our protocols facilitate (i) high-speed lossless data compression and content-based multiview image fusion optimized for multicore CPU architectures, reducing image data size 30-500-fold; (ii) automated large-scale cell tracking and segmentation; and (iii) visualization, editing and annotation of multiterabyte image data and cell-lineage reconstructions with tens of millions of data points. These software modules are open source. They provide high data throughput using a single computer workstation and are readily applicable to a wide spectrum of biological model systems.

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Whole-central nervous system functional imaging in larval Drosophila

Cited by 196 publications

References 51 publications

Visualizing Calcium Flux in Freely Moving Nematode Embryos

Visualizing Calcium Flux in Freely Moving Nematode Embryos

Systematic exploration of unsupervised methods for mapping behavior

Efficient processing and analysis of large-scale light-sheet microscopy data

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