Unit

Prof. Ramdya Group

Laboratory
Summary

The Neuroengineering Laboratory, led by Prof. Ramdya at EPFL, focuses on reverse-engineering the fly, Drosophila melanogaster, to understand how animals process social information, learn about their environment, and exhibit flexible motor behaviors. By combining microscopy, machine learning, genetics, and computational modeling, the lab aims to uncover insights into biological intelligence that can enhance the design of artificial systems and robots. Recent research includes establishing links between neural activity and behavior, developing a neuromechanical model of the fly, recording neural activity during behavior, using deep networks for behavior quantification, and building robotic systems for experimental automation.

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Related publications (32)

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Alexander Mathis, Alberto Silvio Chiappa, Alessandro Marin Vargas, Axel Bisi

Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...
EPFL Infoscience2024

Task-driven neural network models predict neural dynamics of proprioception

Alexander Mathis, Alberto Silvio Chiappa, Alessandro Marin Vargas, Axel Bisi

Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...
2023

Supervised learning and inference of spiking neural networks with temporal coding

Ana Stanojevic

The way biological brains carry out advanced yet extremely energy efficient signal processing remains both fascinating and unintelligible. It is known however that at least some areas of the brain perform fast and low-cost processing relying only on a smal ...
EPFL2023
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