Learning steers the ontogeny of an efficient hunting sequence in zebrafish larvae.

Goal-directed behaviors may be poorly coordinated in young animals but, with age and experience, behavior progressively adapts to efficiently exploit the animal's ecological niche. How experience impinges on the developing neural circuits of behavior is an open question. We have conducted a detailed study of the effects of experience on the ontogeny of hunting behavior in larval zebrafish.

Modelling the mechanics of exploration in larval Drosophila.

The Drosophila larva executes a stereotypical exploratory routine that appears to consist of stochastic alternation between straight peristaltic crawling and reorientation events through lateral bending. We present a model of larval mechanics for axial and transverse motion over a planar substrate, and use it to develop a simple, reflexive neuromuscular model from physical principles. The mechanical model represents the midline of the larva as a set of point masses which interact with each other via damped translational and torsional springs, and with the environment via sliding friction forces.

Monitoring brain activity and behaviour in freely moving Drosophila larvae using bioluminescence.

We present a bioluminescence method, based on the calcium-reporter Aequorin (AEQ), that exploits targeted transgenic expression patterns to identify activity of specific neural groups in the larval Drosophila nervous system. We first refine, for intact but constrained larva, the choice of Aequorin transgene and method of delivery of the co-factor coelenterazine and assay the luminescence signal produced for different neural expression patterns and concentrations of co-factor, using standard photo-counting techniques. We then develop an apparatus that allows simultaneous measurement of this neural signal while video recording the crawling path of an unconstrained animal.

Continuous lateral oscillations as a core mechanism for taxis in larvae.

Taxis behaviour in larva is thought to consist of distinct control mechanisms triggering specific actions. Here, we support a simpler hypothesis: that taxis results from direct sensory modulation of continuous lateral oscillations of the anterior body, sparing the need for 'action selection'. Our analysis of larvae motion reveals a rhythmic, continuous lateral oscillation of the anterior body, encompassing all head-sweeps, small or large, without breaking the oscillatory rhythm.

Using an Insect Mushroom Body Circuit to Encode Route Memory in Complex Natural Environments.

Ants, like many other animals, use visual memory to follow extended routes through complex environments, but it is unknown how their small brains implement this capability. The mushroom body neuropils have been identified as a crucial memory circuit in the insect brain, but their function has mostly been explored for simple olfactory association tasks. We show that a spiking neural model of this circuit originally developed to describe fruitfly (Drosophila melanogaster) olfactory association, can also account for the ability of desert ants (Cataglyphis velox) to rapidly learn visual routes through complex natural environments.

The rise and fall of memory in a model of synaptic integration.

Plasticity-inducing stimuli must typically be presented many times before synaptic plasticity is expressed, perhaps because induction signals gradually accumulate before overt strength changes occur. We consider memory dynamics in a mathematical model with synapses that integrate plasticity induction signals before expressing plasticity. We find that the memory trace initially rises before reaching a maximum and then falling.

Taming fluctuations in a stochastic model of spike-timing-dependent plasticity.

A stochastic model of spike-timing-dependent plasticity proposes that single synapses express fixed-amplitude jumps in strength, the amplitudes being independent of the spike time difference. However, the probability that a jump in strength occurs does depend on spike timing. Although the model has a number of desirable features, the stochasticity of response of a synapse introduces potentially large fluctuations into changes in synaptic strength.