an electric Contrast medium for computationally intensive Electroencephalographies for high REsolution BRain imaging withOut skull trepanation

Project Information

CEREBRO

Grant agreement ID: 101046748

DOI

10.3030/101046748

EC signature date 3 March 2022

Start date 1 September 2022

End date 31 August 2026

Funded under

• The European Innovation Council (EIC)

Total cost

€ 2 498 688,00

EU contribution

€ 2 498 688,00

Coordinated by

POLITECNICO DI TORINO
Italy

Periodic Reporting for period 2 - CEREBRO (an electric Contrast medium for computationally intensive Electroencephalographies for high REsolution BRain imaging withOut skull trepanation)

Reporting period: 2023-09-01 to 2025-02-28

Summary of the context and overall objectives of the project

Imaging the brain activity is fundamentally important for many brain-related scientific disciplines. Among the non-invasive neuroimaging strategies, Electroencephalography (EEG) from scalp potentials is one of the primary. In EEG the neuroninduced electric potential is measured by using electrodes on the patient’s scalp. The skull however, highly resistive, shields EEG recordings limiting the spatial resolution. The standard way to avoid skull shielding effects is to invasively implant EEG electrodes under the skull (ECoG) or in the brain cortex (StereoEEG), in both cases after trepanning the patient’s skull. Scalp EEGs are noninvasive but lack spatial imaging accuracy. ECoG and StereoEEG are highly accurate but require skull trepanation and they image only a limited part of the brain. There is the need for increasing the resolution of scalp EEG providing the same level of accuracy of invasive EEGs. This will be the grand challenge which CEREBRO will achieve by conceiving the first ever existing EEG contrast medium, able to provide imaging of the entire brain and in a non-invasive way.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

The project has advanced steadily towards its main goals and delivered several important outcomes:

WP1: The consortium focused on transforming the contrast-medium concept into practical, testable prototypes, combining electronic particle designs with complementary nanoparticle options. A compact CMOS front-end architecture was defined, and several circuit variants were prepared for prototype production. Two powering strategies were pursued in parallel — fully wireless operation and a catheter-supported backup — to maximise flexibility for upcoming trials. Among the circuit approaches, a digital-based amplifier was introduced as a space-saving solution that integrates upconversion without the need for a separate oscillator. Simulations and block-level validations confirmed that voltage-to-frequency conversion and propagation through realistic head models are feasible at very low power consumption. Bench experiments with nonlinear components further demonstrated the possibility of translating low-frequency neural activity into higher-frequency bands that can be more reliably detected externally. In parallel, a nanoparticle pathway was explored, centred on elongated magnetic nanorods designed to rotate under controlled fields and thereby generate spectral replicas of neural signals. Material choices, actuation strategies and multiphysics simulations were investigated to establish safe and practical parameters for prototype development.

WP2: Work in this package has advanced the modelling and imaging framework that underpins the use of the contrast medium. A major achievement has been the derivation of a new Calderón-type broadband forward solver that remains accurate and fast across the entire frequency band of interest. The solver is well-conditioned and avoids catastrophic loss of accuracy, regardless of the resolution or complexity of the head model, marking a clear step beyond the state of the art. It now serves as the foundation for multi-frequency imaging experiments, generating realistic synthetic data and supporting subject-specific digital twins. Multi-frequency reconstruction strategies were tested and shown to improve source separability compared with single-frequency methods. Complementary segmentation and data-preparation tools were created to enable robust end-to-end simulations. Initial choices for stable inversion strategies have been identified and are being refined in view of upcoming experiments. The complete modelling and imaging pipeline has been integrated with the prototyping platform.

WP3: A rapid prototyping and testbed infrastructure has been established and is now fully operational across the consortium. The platform brings together hardware and software in a common environment, enabling multi-channel data. Circuit prototypes and frequency-upconversion concepts have already been exercised in bench experiments, providing early validation of their performance. By connecting circuits, particles and imaging algorithms in a single workflow, the testbed accelerates iteration and makes it possible to characterise practical detectability and complete signal chains. It also supports trials with rotating particles and integration with anatomically realistic phantoms, creating a bridge between design and experimental validation.

WP4: Experimental validation moved forward through the creation of anatomically realistic phantoms that reproduce both the geometry and electrical properties of the head. Layered and active phantoms were fabricated, carefully characterised, and used in imaging experiments to test the full acquisition and reconstruction chain. In parallel, vascular mock-ups and microfluidic channels were developed to study how particles behave under realistic flow conditions. Injection and flow experiments provided early evidence of particle retention and movement in vessel-like geometries, offering valuable insight for the design of both circuits and nanoparticles. These phantoms and mock-ups now serve as essential tools for validating readout strategies and inversion workflows.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

In the first 30 months of the project, we have achieved a number of advancements that substantially went beyond the current state of the art, including the following points.

1) We have obtained the first brain modeller, based on new Calderón-type forward solvers that remains accurate and fast (well-conditioned and free from catastrophic loss of accuracies) for the whole frequency band of interest, regardless of the resolution and complexity of the head model. The new approach is expected to have a significant impact on this project and beyond, and its exploitation is currently under investigation.

2) A fast prototyping platform has been designed and realized. This platform allows rapid testing of new particle concepts, circuits and imaging algorithms under realistic conditions. It integrates hardware and software in a common test environment, enabling multi-channel data acquisition and real-time processing. By standardizing measurements, it makes it possible to compare different readout strategies quickly and reliably. It shortens the development cycle, accelerates feedback between design and experiment, and provides a reusable infrastructure that will remain valuable beyond the project.

3) We have developed innovative designs for EEG contrast media, the realization of which represents the core breakthrough of CEREBRO. Our approach explores two complementary pathways. The first is a circuit-based strategy, leveraging ultra-compact CMOS front-ends and on-chip upconversion variants. In parallel, a passive nanoparticle strategy employs elongated magnetic nanorods, whose controlled rotation in a magnetic field modulates local conductivity and generates predictable spectral replicas of neural signals. Together, these two approaches expand the design space for non-invasive EEG contrast media, enable clearer spectral separation of brain activity, and allow rapid, phantom-based benchmarking.

4) Bench experiments on upconversion and nonlinear conversion, using prototype diodes and upconverter front-end concepts, provide first-ever practical evidence that low-frequency neural signals can be translated into higher-frequency bands with well-defined sidebands, enhancing the robustness of external readout.