Resolving Colliding Larvae by Fitting ASM to Random Walker-Based Pre-Segmentations

Bian, Ang; Jiang, Xiaoyi; Berh, Dimitri; Risse, Benjamin

doi:10.1109/tcbb.2019.2935718

Cited by 4 publications

(6 citation statements)

References 49 publications

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“…These focus on the average behaviour of groups of animals and thus do not allow for individuals to be followed. More recent approaches have tried to combine the advantages of both types of tracking [ 30 , 31 ]. The major challenge in these cases is that individual Drosophila larvae look very much alike.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, when two larvae collide, their identity is lost, resulting in a multitude of separated tracks and no opportunity for the experimenter to disentangle which tracks belong to which of the animals. Two different strategies have been followed in tackling this problem: one relies on the parallel tracking of many separated individual animals [ 30 ]; the other tries to resolve the collisions between larvae and thus to keep track of the identity of individual larvae within a group of animals [ 31 ] (for an earlier approach not specific to Drosophila larvae, see [ 32 ]; for a similar approach in Caenorhabditis elegans , see [ 33 ]). The latter solution is so far not implemented in any ready-to-use tracking software.…”

Section: Introductionmentioning

confidence: 99%

“…Comparison between FIMtrack and IMBA. The column about FIMtrack is based on[24,25,31]. The cross-platform tracking was done as described in the results part of this study.…”

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confidence: 99%

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High-resolution analysis of individual Drosophila melanogaster larvae uncovers individual variability in locomotion and its neurogenetic modulation

et al. 2023

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Neuronally orchestrated muscular movement and locomotion are defining faculties of multicellular animals. Due to its simple brain and genetic accessibility, the larva of the fruit fly Drosophila melanogaster allows one to study these processes at tractable levels of complexity. However, although the faculty of locomotion clearly pertains to the individual, most studies of locomotion in larvae use measurements aggregated across animals, or animals tested one by one, an extravagance for larger-scale analyses. This prevents grasping the inter- and intra-individual variability in locomotion and its neurogenetic determinants. Here, we present the IMBA (individual maggot behaviour analyser) for analysing the behaviour of individual larvae within groups, reliably resolving individual identity across collisions. We use the IMBA to systematically describe the inter- and intra-individual variability in locomotion of wild-type animals, and how the variability is reduced by associative learning. We then report a novel locomotion phenotype of an adhesion GPCR mutant. We further investigated the modulation of locomotion across repeated activations of dopamine neurons in individual animals, and the transient backward locomotion induced by brief optogenetic activation of the brain-descending ‘mooncrawler’ neurons. In summary, the IMBA is an easy-to-use toolbox allowing an unprecedentedly rich view of the behaviour and its variability of individual larvae, with utility in multiple biomedical research contexts.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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High-resolution analysis of individual Drosophila melanogaster larvae uncovers individual variability in locomotion and its neurogenetic modulation

et al. 2023

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“…As a result, when two larvae collide, their identity is lost, resulting in a multitude of separated tracks and no opportunity for the experimenter to disentangle which tracks belong to which of the animals. Two different strategies have been followed in tackling this problem: one relies on the parallel tracking of many separated individual animals [29]; the other tries to resolve the collisions between larvae and thus to keep track of the identity of individual larvae within a group of animals [30] (for an earlier approach not specific to Drosophila larvae, see [31]). The latter solution has been integrated into the FIM (Frustrated total internal reflection-based Imaging Method) tracker software which requires specific hardware to illuminate the tracked animals [23].…”

Section: Introductionmentioning

confidence: 99%

“…These focus on the average behaviour of groups of animals and thus do not allow for individuals to be followed. More recent approaches have tried to combine the advantages of both types of tracking [29, 30]. The major challenge in these cases is that individual Drosophila larvae look very much alike.…”

Section: Introductionmentioning

confidence: 99%

High-resolution analysis of individualDrosophila melanogasterlarvae within groups uncovers inter- and intra-individual variability in locomotion and its neurogenetic modulation

Thane

Paisios

Stöter

et al. 2022

Preprint

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Neuronally orchestrated muscular movement and locomotion are defining faculties of multicellular animals. Due to its numerically simple brain and neuromuscular system and its genetic accessibility, the larva of the fruit fly Drosophila melanogaster is an established model to study these processes at tractable levels of complexity. However, although the faculty of locomotion clearly pertains to the individual animal, present studies of locomotion in larval Drosophila mostly use group assays and measurements aggregated across individual animals. The alternative is to measure animals one at a time, an extravagance for larger-scale analyses. In principle or in practice, this in particular rules out grasping the inter- and intra-individual variability in locomotion and its genetic and neuronal determinants. Here we present the IMBA (Individual Maggot Behaviour Analyser) for tracking and analysing the behaviour of individual larvae within groups. Using a combination of computational modelling and statistical approaches, the IMBA reliably resolves individual identity across collisions. It does not require specific hardware and can therefore be used in non-expert labs. We take advantage of the IMBA first to systematically describe the inter- and intra-individual variability in free, unconstrained locomotion in wild-type animals. We then report the discovery of a novel, complex locomotion phenotype of a mutant lacking an adhesion-type GPCR. The IMBA further allows us to determine, at the level of individual animals, the modulation of locomotion across repeated activations of dopamine neurons. Strikingly, IMBA can also be used to analyse 'silly walks', that is patterns of locomotion it was not originally designed to investigate. This is shown for the transient backward locomotion induced by brief optogenetic activation of the brain-descending 'mooncrawler' neurons, and the variability in this behaviour. Thus, the IMBA is an easy-to-use toolbox allowing an unprecedentedly rich view of the behaviour and behavioural variability of individual Drosophila larvae, with utility in multiple biomedical research contexts.

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An optimized denoised bias correction model with local pre-fitting function for weak boundary image segmentation

Wang,

Li,

Weng

et al. 2024

Signal Processing

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Resolving Colliding Larvae by Fitting ASM to Random Walker-Based Pre-Segmentations

Cited by 4 publications

References 49 publications

High-resolution analysis of individual Drosophila melanogaster larvae uncovers individual variability in locomotion and its neurogenetic modulation

High-resolution analysis of individual Drosophila melanogaster larvae uncovers individual variability in locomotion and its neurogenetic modulation

High-resolution analysis of individualDrosophila melanogasterlarvae within groups uncovers inter- and intra-individual variability in locomotion and its neurogenetic modulation

An optimized denoised bias correction model with local pre-fitting function for weak boundary image segmentation

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