neuroscience

In this talk I present how our anatomically accurate incentive circuit predicts the responses of mushroom body neurons from the fruit fly brain and how they can be used to create similar behaviour to the one observed in the animals.

We test the performance of the incentive circuit in the visual place recognition task and suggest that the familiarity must increase along a familiar route. Additionally, PCA whitenning and combinatorial encoding techniques enhanced the separability of visual scenes. The familiarity could be used as input to the central complex for visual homing.

The goal of the project is to develop nanophotonic on-chip devices for integrated sensing and neural computation, inspired by the insect brain.

We present how our novel dopaminergic learning rule and the incentive circuit predict the responses of mushroom body neurons from the fruit fly brain and create similar behaviour to the one observed in the animals.

Modelling differential roles for identified dopaminergic and output neurons of the fruit-fly mushroom bodies combined with a novel dopaminergic plasticity rule explains neural and behavioural phenomena in olfactory learning tasks.

In this poster we show how our anatomically accurate incentive circuit predicts the responses of mushroom body neurons from the fruit fly brain and how they can be used to create similar behaviour to the one observed in the animals.

In this talk we present our recent work building an anatomically accurate neural circuit that allow memory dynamics in the fruit-fly brain.

We propose a new hypothesis for how insects process polarised skylight to extract global orientation information that can be used for accurate path integration. Our model solves the problem of solar-antisolar meridian ambiguity by using a biologically constrained sensor array, and includes methods to deal with tilt and time, providing a complete insect celestial compass output. We analyse the performance of the model using a realistic sky simulation and various forms of disturbances, and compare the results to both engineering approaches and biological data.

Thesis - Doctor of Philosophy. I inversigated how insects form associative memories in their mushroom bodies and how this impacts their olfactory learning, visual navigation, and time-delayed reinforcements tasks.

We develop a new foundation for understanding natural learning by developing a complete multilevel model of learning in larvae