Active sampling and decision making in Drosophila chemotaxis

Gomez‐Marin, Alex; Stephens, Greg J.; Louis, Matthieu

doi:10.1038/ncomms1455

Cited by 236 publications

(399 citation statements)

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“…T he ability of animals to track odour trails is well known but sparingly studied [1][2][3][4][5][6] . Fundamental issues regarding the behavioural and neural mechanisms of this ethologically important behaviour remain poorly understood.…”

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confidence: 99%

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Rats track odour trails accurately using a multi-layered strategy with near-optimal sampling

2012

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Tracking odour trails is a crucial behaviour for many animals, often leading to food, mates or away from danger. It is an excellent example of active sampling, where the animal itself controls how to sense the environment. Here we show that rats can track odour trails accurately with near-optimal sampling. We trained rats to follow odour trails drawn on paper spooled through a treadmill. By recording local field potentials (LFPs) from the olfactory bulb, and sniffing rates, we find that sniffing but not LFPs differ between tracking and non-tracking conditions. Rats can track odours within ~1 cm, and this accuracy is degraded when one nostril is closed. moreover, they show path prediction on encountering a fork, wide 'casting' sweeps on encountering a gap and detection of reappearance of the trail in 1-2 sniffs. We suggest that rats use a multi-layered strategy, and achieve efficient sampling and high accuracy in this complex task.

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confidence: 99%

“…Second, the use of stereo olfaction in efficiently performing this task has been repeatedly suggested. Disrupting bilateral input affects tracking in bees 12 , drosophila larvae 6,13 and humans 11 .…”

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confidence: 99%

Rats track odour trails accurately using a multi-layered strategy with near-optimal sampling

2012

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“…For many ecological questions it is necessary to obtain quantitative information about the environmental landscape, which can be integrated with tracking data to understand how the environment influences behavior [1,5,17,57] (Box 1). Remote quantification of the environment is a key advantage of imaging over bio-logging, which only provides environmental information in the immediate vicinity of the individual to which the logger is attached.…”

Section: Call To Developers: the Ideal Automated Image-based Trackingmentioning

confidence: 99%

Automated image-based tracking and its application in ecology

Dell

Bender²,

Branson

et al. 2014

Trends in Ecology & Evolution

453

484

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The behavior of individuals determines the strength and outcome of ecological interactions, which drive population, community, and ecosystem organization. Bio-logging, such as telemetry and animal-borne imaging, provides essential individual viewpoints, tracks, and life histories, but requires capture of individuals and is often impractical to scale. Recent developments in automated image-based tracking offers opportunities to remotely quantify and understand individual behavior at scales and resolutions not previously possible, providing an essential supplement to other tracking methodologies in ecology. Automated image-based tracking should continue to advance the field of ecology by enabling better understanding of the linkages between individual and higher-level ecological processes, via high-throughput quantitative analysis of complex ecological patterns and processes across scales, including analysis of environmental drivers. Measuring behaviorIndividual behavior (see Glossary) underlies almost all aspects of ecology [1][2][3][4][5]. Accurate and highly resolved behavioral data are therefore critical for obtaining a mechanistic and predictive understanding of ecological systems [5]. Historically, direct observation by trained biologists was used to quantify behavior [6,7]. However, the extent and resolution to which direct observations can be made is highly constrained [8] and the number of individuals that can be observed simultaneously is small. In addition, an exact record of events is not preserved, only the biologist's subjective account of them.Recent technological advances in tracking now make it possible to collect large amounts of highly precise and accurate behavioral data. For many organisms equipment can be attached that provide information about the Glossary Background subtraction: a method used by software to compare the current video frame with a stored picture of the background; any pixel of the current frame that is significantly different from the corresponding pixel in the background is likely to be associated with the body of an animal. Useful in situations where the background is unchanging, for example, when the surface of the background is rigid and lighting does not change. Behavior: the actions of individuals, often in response to stimuli. Behavior can involve movement of the individual's body through space, such as walking or chasing, or can occur while the animal is stationary, such as grooming or eating. Bio-logging: attachment or implantation of equipment to organisms to provide information about their identity, location, behavior, or physiology (e.g., global positioning systems, accelerometers, video cameras, telemetry tags). Ecological interaction: any interaction between an organism and its environment, or between two organisms (i.e., including interactions between conspecifics). Fingerprinting: a method used to identify unmarked individuals using natural variation in their physical and/or behavioral appearance. The method works by transforming the images of each individual ...

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“…A number of studies using Drosophila have examined the impact of visual, chemosensory, or thermal cues on navigational decisions (Gomez-Marin et al 2011;Clark et al 2011;Censi et al 2013;Klein et al 2014;Gepner et al 2015;Schulze et al 2015). In these studies, the detailed recording of fly movement parameters with a quantitative, model-supported analysis of the behavior revealed the navigational strategies with which Drosophila negotiates its environment to find food and avoid noxious chemical, heat, or light stimuli.…”

Section: Linking Sensory Stimuli With Behaviormentioning

confidence: 99%

“…Given that their model could predict more than 90% of the saccades, the authors concluded that the majority of flight decisions in their arena was driven by visual cues. (Gomez-Marin et al 2011) used behavioral manipulation and computational modeling to show how Drosophila larvae find the source of an attractive odorant. The first step in understanding the computations underlying this behavior was to reconstruct the larva's sensory environment -in this case the concentration of odorants at the chemosensory organ in the head.…”

Section: Linking Sensory Stimuli With Behaviormentioning

confidence: 99%

The use of computational modeling to link sensory processing with behavior in Drosophila

Clemens

Murthy

2017

Preprint

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A major goal of systems neuroscience is to understand how the brain represents information, and how those representations are used to drive behavior. Even though genetic model organisms like Drosophila grant unprecedented experimental access to the nervous system for manipulating and recording neural activity, the complexity of natural stimuli and natural behaviors still poses a challenge for solving the connections between neural activity and behavior. Here, we advocate for the use of computational modeling to complement (and enhance) the Drosophila toolkit. We first lay out a modelling framework for making sense of the relation between natural sensory stimuli, neuronal responses, and natural behavior. We then highlight how this framework can be used to reveal how neural circuits drive behavior, using selected case studies.PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2720v1 | CC BY 4.0 Open Access |

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Active sampling and decision making in Drosophila chemotaxis

Cited by 236 publications

References 40 publications

Rats track odour trails accurately using a multi-layered strategy with near-optimal sampling

Rats track odour trails accurately using a multi-layered strategy with near-optimal sampling

Automated image-based tracking and its application in ecology

The use of computational modeling to link sensory processing with behavior in Drosophila

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