Thibault Honegger

Host institution: CNRS

Laboratory: LTM

Call for projects: Starting (PE7)

Project Name: CONNEXIO – Physiologically Relevant Microfluidic Neuroengineering

Amount: €1.72 million

Description :

Developing minimalist biological neural networks and observing their functional activity is crucial for deciphering information processing in the brain.

This project aims to address two major challenges: to design and fabricate in vitro biological neural networks organized in physiologically relevant ways and to provide a label-free monitoring platform capable of observing neuronal activity both at the resolution of neurons and large fields of vision.

To do so, the project is developing unique microfluidic compartmentalized chips where populations of primary neurons will be seeded into deposition chambers with physiologically relevant numbers and densities.

The chambers will be connected by micro-grooves in which only the neurites can develop and whose dimensions will be adjusted according to the transmission scheme to be reproduced.

To observe the activity of these complex neural networks, we are developing a disruptive observation technique that will translate the electrical activity of spiking neurons into optical differences reflected on a lens-less, calcium-label-free, always-incubo platform.

By combining neuroengineering patterning and the lensless platform, we compare individual spikes to global oscillators in basic neural networks under localized external stimuli.

Such findings provide experimental insight into current approaches to computational neuroscience.

Finally, we will design an in vitro network that will reproduce a neural loop implicated in the main neurodegenerative diseases with physiologically applicable neuronal types, densities and connectivities.

This circuit will be manipulated in order to model Huntington’s and Parkinson’s diseases on the chip and to evaluate the impact of known drugs on the functional activity of the entire network.

This project will design microfluidic chips with a physiologically relevant neural network and a lensless activity monitoring platform to address fundamental and clinically relevant problems in neuroscience.