News & Press Releases

Networking during the Virtual physiological human conference (VPH) on 1-4 September, Milan

EBRAINS at VPH 2026: From computational modelling to Virtual Human Twins

EBRAINS participated in VPH 2026 in Milan, from 1–4 September 2026, represented by Giacomo Preti from Aix-Marseille University (AMU). The event brought together researchers, clinicians, engineers and industry representatives working on Virtual Physiological Human approaches and computational modelling in healthcare.

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Thomas Skordas, Deputy Director-General of DG CONNECT, opens the Second Annual EDIC Gathering.

EBRAINS joins the Second Annual EDIC Gathering in Brussels

On 30 September 2026, EBRAINS participated in the Second Annual EDIC Gathering, organised by the European Commission’s Directorate-General for Communications Networks, Content and Technology (DG CONNECT) in Brussels.

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Viktor Jirsa delivering his lecture at PNC in Padova

From brain maps to brain twins

How can we move from describing the brain to understanding - and eventually predicting - its individual dynamics?

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Cover of Stroke Journal

Looking at the brain’s “disconnectome” can predict recovery in severe forms of stroke

A new study in the journal Stroke now suggests that looking at disrupted brain connections can predict how patients who survived a basilar artery occlusion will recover.

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BrainScaleS

A new way to find the parameters for analogue neurons

Programming analogue neuromorphic hardware can be challenging because the behaviour of its artificial neurons depends on many physical parameters.

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Schematic

Using noise to regulate information flow in neural networks

Researchers have developed a learning mechanism that uses the natural variability of neural activity — often dismissed as random “noise” — to understand how synapses buried deep inside brain networks — or brain-inspired devices — can adapt to improve the learning capabilities of the networks as a whole.

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Image of the BrainScaleS-2 multi-chip system

Scaling up BrainScaleS-2: connecting neuromorphic chips for larger networks

A single BrainScaleS-2 chip can emulate hundreds of neurons and more than 130,000 synaptic connections. But to study larger and more complex neural networks, researchers need to connect many such chips and make them work in unison.

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Image of a scientist using a microscope

EBRAINS endorses new EU Charter to boost industry access to research infrastructures

EBRAINS has endorsed the Charter of Access for Industrial Users to Research and Technology Infrastructures, adopted by the European Commission to speed up and simplify companies' access to Europe's world-class research and technology infrastructures.

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Joint Declaration Teaser Image

EBRAINS endorses Joint Declaration on Advancing Neurological Health

EBRAINS has endorsed the Joint Declaration on Advancing Neurological Health, adding its support to the call for coordinated European action on neurological health during Ireland's Presidency of the Council of the European Union.

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Image of owl figure and servo motor

From sound to movement: BrainScaleS-2 processes analogue signals in real time

Two microphones hear a sound. A small owl turns towards it. Behind this simple demonstration is a neuromorphic computing system that processes the microphone signals directly in analogue form and uses the result to control a motor in real time.

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EBRAINS Logo

Discover EBRAINS Support for EuroHPC Applications

EBRAINS Support for EuroHPC Applications offers a dedicated consultancy service to assist users from the neuroscience community, particularly those within the EBRAINS community, in preparing competitive project proposals for the calls of the European High‑Performance Computing Joint Undertaking.

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Brain activity stimulation - Adobe Stock

New study helps explain why brain stimulation responses vary

Brain stimulation can produce very different effects at different moments, even when the stimulus is delivered the exact same way. A new study published in Brain Stimulation, based on detailed EBRAINS-hosted brain data, shows that the brain’s ongoing activity before stimulation can predict much of this variability.

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