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NEUREKA consortium partners LAAS-CNRS recently published a new article in Advanced Materials about their work in NEUREKA.

Guilhem Larrieu and co-workers demonstrate a precision-controlled electrodeposition of PEDOT:PSS onto 3D nanowire electrodes, yielding remarkable improvements in electrochemical performance for neural interface applications. This nanoscale-controlled coating substantially reduces interface impedance and enhances stimulation capability compared with conventional metallic coatings.

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Last week, the NEUREKA project partners gathered in Padova for its Consortium Meeting. The meeting provided an opportunity for the partners to discuss the overall advancement of the project and delve into the specifics of each Work Package. With discussions and planning sessions, the consortium members charted the course for the next steps of the project.

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Welcome back to our series involving online interviews of our main partners from the Neureka Consortium, where they get the chance to tell us a little bit about their expertise and contributions towards this multi-national project.

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Join us on 12 May 2023 at 15:00 for a fascinating presentation by Dr. Panayiota Poirazi, coordinator of the NEUREKA project, on “Learning with dendrites in brains and machines” at UNIPD VIMM Institute. Don’t miss the opportunity to learn about the Neureka project including computational modelling and dendritic function. 

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Don’t miss the chance to attend the 3rd In-Vitro 2D & 3D Neuronal Networks Summit from May 15 – 17 in Zurich, Switzerland, hosted by MaxWell Biosystems, one of the NEUREKA grant consortium partners

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One of the grant consortium partners for the NEUREKA project, Marco Fanciulli’s group at UNIMIB, has recently published a new article in Nanomaterials journal, with Valerio Di Palma as the first author, a talented member of Marco Fanciulli’s group.

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Researchers at the Poirazi Lab at FORTH (A NEUREKA partner) have developed new software that allows the incorporation of important dendritic properties into neural network models. Such models advance our understanding of brain function and lead to new artificial intelligence systems.

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