Category Archives: Progress

Papers published

Two papers describing and modelling the behaviour of the larva have been recently published by UEDIN: A Model of Drosophila Larva Chemotaxis A Davies, M Louis, B Webb PLoS Comput Biol 11 (11), e1004606 Searching for motifs in the behaviour … Continue reading

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Lego Drosophila Larval Robot in Gradient

This is a short video of a Lego Drosophila larval robot in gradient. The light gradient in video was interpreted as odour gradient.

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Periodic Review

The publishable summary from our successful periodic review is available here.

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Magdeburg Update – December 2014

Impact of memory expression on larval chemotaxis We are working on a joint publication with Matthieu Louis and Sam Reid from the CRG. We analyze learned and innate olfactory behavior and propose a model of how an olfactory memory is … Continue reading

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Edinburgh update – November 2014

From perception to behaviour Initially scaled a drosophila adult spiking network (Wessnitzer et al. 2012) to larva size by collecting known data on the number of ORNs, projection neurons and Kenyon cells. Verified it can display conditioning with a simple … Continue reading

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What can larvae do?

State of the art: Drosophila melanogaster is a small fly that has been used as one of the major biological research tools for around 100 years; much of what we know about genetics, neuroscience and development, and now learning, comes from this … Continue reading

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How do larvae do it?

State of the art: To bridge the gap between cognitive learning capabilities and neural circuits, we need to understand behavioural control. We can tackle this directly in the larvae. Placed on an agarose substrate in a petri-dish (as is the standard situation … Continue reading

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Learning architectures for robot control

State of the art: Many architectures have been proposed for robot control that combine innate, low-level sensorimotor controllers with learning mechanisms to refine the behaviour. Perhaps most widely deployed are ‘hybrid’ architectures, in which the upper layers use explicit knowledge representation and … Continue reading

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